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Guo Z, Wu Q, Wang X, Dai Y, Ma Y, Qiu Y, Zhang Y, Wang X, Jin J. Effects of message framing and risk perception on health communication for optimum cardiovascular disease primary prevention: a protocol for a multicenter randomized controlled study. Front Public Health 2024; 12:1308745. [PMID: 38550324 PMCID: PMC10972929 DOI: 10.3389/fpubh.2024.1308745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 03/04/2024] [Indexed: 04/02/2024] Open
Abstract
Background Although several guidelines for cardiovascular disease (CVD) management have highlighted the significance of primary prevention, the execution and adherence to lifestyle modifications and preventive medication interventions are insufficient in everyday clinical practice. The utilization of effective risk communication can assist individuals in shaping their perception of CVD risk, motivating them to make lifestyle changes, and increasing their willingness to engage with preventive medication, ultimately reducing their CVD risks and potential future events. However, there is limited evidence available regarding the optimal format and content of CVD risk communication. Objective The pilot study aims to elucidate the most effective risk communication strategy, utilizing message framing (gain-framed, loss-framed, or no-framed), for distinct subgroups of risk perception (under-perceived, over-perceived, and correctly-perceived CVD risk) through a multi-center randomized controlled trial design. Methods A multi-center 3 × 3 factorial, observer-blinded experimental design was conducted. The participants will be assigned into three message-framing arms randomly in a 1:1:1 ratio and will receive an 8-week intervention online. Participants are aged 20-80 years old and have a 10-year risk of absolute CVD risk of at least 5% (moderate risk or above). We plan to enroll 240 participants based on the sample calculation. The primary outcome is the CVD prevention behaviors and CVD absolute risk value. Data collection will occur at baseline, post-intervention, and 3-month follow-up. Discussion This experimental study will expect to determine the optimal matching strategy between risk perception subgroups and risk information format, and it has the potential to offer health providers in community or clinic settings a dependable and efficient health communication information template for conducting CVD risk management.Clinical trial registration: https://www.chictr.org.cn/bin/project/edit?pid=207811, ChiCTR2300076337.
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Affiliation(s)
- Zhiting Guo
- Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine (SAHZU), Hangzhou, China
- Faculty of Nursing, Zhejiang University School of Medicine, Hangzhou, China
| | - Qunhua Wu
- Referral Office, The People’s No.3 Hospital of Hangzhou Xiaoshan, Hangzhou, China
| | - Xiaomei Wang
- School of Media, Hangzhou City University, Hangzhou, China
| | - Yuehua Dai
- Office of Chronic Disease Management, Nanxing Community Health Service Center, Hangzhou, China
| | - Yajun Ma
- Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine (SAHZU), Hangzhou, China
- Faculty of Nursing, Zhejiang University School of Medicine, Hangzhou, China
| | - YunJing Qiu
- School of Nursing and Midwifery, Faculty of Health, University of Technology Sydney, Sydney, NSW, Australia
| | - Yuping Zhang
- Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine (SAHZU), Hangzhou, China
| | - Xuyang Wang
- Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine (SAHZU), Hangzhou, China
- Faculty of Nursing, Zhejiang University School of Medicine, Hangzhou, China
| | - Jingfen Jin
- Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine (SAHZU), Hangzhou, China
- Key Laboratory of the Diagnosis and Treatment of Severe Trauma and Burn of Zhejiang Province, Hangzhou, China
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Zhao K, Shen X, Liu H, Lin Z, Li J, Chen S, Liu F, Huang K, Cao J, Liu X, Shen C, Yu L, Zhao Y, Zhao L, Li Y, Hu D, Huang J, Lu X, Gu D. Somatic and Germline Variants and Coronary Heart Disease in a Chinese Population. JAMA Cardiol 2024; 9:233-242. [PMID: 38198131 PMCID: PMC10782380 DOI: 10.1001/jamacardio.2023.5095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 10/03/2023] [Indexed: 01/11/2024]
Abstract
Importance The genetic basis of coronary heart disease (CHD) has expanded from a germline to somatic genome, including clonal hematopoiesis of indeterminate potential (CHIP). How CHIP confers CHD risk in East Asian individuals, especially those with small clones (variant allele fraction [VAF] 0.5%-2%) and different genetic backgrounds, was completely unknown. Objective To investigate the CHIP profile in a general Chinese cohort by deep sequencing and further explore the association between CHIP and incident CHD considering germline predisposition. Design, Setting, and Participants This cohort study used data from 3 prospective cohorts in the project Prediction for Atherosclerotic Cardiovascular Disease Risk in China. Participants without cardiovascular disease or cancer at baseline were enrolled in 2001 and 2008 and had a median follow-up of 12.17 years extending into 2021. Exposures CHIP mutations were detected by targeted sequencing (mean depth, 916×). A predefined CHD polygenic risk score (PRS) comprising 531 variants was used to evaluate germline predisposition. Main Outcomes and Measures The main outcome was first incident CHD. Results Among 6181 participants, the median (IQR) age was 53.83 years (45.35-62.39 years); 3082 participants (49.9%) were female, and 3099 (50.1%) were male. A total of 1100 individuals (17.80%) harbored 1372 CHIP mutations at baseline. CHIP was independently associated with incident CHD (hazard ratio [HR], 1.42; 95% CI, 1.18-1.72; P = 2.82 × 10-4) and presented a risk gradient with increasing VAF (P = 3.98 × 10-3 for trend). Notably, individuals with small clones, nearly half of CHIP carriers, also demonstrated a higher CHD risk compared with non-CHIP carriers (HR, 1.33; 95% CI, 1.02-1.74; P = .03) and were 4 years younger than those with VAF of 2% or greater (median age, 58.52 vs 62.70 years). Heightened CHD risk was not observed among CHIP carriers with low PRS (HR, 1.02; 95% CI, 0.64-1.64; P = .92), while high PRS and CHIP jointly contributed a 2.23-fold increase in risk (95% CI, 1.51-3.29; P = 6.29 × 10-5) compared with non-CHIP carriers with low PRS. Interestingly, the diversity in CHIP-related CHD risk within each PRS group was substantially diminished when removing variants in the inflammatory pathway from the PRS. Conclusions This study revealed that elevated CHD risk attributed to CHIP was nonnegligible even for small clones. Inflammation genes involved in CHD could aggravate or abrogate CHIP-related CHD risk.
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Affiliation(s)
- Kun Zhao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xuxiang Shen
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hongwei Liu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhennan Lin
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianxin Li
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shufeng Chen
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fangchao Liu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Keyong Huang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie Cao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People’s Hospital and Cardiovascular Institute, Guangzhou, China
| | - Chong Shen
- Department of Epidemiology and Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ling Yu
- Department of Cardiology, Fujian Provincial Hospital, Fuzhou, China
| | - Yingxin Zhao
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, China
| | - Liancheng Zhao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ying Li
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, China
| | - Jiangfeng Huang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiangfeng Lu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dongfeng Gu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- School of Public Health and Emergency Management, School of Medicine, Southern University of Science and Technology, Shenzhen, China
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103
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Song C, Ouyang F, Ma T, Gong L, Cheng X, Bai Y. Parental cardiometabolic multimorbidity and subsequent cardiovascular incidence in middle-aged adults: A prospective cohort study. SSM Popul Health 2024; 25:101634. [PMID: 38434445 PMCID: PMC10907827 DOI: 10.1016/j.ssmph.2024.101634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 02/15/2024] [Accepted: 02/15/2024] [Indexed: 03/05/2024] Open
Abstract
Background The prevalence of cardiometabolic multimorbidity, defined as the coexistence of two or three cardiometabolic diseases (CMDs), including coronary heart disease (CHD), diabetes, and stroke, has increased rapidly in recent years, but the additive association between parental cardiometabolic multimorbidity and cardiovascular incidence in middle-aged adults remains unclear. Methods All the data analysed in this study were derived from the UK Biobank, and a total of 71,923 participants aged 40-55 years old without CVD were included in the main analyses. A weighted score was developed and grouped participants into four parental CMDs patterns: non-CMD, low burden, middle burden, and high burden. Cox proportional hazard models were used to estimate the associations between parental CMDs pattern and CVD incidence before 65 years old. Improvement in CVD risk prediction by adding parental CMDs pattern to a basic model was evaluated. Results Among the 71,923 participants, 3070 CVD events were observed during a median 12.04 years of follow-up. Compared to non-CMD groups, adults in high burden group had a 94% (73-117%) increased risk of CVD. The restricted cubic spline analysis revealed an exposure-response association between parental CMDs burden and risk of CVD (Pnonlinear = 0.24). Additionally, models involving parental CMDs pattern showed slightly improvements in CVD risk prediction, especially for CHD. Conclusion An increased burden of parental CMDs was associated with an increased risk of CVD incidence in middle-aged adults. Parental CMDs pattern may provide valuable information in primary prevention of CVD in middle-aged adults.
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Affiliation(s)
- Chao Song
- Infection Control Center, Xiangya Hospital, Central South University, Changsha, China
| | - Feiyun Ouyang
- Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China
| | - Tianqi Ma
- Department of Geriatric Medicine, Center of Coronary Circulation, Xiangya Hospital, Central South University, Changsha, China
| | - Li Gong
- Department of Cardiovascular Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Xunjie Cheng
- Department of Geriatric Medicine, Center of Coronary Circulation, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Yongping Bai
- Department of Geriatric Medicine, Center of Coronary Circulation, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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Yue X, Chen L, Shi Y, Suo Y, Liao S, Cheang I, Gao R, Zhu X, Zhou Y, Yao W, Sheng Y, Kong X, Li X, Zhang H. Comparison of arterial stiffness indices measured by pulse wave velocity and pulse wave analysis for predicting cardiovascular and all-cause mortality in a Chinese population. Hypertens Res 2024; 47:767-777. [PMID: 38195990 DOI: 10.1038/s41440-023-01552-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 10/31/2023] [Accepted: 11/20/2023] [Indexed: 01/11/2024]
Abstract
Arterial stiffness measured by pulse wave velocity and pulse wave analysis has been widely studied in different populations in terms of its correlation with cardiovascular events and all-cause mortality. It remains unknown which arterial stiffness index is better for risk stratification in the general population. We included 4129 participants from Gaoyou County, Jiangsu Province, China, with a median follow-up of 11 years. The primary endpoint was cardiovascular mortality, and the secondary endpoint was all-cause mortality. Harrell's C-index, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) based on the Cox proportional hazards regression model were evaluated to assess predictive discrimination and accuracy. The associations between the 4 indices and cardiovascular mortality remained significant after adjusting for the Framingham Risk Score (FRS) and/or associated risk factors. Considering reclassification based on the newly integrated models (FRS model combined with the 4 indices), NRI for cardiovascular mortality showed that haPWV and baPWV had more significant improvement in reclassification compared with C1 and C2 [NRI with 95% CI: haPWV 0.410 (0.293, 0.523); baPWV 0.447 (0.330, 0.553); C1 0.312 (0.182, 0.454); C2 0.328 (0.159, 0.463); all P < 0.05]. This study showed that pulse wave velocity (haPWV and baPWV) provides better discrimination of long-term risk than arterial elasticity indices (C1 and C2) in the general population.
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Affiliation(s)
- Xin Yue
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China
| | - Lu Chen
- Department of Cardiology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Suzhou, 215002, China
| | - Yanping Shi
- Department of Cardiology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Suzhou, 215002, China
| | - Yifang Suo
- Department of Cardiology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Suzhou, 215002, China
| | - Shengen Liao
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China
| | - Iokfai Cheang
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China
| | - Rongrong Gao
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China
| | - Xu Zhu
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China
| | - Yanli Zhou
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China
| | - Wenming Yao
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China
| | - Yanhui Sheng
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China
| | - Xiangqing Kong
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China
| | - Xinli Li
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China
| | - Haifeng Zhang
- Department of Cardiology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Suzhou, 215002, China.
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105
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Ding Y, Zhou Y, Han H, Chen C, Tarasenko Y. Risk Factors of Premature Atherosclerotic Cardiovascular Disease in China: A Longitudinal Analysis of the China Health and Nutrition Survey Cohort. Asia Pac J Public Health 2024; 36:192-201. [PMID: 38247055 DOI: 10.1177/10105395241226525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2024]
Abstract
The burden of premature atherosclerotic cardiovascular disease (ASCVD) has increased rapidly in China. Using the China Health and Nutrition Survey (CHNS) data, we assessed the risk factors of premature ASCVD (age of diagnosis: <55 years for men and <65 years for women). Propensity score matching was used to reduce selection bias. Multivariable Cox proportional-hazards analyses indicated that factors associated with increased risk of premature ASCVD included hypertension (adjusted hazard ratio [HRadj.] = 1.68), obesity (HRadj. = 1.64), and high carbohydrate intake (HRadj. = 1.46). Conversely, participants with medical insurance (HRadj. = 0.42), high urbanization index (HRadj. = 0.53), and high household income (HRadj. = 0.48) had lower risk of premature ASCVD. When comparing premature vs non-premature ASCVD participants, those who were obese (HRadj. = 2.08) or living in more urbanized areas had higher hazards of early onset (HRadj. = 2.29).
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Affiliation(s)
- Yihong Ding
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
| | - Yifan Zhou
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
| | - Hui Han
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
| | - Chen Chen
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China
- Center for Biostatistics, Bioinformatics, and Big Data, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yelena Tarasenko
- Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, GA, USA
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106
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Zhou Z, Liu X, Xian W, Wang Y, Tao J, Xia W. Estimated pulse wave velocity added additional prognostic information in general population: Evidence from National Health and Nutrition Examination Survey (NHANES) 1999-2018. INTERNATIONAL JOURNAL OF CARDIOLOGY. CARDIOVASCULAR RISK AND PREVENTION 2024; 20:200233. [PMID: 38229680 PMCID: PMC10789630 DOI: 10.1016/j.ijcrp.2023.200233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 12/04/2023] [Accepted: 12/21/2023] [Indexed: 01/18/2024]
Abstract
Background As an indicator of arterial stiffness, there is controversy over whether estimated pulse wave velocity (ePWV) add additional prognostic information other than cardiovascular risk factors or traditional risk estimation model in general population. Methods Data from National Health and Nutrition Examination Survey in 1999-2018 was analyzed. Cardiovascular risk factors were collected and Framingham Risk Score (FRS) was calculated. Using all-cause and cardiovascular mortality as outcomes, Cox and restricted cubic spline (RCS) analysis was performed. Receiver operator characteristic (ROC) curves, Harrell's C-statistic and net reclassification index (NRI) analysis were used to assess whether ePWV adds additional predictive value. Results The association between ePWV and outcomes was independent of cardiovascular risk factors (HR = 1.23 [95%CI 1.23-1.50] per m/s for all-cause mortality, and 1.52 [1.30-1.78] for cardiovascular mortality) and FRS (1.22 [1.12-1.32] for all-cause mortality, and 1.32 [1.10-1.59] for cardiovascular mortality). Except for ePWV and all-cause mortality adjusted by FRS, a liner association was found between ePWV and outcomes. For predictive value, the area under ROC and C-index of the model added with ePWV was higher than the one with FRS or risk factors alone (P < 0.01). The elevated ePWV upgraded 1338456 subjects from high-intermediate to high FRS category, and NRI was 3.61 % and 2.62 % for all-cause and cardiovascular deaths, respectively (all P < 0.001). Conclusions In general population, the present study demonstrated the association between ePWV and all-cause, cardiovascular mortality is independent of cardiovascular risk factors and traditional risk estimated model. ePWV also added additional information to them in predicting clinical outcomes.
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Affiliation(s)
- Zhe Zhou
- Department of Hypertension and Vascular Disease, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-Sen University, Guangzhou, China
- National-Guangdong Joint Engineering Laboratory for Diagnosis and Treatment of Vascular Diseases, Guangzhou, China
| | - Xiaoling Liu
- Department of Cardiology, Shantou Central Hospital, China
- Department of Critical Care Medicine, Shantou Central Hospital, China
| | - Wanyong Xian
- The Fourth People's Hospital of Nanhai District of Foshan City, Foshan, China
| | - Yan Wang
- Health Management Center of the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Jun Tao
- Department of Hypertension and Vascular Disease, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-Sen University, Guangzhou, China
- National-Guangdong Joint Engineering Laboratory for Diagnosis and Treatment of Vascular Diseases, Guangzhou, China
| | - Wenhao Xia
- Department of Hypertension and Vascular Disease, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
- NHC Key Laboratory of Assisted Circulation, Sun Yat-Sen University, Guangzhou, China
- National-Guangdong Joint Engineering Laboratory for Diagnosis and Treatment of Vascular Diseases, Guangzhou, China
- Guangxi Hospital Division of the First Affiliated Hospital, Sun Yat-sen University, China
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Tang L, Zeng L. Comparative efficacy of anthropometric indices in predicting 10-year ASCVD risk: insights from NHANES data. Front Cardiovasc Med 2024; 11:1341476. [PMID: 38486705 PMCID: PMC10937732 DOI: 10.3389/fcvm.2024.1341476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 02/20/2024] [Indexed: 03/17/2024] Open
Abstract
Background Cardiovascular diseases remain a leading cause of morbidity and mortality worldwide. Accurately predicting the 10-year risk of Atherosclerotic Cardiovascular Disease (ASCVD) is crucial for timely intervention and management. This study aimed to evaluate the predictive performance of six anthropometric indices in assessing the 10-year ASCVD risk. Methods Utilizing data from the National Health and Nutrition Examination Survey (NHANES) database (1999-2018), the study involved 11,863 participants after applying exclusion criteria. Six anthropometric indices-waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), and waist-to-height0.5 ratio (WHT.5R)-were calculated. The 10-year ASCVD risk was assessed using the 2013 ACC/AHA guidelines & pooled cohort equations model. Participants were divided into two groups based on an ASCVD risk threshold of 7.5%. Statistical analysis included chi-square tests, odds ratios, and receiver operating characteristic (ROC) curves. Results The study found significant differences in baseline characteristics between participants with ASCVD risk less than 7.5% and those with a risk greater than or equal to 7.5%, stratified by gender. In both male and female groups, individuals with higher ASCVD risk exhibited higher age, waist circumference, BMI, and a higher prevalence of health-compromising behaviors. ABSI emerged as the most accurate predictor of ASCVD risk, with the highest area under the curve (AUC) values in both genders. The optimal cut-off values for ABSI was established for effective risk stratification (cut-off value = 0.08). Conclusion The study underscores the importance of anthropometric indices, particularly ABSI, in predicting the 10-year risk of ASCVD. These findings suggest that ABSI, along with other indices, can be instrumental in identifying individuals at higher risk for ASCVD, thereby aiding in early intervention and prevention strategies.
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Affiliation(s)
- Li Tang
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
- West China School of Nursing, Sichuan University, Chengdu, China
| | - Ling Zeng
- Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China
- West China School of Nursing, Sichuan University, Chengdu, China
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Wang B, Yu W, Zhang Z, Jin W, Chen H, Wang L, Xu M, Hou C, Qian Z, Qiu Z, Zhang S. Assessing peptic ulcer risk with the HAMPROW score in the general Chinese population. Sci Rep 2024; 14:4442. [PMID: 38396123 PMCID: PMC10891164 DOI: 10.1038/s41598-024-55224-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 02/21/2024] [Indexed: 02/25/2024] Open
Abstract
The timely identification of individuals at high risk for peptic ulcers (PUs) is vital in preventing gastrointestinal bleeding after antiplatelet therapy. This study was designed to determine PU risk factors and develop a risk assessment model for PU detection in the general Chinese population. In a prospective dataset, clinical data from individuals undergoing gastroscopic evaluation between April 2019 and May 2022 were recorded. PUs were defined as mucosal defects exceeding 5 mm confirmed via gastroscopy. Participants were categorized into development (April 2019 to April 2021) and validation (May 2021 to May 2022) sets based on chronological order. LASSO-derived logistic regression analysis was employed to create a score, which was further validated via temporal validation. A total of 902 patients were ultimately enrolled, 204 (22.6%) of whom had PUs based on endoscopic findings. In the development cohort (n = 631), seven independent risk factors emerged: male sex (OR = 2.35, P = 0.002), white blood cell (WBC) count (OR = 1.16, P = 0.010), red blood cell (RBC) count (OR = 0.49, P < 0.001), globulin level (OR = 0.92, P = 0.004), albumin level (OR = 0.94, P = 0.020), pepsinogen I (PGI) level (OR = 1.01, P < 0.001), and positive Helicobacter pylori (HP) antibody (OR = 2.50, P < 0.001). Using these factors, a nomogram (HAMPROW score [hazard ratio (HP) antibody, albumin, male, PGI, RBC, globulin, and WBC]) was developed for individual PU prediction. The ability of the HAMPROW score to predict survival was confirmed with AUCs of 0.854 (95% CI 0.816-0.891) and 0.833 (95% CI 0.771-0.895) in the development and validation sets, respectively. In conclusion, the HAMPROW score can be used to screen for PUs effectively in the general Chinese population, facilitating personalized early detection of high risk of gastrointestinal bleeding before antiplatelet therapy.
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Affiliation(s)
- Binli Wang
- Department of Neurology, Huzhou Nanxun People's Hospital, Zhejiang Provincial People's Hospital Nanxun District, Huzhou, China
| | - Weitao Yu
- Center for Rehabilitation Medicine, Department of Neurology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China
- The Second School of Clinical Medicine, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Zheyu Zhang
- Department of Neurology, School of Medicine, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Weili Jin
- Department of Gastroenterology, Huzhou Nanxun People's Hospital, Zhejiang Provincial People's Hospital Nanxun District, Huzhou, China
| | - Haojun Chen
- Department of Nephrology, Huzhou Nanxun People's Hospital, Zhejiang Provincial People's Hospital Nanxun District, Huzhou, China
| | - Linfeng Wang
- Department of Science and Education, Huzhou Nanxun People's Hospital, Zhejiang Provincial People's Hospital Nanxun District, Huzhou, China
| | - Min Xu
- Department of Neurology, Huzhou Nanxun People's Hospital, Zhejiang Provincial People's Hospital Nanxun District, Huzhou, China
| | - Chaoqun Hou
- Department of Neurology, Huzhou Nanxun People's Hospital, Zhejiang Provincial People's Hospital Nanxun District, Huzhou, China
| | - Zhiquan Qian
- Department of Neurology, Huzhou Nanxun People's Hospital, Zhejiang Provincial People's Hospital Nanxun District, Huzhou, China
| | - Ziyue Qiu
- Department of Neurology, Huzhou Nanxun People's Hospital, Zhejiang Provincial People's Hospital Nanxun District, Huzhou, China
| | - Sheng Zhang
- Center for Rehabilitation Medicine, Department of Neurology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China.
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Xu T, Lu Y, Chen B, Deng C, Zhang Y, Wang M, Ling H, Huang Y, Yuan J, Jin X, Ruan L, Li T, Zhang CT. Cohort profile for the Tongji Cardiovascular Health Study: a prospective multiomics cohort study. BMJ Open 2024; 14:e074768. [PMID: 38365303 PMCID: PMC10875488 DOI: 10.1136/bmjopen-2023-074768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 01/17/2024] [Indexed: 02/18/2024] Open
Abstract
PURPOSE The Tongji Cardiovascular Health Study aimed to further explore the onset and progression mechanisms of cardiovascular disease (CVD) through a combination of traditional cohort studies and multiomics analysis, including genomics, metabolomics and metagenomics. STUDY DESIGN AND PARTICIPANTS This study included participants aged 20-70 years old from the Geriatric Health Management Centre of Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology. After enrollment, each participant underwent a comprehensive series of traditional and novel cardiovascular risk factor assessments at baseline, including questionnaires, physical examinations, laboratory tests, cardiovascular health assessments and biological sample collection for subsequent multiomics analysis (whole genome sequencing, metabolomics study from blood samples and metagenomics study from stool samples). A biennial follow-up will be performed for 10 years to collect the information above and the outcome data. FINDINGS TO DATE A total of 2601 participants were recruited in this study (73.4% men), with a mean age of 51.5±11.5 years. The most common risk factor is overweight or obesity (54.8%), followed by hypertension (39.7%), hyperlipidaemia (32.4%), current smoking (23.9%) and diabetes (12.3%). Overall, 13.1% and 48.7% of men and women, respectively, did not have any of the CVD risk factors (hypertension, hyperlipidaemia, diabetes, cigarette smoking and overweight or obesity). Additionally, multiomics analyses of a subsample of the participants (n=938) are currently ongoing. FUTURE PLANS With the progress of the cohort follow-up work, it is expected to provide unique multidimensional and longitudinal data on cardiovascular health in China.
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Affiliation(s)
- Ting Xu
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yueqi Lu
- BGI Research, Shenzhen, Guangdong, China
| | | | - Chenxin Deng
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yucong Zhang
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Mei Wang
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Huifen Ling
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yi Huang
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jing Yuan
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xin Jin
- BGI Research, Shenzhen, Guangdong, China
| | - Lei Ruan
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Tao Li
- BGI Research, Shenzhen, Guangdong, China
| | - Cun-Tai Zhang
- Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China
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Xie S, Yu LP, Chen F, Wang Y, Deng RF, Zhang XL, Zhang B. Age-specific differences in the association between prediabetes and cardiovascular diseases in China: A national cross-sectional study. World J Diabetes 2024; 15:240-250. [PMID: 38464373 PMCID: PMC10921163 DOI: 10.4239/wjd.v15.i2.240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/20/2023] [Accepted: 01/22/2024] [Indexed: 02/04/2024] Open
Abstract
BACKGROUND Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide, the global burden of which is rising. It is still unclear the extent to which prediabetes contributes to the risk of CVD in various age brackets among adults. To develop a focused screening plan and treatment for Chinese adults with prediabetes, it is crucial to identify variations in the connection between prediabetes and the risk of CVD based on age. AIM To examine the clinical features of prediabetes and identify risk factors for CVD in different age groups in China. METHODS The cross-sectional study involved a total of 46239 participants from June 2007 through May 2008. A thorough evaluation was conducted. Individuals with prediabetes were categorized into two groups based on age. Chinese atherosclerotic CVD risk prediction model was employed to evaluate the risk of developing CVD over 10 years. Random forest was established in both age groups. SHapley Additive exPlanation method prioritized the importance of features from the perspective of assessment contribution. RESULTS In total, 6948 people were diagnosed with prediabetes in this study. In pre-diabetes, prevalences of CVD were 5 (0.29%) in the younger group and 148 (2.85%) in the older group. Overall, 11.11% of the younger group and 29.59% of the older group were intermediate/high-risk of CVD for prediabetes without CVD based on the Prediction for ASCVD Risk in China equation in ten years. In the younger age group, the 10-year risk of CVD was found to be more closely linked to family history of CVD rather than lifestyle, whereas in the older age group, resident status was more closely linked. CONCLUSION The susceptibility to CVD is age-specific in newly diagnosed prediabetes. It is necessary to develop targeted approaches for the prevention and management of CVD in adults across various age brackets.
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Affiliation(s)
- Shuo Xie
- Department of Endocrinology, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100730, China
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Li-Ping Yu
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Fei Chen
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Yao Wang
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Rui-Fen Deng
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Xue-Lian Zhang
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing 100029, China
| | - Bo Zhang
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing 100029, China
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Liang F, Yang X, Peng W, Zhen S, Cao W, Li Q, Xiao Z, Gong M, Wang Y, Gu D. Applications of digital health approaches for cardiometabolic diseases prevention and management in the Western Pacific region. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2024; 43:100817. [PMID: 38456090 PMCID: PMC10920052 DOI: 10.1016/j.lanwpc.2023.100817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 05/04/2023] [Accepted: 05/23/2023] [Indexed: 03/09/2024]
Abstract
Cardiometabolic diseases (CMDs) are the major types of non-communicable diseases, contributing to huge disease burdens in the Western Pacific region (WPR). The use of digital health (dHealth) technologies, such as wearable gadgets, mobile apps, and artificial intelligence (AI), facilitates interventions for CMDs prevention and treatment. Currently, most studies on dHealth and CMDs in WPR were conducted in a few high- and middle-income countries like Australia, China, Japan, the Republic of Korea, and New Zealand. Evidence indicated that dHealth services promoted early prevention by behavior interventions, and AI-based innovation brought automated diagnosis and clinical decision-support. dHealth brought facilitators for the doctor-patient interplay in the effectiveness, experience, and communication skills during healthcare services, with rapidly development during the pandemic of coronavirus disease 2019. In the future, the improvement of dHealth services in WPR needs to gain more policy support, enhance technology innovation and privacy protection, and perform cost-effectiveness research.
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Affiliation(s)
- Fengchao Liang
- School of Public Health and Emergency Management, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055, People's Republic of China
| | - Xueli Yang
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, 22 Qixiangtai Rd, Tianjin 300070, People's Republic of China
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, 22 Qixiangtai Rd, Tianjin 300070, People's Republic of China
| | - Wen Peng
- Nutrition and Health Promotion Center, Department of Public Health, Medical College, Qinghai University, 251 Ningda Road, Xining City 810016, People's Republic of China
- Qinghai Provincial Key Laboratory of Prevention and Control of Glucolipid Metabolic Diseases with Traditional Chinese Medicine, Xining 810008, People's Republic of China
| | - Shihan Zhen
- School of Public Health and Emergency Management, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055, People's Republic of China
| | - Wenzhe Cao
- School of Public Health and Emergency Management, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055, People's Republic of China
| | - Qian Li
- School of Public Health and Emergency Management, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055, People's Republic of China
| | - Zhiyi Xiao
- School of Public Health and Emergency Management, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055, People's Republic of China
| | - Mengchun Gong
- Institute of Health Management, Southern Medical University, No. 1023-1063, Shatai South Road, Guangzhou 510515, People's Republic of China
| | - Youfa Wang
- The First Affiliated Hospital of Xi'an Jiaotong University Public Health Institute, Global Health Institute, School of Public Health, International Obesity and Metabolic Disease Research Center, Xi'an Jiaotong University, Xi'an 710061, People's Republic of China
| | - Dongfeng Gu
- School of Public Health and Emergency Management, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055, People's Republic of China
- School of Medicine, Southern University of Science and Technology, 1088 Xueyuan Avenue, Shenzhen 518055, People's Republic of China
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Dai L, Guo J, Hui X, Wang X, Luo J, Huang R, Xiao Y. The potential interaction between chemosensitivity and the development of cardiovascular disease in obstructive sleep apnea. Sleep Med 2024; 114:266-271. [PMID: 38244464 DOI: 10.1016/j.sleep.2024.01.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Revised: 01/03/2024] [Accepted: 01/07/2024] [Indexed: 01/22/2024]
Abstract
OBJECTIVES Chemosensitivity is an essential part of the pathophysiological mechanisms of obstructive sleep apnea (OSA). Not only does OSA have a certain relationship with the comorbidity of cardiovascular disease (CVD) but also chemosensitivity plays a crucial role in the development of CVD. This study aims to investigate the potential interaction between chemosensitivity and the development of CVD in OSA. METHODS A total of 169 participants with suspected OSA were included. Data were gathered on the parameters of polysomnography and baseline clinical features. Peripheral chemosensitivity was evaluated by employing the rebreathing test. The lifetime CVD risk was computed using the China-PAR (Prediction for atherosclerotic CVD Risk in China) risk equation. RESULTS After controlling for covariates, participants with chemosensitivity levels in the second and fifth quantiles tended to hold an increased proportion of high lifetime CVD risk (OR 10.90, 95%CI [2.81-42.28]; OR 6.78, 95%CI [1.70-27.05], respectively). The diagnosis of OSA would significantly increase the 10-year and lifetime CVD risks in participants with low chemosensitivity, while no such differences were found in participants with high chemosensitivity. CONCLUSION Higher lifetime CVD risk was associated with participants who had greater peripheral chemosensitivity. In terms of the CVD outcomes, adult patients with a relatively low level of chemosensitivity may be primarily related to their diagnosis of OSA, whereas adult patients with a relatively high level of chemosensitivity may be more strongly associated with their elevated levels of chemosensitivity rather than OSA.
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Affiliation(s)
- Lu Dai
- Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Junwei Guo
- Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Xinjie Hui
- Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Xiaona Wang
- Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Jinmei Luo
- Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Rong Huang
- Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Yi Xiao
- Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
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Lim HS, Han H, Won S, Ji S, Park Y, Lee HY. Sex differences in the applicability of Western cardiovascular disease risk prediction equations in the Asian population. PLoS One 2024; 19:e0292067. [PMID: 38295132 PMCID: PMC10830057 DOI: 10.1371/journal.pone.0292067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 09/12/2023] [Indexed: 02/02/2024] Open
Abstract
AIMS Cardiovascular diseases (CVDs) are the most common cause of death, but they can be effectively managed through appropriate prevention and treatment. An important aspect in preventing CVDs is assessing each individual's comprehensive risk profile, for which various risk engines have been developed. The important keys to CVD risk engines are high reliability and accuracy, which show differences in predictability depending on disease status or race. Framingham risk score (FRS) and the atherosclerotic cardiovascular disease risk equations (ASCVD) were applied to the Korean population to assess their suitability. METHODS A retrospective cohort study was conducted using National Health Insurance Corporation sample cohort from 2003 to 2015. The enrolled participants over 30 years of age and without CVD followed-up for 10 years. We compared the prediction performance of FRS and ASCVD and calculated the relative importance of each covariate. RESULTS The AUCs of FRS (men: 0.750; women: 0.748) were higher than those of ASCVD (men: 0.718; women: 0.727) for both sexes (Delong test P <0.01). Goodness of fits (GOF) were poor for all models (Chi-square P < 0.001), especially, underestimation of the risk was pronounced in women. When the men's coefficients were applied to women's data, AUC (0.748; Delong test P<0.01) and the GOF (chi-square P = 0.746) were notably improved in FRS. Hypertension was found to be the most influential variable for CVD, and this is one of the reasons why FRS, having the highest relative weight to blood pressure, showed better performance. CONCLUSION When applying existing tools to Korean women, there was a noticeable underestimation. To accurately predict the risk of CVD, it was more appropriate to use FRS with men's coefficient in women. Moreover, hypertension was found to be a main risk factor for CVD.
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Affiliation(s)
- Hee-Sook Lim
- Department of Gerontology, AgeTech-Service Convergence Major, Graduate School of East-West Medical Science, Kyung Hee University, Yongin, Republic of Korea
| | - Hyein Han
- Department of Public Health Sciences, Seoul National University, Seoul, Republic of Korea
| | - Sungho Won
- Department of Public Health Sciences, Seoul National University, Seoul, Republic of Korea
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
- Institute of Health and Environment, Seoul National University, Seoul, Republic of Korea
- RexSoft Corps, Seoul, Republic of Korea
| | - Sungin Ji
- Department of Preventive Medicine, Soonchunhyang University College of Medicine, Cheonan, Republic of Korea
| | - Yoonhyung Park
- Department of Preventive Medicine, Soonchunhyang University College of Medicine, Cheonan, Republic of Korea
| | - Hae-Young Lee
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
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Yu S, Zheng Y, Dai X, Chen H, Yang S, Ma M, Huang F, Zhu P. The value of coordinated analysis of multimodal atherosclerotic plaque imaging in the assessment of cardiovascular and cerebrovascular events. Front Cardiovasc Med 2024; 11:1320222. [PMID: 38333417 PMCID: PMC10850297 DOI: 10.3389/fcvm.2024.1320222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 01/10/2024] [Indexed: 02/10/2024] Open
Abstract
Background Although atherosclerosis (AS) can affect multiple vascular beds, previous studies have focused on the analysis of single-site AS plaques. Objective The aim of this study is to explore the differences or similarities in the characteristics of atherosclerotic plaque found in the internal carotid artery, cerebral artery, and coronary artery between patients with atherosclerotic cardiovascular disease (ASCVD) and those without events. Methods Patients aged ≥ 18 years who underwent both high-resolution vessel wall imaging (HR-VWI) and coronary computed tomography angiography (CCTA) were retrospectively collected and categorized into the ASCVD group and the non-event group. The plaques were then categorized into culprit plaques, non-culprit plaques, and non-event plaques. Plaque morphological data such as stenosis, stenosis grades, plaque length (PL), plaque volume (PV), minimal lumen area (MLA), enhancement grade, and plaque composition data such as calcified plaque volume (CPV), fibrotic plaque volume (FPV), fibro-lipid plaque volume (FLPV), lipid plaque volume (LPV), calcified plaque volume ratio (CPR), fibrotic plaque volume ratio (FPR), fibro-lipid plaque ratio (FLPR), lipid plaque volume ratio (LPR), intraplaque hemorrhage volume (IPHV), and intraplaque hemorrhage volume ratio (IPHR)were recorded and analyzed. Results A total of 44 patients (mean age 66 years, SD 9 years, 28 men) were included. In cervicocephalic plaques, the ASCVD group had more severe stenosis grades (p = 0.030) and demonstrated significant differences in LPV, LPR, and CPV (p = 0.044, 0.030, 0.020) compared with the non-event group. In coronary plaques, the ASCVD group had plaques with greater stenosis (p < 0.001), more severe stenosis grades (p < 0.001), larger volumes (p = 0.001), longer length (p = 0.008), larger FLPV (p = 0.012), larger FPV (p = 0.002), and higher FPR (p = 0.043) compared with the non-event group. There were significant differences observed in stenosis (HR-VWI, CCTA: p < 0.001, p < 0.001), stenosis grades (HR-VWI, CCTA: p < 0.001, p < 0.001), plaque length (HR-VWI, CCTA: p = 0.028, p < 0.001), and plaque volume (HR-VWI, CCTA: p = 0.013, p = 0.018) between the non-event plaque, non-culprit plaque, and culprit plaque. In the image analysis of HR-VWI, there were differences observed between IPHR (p < 0.001), LPR (p = 0.001), FPV (p = 0.011), and CPV (p = 0.015) among the three groups of plaques. FLPV and FPV were significantly different among the three different plaque types from the coronary artery (p = 0.043, p = 0.022). Conclusion There is a consistent pattern of change in plaque characteristics between the cervicocephalic and coronary arteries in the same patient.
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Affiliation(s)
- Shun Yu
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, Republic of China
- Department of Radiology, Fujian Provincial Hospital, Fuzhou, Fujian, Republic of China
| | - Yonghong Zheng
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, Republic of China
- Department of Radiology, Fujian Provincial Hospital, Fuzhou, Fujian, Republic of China
| | - Xiaomin Dai
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, Republic of China
- Department of Radiology, Fujian Provincial Hospital, Fuzhou, Fujian, Republic of China
| | - Huangjing Chen
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, Republic of China
- Department of Radiology, Fujian Provincial Hospital, Fuzhou, Fujian, Republic of China
| | - Shengsheng Yang
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, Republic of China
- Department of Radiology, Fujian Provincial Hospital, Fuzhou, Fujian, Republic of China
| | - Mingping Ma
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, Republic of China
- Department of Radiology, Fujian Provincial Hospital, Fuzhou, Fujian, Republic of China
| | - Feng Huang
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, Republic of China
- Department of Geriatric Medicine, Fujian Provincial Hospital, Fuzhou, Fujian, Republic of China
- Fujian Key Laboratory of Geriatrics, Fuzhou, Fujian, Republic of China
- Fujian Provincial Center for Geriatrics, Fuzhou, Fujian, Republic of China
| | - Pengli Zhu
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, Republic of China
- Department of Geriatric Medicine, Fujian Provincial Hospital, Fuzhou, Fujian, Republic of China
- Fujian Key Laboratory of Geriatrics, Fuzhou, Fujian, Republic of China
- Fujian Provincial Center for Geriatrics, Fuzhou, Fujian, Republic of China
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Wang Z, Sun Z, Yu L, Wang Z, Li L, Lu X. Machine learning-based prediction of composite risk of cardiovascular events in patients with stable angina pectoris combined with coronary heart disease: development and validation of a clinical prediction model for Chinese patients. Front Pharmacol 2024; 14:1334439. [PMID: 38269285 PMCID: PMC10806135 DOI: 10.3389/fphar.2023.1334439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 12/18/2023] [Indexed: 01/26/2024] Open
Abstract
Objective: To develop a risk score model for the occurrence of composite cardiovascular events (CVE) in patients with stable angina pectoris (SA) combined with coronary heart disease (CHD) by comparing the modeling effects of various machine learning (ML) algorithms. Methods: In this prospective study, 690 patients with SA combined with CHD attending the Department of Integrative Cardiology, China-Japan Friendship Hospital, from October 2020 to October 2021 were included. The data set was randomly divided into a training group and a testing group in a 7:3 ratio in the per-protocol set (PPS). Model variables were screened using the least absolute shrinkage selection operator (LASSO) regression, univariate analysis, and multifactor logistic regression. Then, nine ML algorithms are integrated to build the model and compare the model effects. Individualized risk assessment was performed using the SHapley Additive exPlanation (SHAP) and nomograms, respectively. The model discrimination was evaluated by receiver operating characteristic curve (ROC), the calibration ability of the model was evaluated by calibration plot, and the clinical applicability of the model was evaluated by decision curve analysis (DCA). This study was approved by the Clinical Research Ethics Committee of China-Japan Friendship Hospital (2020-114-K73). Results: 690 patients were eligible to finish the complete follow-up in the PPS. After LASSO screening and multifactorial logistic regression analysis, physical activity level, taking antiplatelets, Traditional Chinese medicine treatment, Gensini score, Seattle Angina Questionnaire (SAQ)-exercise capacity score, and SAQ-anginal stability score were found to be predictors of the occurrence of CVE. The above predictors are modeled, and a comprehensive comparison of the modeling effectiveness of multiple ML algorithms is performed. The results show that the Light Gradient Boosting Machine (LightGBM) model is the best model, with an area under the curve (AUC) of 0.95 (95% CI = 0.91-1.00) for the test set, Accuracy: 0.90, Sensitivity: 0.87, and Specificity: 0.96. Interpretation of the model using SHAP highlighted the Gensini score as the most important predictor. Based on the multifactorial logistic regression modeling, a nomogram, and online calculators have been developed for clinical applications. Conclusion: We developed the LightGBM optimization model and the multifactor logistic regression model, respectively. The model is interpreted using SHAP and nomogram. This provides an option for early prediction of CVE in patients with SA combined with CHD.
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Affiliation(s)
- Zihan Wang
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Ziyi Sun
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Linghua Yu
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Zhitian Wang
- Science Faculty, University of Auckland, Auckland, New Zealand
| | - Lin Li
- Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, China
| | - Xiaoyan Lu
- Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, China
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Huang H, Sun Z, Xu J, Wang L, Zhao J, Li J, Zhang S, Yuan F, Liu M, Fang Z. Yang-Xin-Shu-Mai granule alleviates atherosclerosis by regulating macrophage polarization via the TLR9/MyD88/NF-κB signaling pathway. JOURNAL OF ETHNOPHARMACOLOGY 2024; 318:116868. [PMID: 37454749 DOI: 10.1016/j.jep.2023.116868] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/04/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Previous studies have found that Yang-Xin-Shu-Mai granule (YXSMG) has certain advantages in the treatment of stable coronary heart disease. However, YXSMG can inhibit the progression of atherosclerotic plaque and stabilize vulnerable plaque needs to be further explored and studied. This research, mass spectrometry analysis, network pharmacology, in vivo and in vitro experimental studies were conducted to explore the mechanism of YXSMG on atherosclerosis. AIM OF THE STUDY To decipher the mechanism of atherosclerotic plaque, stabilization for YXSMG by analysis of its active ingredients and biological network and activity in whole animal and at cellular and molecular levels. METHODS The active components of YXSMG were determined using high performance liquid chromatography-mass spectrometry/mass spectrometry (HPLC-MS/MS) analysis. The 'Disease-Compound-Target-Pathway' network diagram was constructed using network pharmacology, and the stability of binding between core targets and core compounds was analyzed with molecular docking. After intervention with YXSMG, the pathology of aortic plaque, inflammation in the surrounding tissue, expression of TLR9/MyD88/NF-κB pathway protein in plaque and M1/M2 polarization of plaque macrophages were evaluated in vivo in apolipoprotein E-deficient (ApoE-/-) mice fed with high-fat diet. To verify whether it suppressed inflammation by inhibiting Toll-like receptor 9 (TLR9) reprogramming of macrophage polarization, we used RAW264.7 macrophages treated with specific TLR9 agonist (ODN1826) and inhibitor (ODN2088). RESULTS Five active compounds were identified in YXSMG: catechin, formononetin, tanshinone IIA, cryptotanshinone and glycitein. Network pharmacology studies revealed TLR9 as one of the core targets of YXSMG intervention in atherosclerosis. Computer simulation of molecular docking showed that TLR9 could interact with the core compound to form a stable complex. In vivo experiments confirmed that YXSMG could significantly inhibit atherosclerotic plaque, reduce levels of blood lipids and inflammatory factors, downregulate TLR9/MyD88/NF-κB pathway protein and inhibit aortic sinus macrophages polarization to M1, but promote their polarization to M2 to inhibit inflammation. In vitro experiments revealed that YXSMG could downregulate expression of TLR9 gene and protein in ODN1826-activated RAW264.7 macrophages. ODN2088 had a synergistic effect with YXSMG on the TLR9/MyD88/NF-κB signaling pathway, and reprogrammed macrophages polarization from M1 to M2 by inhibiting TLR9, thus reducing immuno-inflammatory response. CONCLUSION YXSMG can reduce the level of blood lipid and improve the size of atherosclerotic plaque and inflammatory infiltration in ApoE-/- mice fed with high fat. It is concluded that YXSMG can improve the mechanism of atherosclerotic plaque by inhibiting TLR9/MyD88/NF-κB pathway reprogramming macrophage M1/M2 polarization and reducing arterial inflammation.
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Affiliation(s)
- Hong Huang
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China.
| | - Zeqi Sun
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China.
| | - Junyao Xu
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China
| | - Linjie Wang
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China
| | - Jing Zhao
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China
| | - Jie Li
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China
| | - Siqi Zhang
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China; Institute of Hypertension, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China
| | - Fang Yuan
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China
| | - Ming Liu
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China; Institute of Hypertension, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China.
| | - Zhuyuan Fang
- Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China; Institute of Hypertension, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210029, PR China.
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Suo X, Huang X, Zhong L, Luo Q, Ding L, Xue F. Development and Validation of a Bayesian Network-Based Model for Predicting Coronary Heart Disease Risk From Electronic Health Records. J Am Heart Assoc 2024; 13:e029400. [PMID: 38156626 PMCID: PMC10863831 DOI: 10.1161/jaha.123.029400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 10/04/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND Traditional risk evaluation models have been applied to guide public health and clinical practice in various studies. However, the application of existing methods to data sets with missing and censored data, as is often the case in electronic health records, requires additional considerations. We aimed to develop and validate a predictive model that exhibits high performance with data sets that contain missing and censored data. METHODS AND RESULTS This is a retrospective cohort study of coronary heart disease at Weihai Municipal Hospital on unique patients aged 18 to 96 years between 2013 and 2021. A total of 169 692 participants formed our study population, of which 10 895 participants were diagnosed with coronary heart disease. Models were built for the risk of coronary heart disease based on demographic, laboratory, and medical history variables. All complete samples were assigned to the training set (n=110 325), whereas the remaining samples were assigned to the validation set (n=59 367). The area under the receiver operating characteristic curve value was 0.800 (95% CI, 0.794-0.805), and the C statistic was 0.796 (95% CI, 0.791-0.801) in the derivation cohort, and the corresponding values were 0.837 (95% CI, 0.821-0.853) and 0.838 (95% CI, 0.822-0.854) in the validation cohort. The calibration curve demonstrated its good calibration ability, and decision curve analysis showed its clinical usefulness. CONCLUSIONS Our proposed risk prediction model has demonstrated significant effectiveness in handling the complexities of electronic health record data, which often involve extensive missing data and censoring. This approach may offer potential assistance in the use of electronic health records to enhance patient outcomes.
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Affiliation(s)
- Xiaowen Suo
- Department of BiostatisticsSchool of Public Health, Cheeloo College of Medicine, Shandong UniversityJinanShandongChina
- National Institute of Health Data Science of ChinaJinanShandongChina
| | - Xiaocheng Huang
- Department of Health ExaminationWeihai Municipal Hospital affiliated to Shandong UniversityWeihaiShandongChina
| | - Lu Zhong
- Department of BiostatisticsSchool of Public Health, Cheeloo College of Medicine, Shandong UniversityJinanShandongChina
- National Institute of Health Data Science of ChinaJinanShandongChina
| | - Qingxin Luo
- Department of BiostatisticsSchool of Public Health, Cheeloo College of Medicine, Shandong UniversityJinanShandongChina
- National Institute of Health Data Science of ChinaJinanShandongChina
| | - Lijie Ding
- Department of Health ManagementShandong Sports UniversityJinanShandongChina
| | - Fuzhong Xue
- Department of BiostatisticsSchool of Public Health, Cheeloo College of Medicine, Shandong UniversityJinanShandongChina
- National Institute of Health Data Science of ChinaJinanShandongChina
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Kim JY, Ilham S, Alshannaq H, Pollock RF, Ahmed W, Norman GJ, Jin SM, Kim JH. Real-time continuous glucose monitoring vs. self-monitoring of blood glucose: cost-utility in South Korean type 2 diabetes patients on intensive insulin. J Med Econ 2024; 27:1245-1252. [PMID: 39275990 DOI: 10.1080/13696998.2024.2405293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Revised: 09/03/2024] [Accepted: 09/13/2024] [Indexed: 09/16/2024]
Abstract
AIMS This study investigated the cost-utility of real-time continuous glucose monitoring (rt-CGM) versus self-monitoring of blood glucose (SMBG) in people with type 2 diabetes (T2D) receiving intensive insulin therapy in South Korea. METHODS The IQVIA Core Diabetes Model (CDM v9.5) was used, with clinical effectiveness data obtained from a large-scale real world study. Costs were obtained from South Korean sources and inflated to 2022 South Korean Won (KRW). A South Korean payer perspective was adopted over a lifetime horizon, with future costs and effects discounted at 4.5% per annum. Baseline characteristics included a mean baseline HbA1c level of 8.6% (71 mmol/mol), and a mean age of 64.4 years. A willingness-to-pay (WTP) threshold of KRW 46.0 million was used. RESULTS Rt-CGM led to an increase of 0.683 quality-adjusted life years (QALYs) versus SMBG (7.526 QALYs for rt-CGM versus 6.843 QALYs for SMBG). An increase in costs of KRW 16.4 million (from KRW 90.4 million to KRW 106.8 million) was associated with rt-CGM. The incremental cost-utility ratio was KRW 24.0 million per QALY gained, significantly lower than the KRW 46 million threshold. CONCLUSIONS For individuals with T2D managed by intensive insulin therapy in South Korea, rt-CGM is cost-effective relative to SMBG.
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Affiliation(s)
- Ji Yoon Kim
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sabrina Ilham
- Health Economics & Outcomes Research, Dexcom, San Diego, CA, USA
| | - Hamza Alshannaq
- Health Economics & Outcomes Research, Dexcom, San Diego, CA, USA
- College of Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Richard F Pollock
- Health Economics and Outcomes Research, Covalence Research Ltd, Harpenden, UK
| | - Waqas Ahmed
- Health Economics and Outcomes Research, Covalence Research Ltd, Harpenden, UK
| | - Gregory J Norman
- Health Economics & Outcomes Research, Dexcom, San Diego, CA, USA
| | - Sang-Man Jin
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jae Hyeon Kim
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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Hu C, Huang K, Cai C, Liu F, Li J, Hu D, Zhao Y, Liu X, Cao J, Chen S, Li H, Yu L, Li Y, Shen C, Huang J, Gu D, Lu X. Genetic Predisposition, Sedentary Behavior, and Incident Coronary Artery Disease: A Prospective Chinese Cohort Study. Med Sci Sports Exerc 2024; 56:103-109. [PMID: 37703277 DOI: 10.1249/mss.0000000000003277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
PURPOSE Whether the association of sedentary behaviors with coronary artery disease (CAD) can be influenced by genetic susceptibility remains unclear. We aimed to investigate the joint and interplay effects between genetic risk and sedentary time (ST) and to further explore the extent to which the risk for CAD can be counteracted by reducing ST in different genetic groups. METHODS This prospective cohort study included 39,164 Chinese adults without CAD history. Genetic susceptibility was quantified by a predefined polygenic risk score (PRS) with 540 genetic variants, and daily ST was assessed by questionnaire. We analyzed the modification effect of genetic risk on the association of ST with CAD using the Cox proportional hazards models. RESULTS During a median follow-up of 11.60 yr, 1156 CAD events were documented. Higher ST and PRS were separately related to elevated CAD risk. Significant additive interaction was also observed (relative excess risk due to interaction: 0.77; 95% confidence interval [CI] = 0.27-1.28). Compared with participants with low genetic risk and low ST (<6 h·d -1 ), those with high genetic risk and high ST (≥10 h·d -1 ) had the highest CAD risk, with the hazard ratio (HR) and 95% CI of 4.22 (2.65-6.71). When stratified by genetic risks, participants with high ST had gradient increment of CAD risks across low, intermediate, and high genetic risk groups, with HR (95% CI) values of 1.21 (0.61-2.40), 1.57 (1.14-2.16), and 2.15 (1.40-3.31), respectively. For the absolute risk reduction, individuals with high genetic risk achieved the greatest benefit from low ST ( Ptrend = 0.024). CONCLUSIONS Genetic susceptibility may synergistically interact with ST to increase CAD risk. Reducing ST could attenuate the CAD risk, especially among individuals with high genetic risk.
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Affiliation(s)
- Chunyu Hu
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
| | - Keyong Huang
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
| | - Can Cai
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
| | - Fangchao Liu
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
| | - Jianxin Li
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
| | | | - Yingxin Zhao
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, CHINA
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou, CHINA
| | - Jie Cao
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
| | - Shufeng Chen
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
| | - Hongfan Li
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
| | - Ling Yu
- Department of Cardiology, Fujian Provincial Hospital, Fuzhou, CHINA
| | - Ying Li
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
| | - Chong Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, CHINA
| | - Jianfeng Huang
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
| | | | - Xiangfeng Lu
- Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CHINA
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Huang K, Jia J, Liang F, Li J, Niu X, Yang X, Chen S, Cao J, Shen C, Liu X, Yu L, Lu F, Wu X, Zhao L, Li Y, Hu D, Huang J, Liu Y, Gu D, Liu F, Lu X. Fine Particulate Matter Exposure, Genetic Susceptibility, and the Risk of Incident Stroke: A Prospective Cohort Study. Stroke 2024; 55:92-100. [PMID: 38018834 PMCID: PMC11831602 DOI: 10.1161/strokeaha.123.043812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 09/25/2023] [Accepted: 10/12/2023] [Indexed: 11/30/2023]
Abstract
BACKGROUND Both genetic factors and environmental air pollution contribute to the risk of stroke. However, it is unknown whether the association between air pollution and stroke risk is influenced by the genetic susceptibilities of stroke and its risk factors. METHODS This prospective cohort study included 40 827 Chinese adults without stroke history. Satellite-based monthly fine particulate matter (PM2.5) estimation at 1-km resolution was used for exposure assessment. Based on 534 identified genetic variants from genome-wide association studies in East Asians, we constructed 6 polygenic risk scores for stroke and its risk factors, including atrial fibrillation, blood pressure, type 2 diabetes, body mass index, and triglyceride. The Cox proportional hazards model was applied to evaluate the hazard ratios and 95% CIs for the associations of PM2.5 and polygenic risk score with incident stroke and the potential effect modifications. RESULTS Over a median follow-up of 12.06 years, 3147 incident stroke cases were documented. Compared with the lowest quartile of PM2.5 exposure, the hazard ratio (95% CI) for stroke in the highest quartile group was 2.72 (2.42-3.06). Among individuals at high genetic risk, the relative risk of stroke was 57% (1.57; 1.40-1.76) higher than those at low genetic risk. Although no statistically significant interaction was found, participants with both the highest PM2.5 and high genetic risk showed the highest risk of stroke, with ≈4× that of the lowest PM2.5 and low genetic risk group (hazard ratio, 3.55 [95% CI, 2.84-4.44]). Similar upward gradients were observed in the risk of stroke when assessing the joint effects of PM2.5 and genetic risks of blood pressure, type 2 diabetes, body mass index, atrial fibrillation, and triglyceride. CONCLUSIONS Long-term exposure to PM2.5 was associated with a higher risk of incident stroke across different genetic susceptibilities. Our findings highlighted the great importance of comprehensive assessment of air pollution and genetic risk in the prevention of stroke.
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Affiliation(s)
- Keyong Huang
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Jiajing Jia
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Fengchao Liang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen 518055, China
| | - Jianxin Li
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Xiaoge Niu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Department of Nephrology, Henan Provincial Key Laboratory of Kidney Disease and Immunology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Provincial People’s Hospital and People’s Hospital of Zhengzhou University, Zhengzhou, 450053, China
| | - Xueli Yang
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300203, China
| | - Shufeng Chen
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Jie Cao
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Chong Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People’s Hospital and Cardiovascular Institute, Guangzhou, 510080, China
| | - Ling Yu
- Department of Cardiology, Fujian Provincial People’s Hospital, Fuzhou, 350014, China
| | - Fanghong Lu
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, 250062, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, 610041, China
| | - Liancheng Zhao
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Ying Li
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen 518071, China
| | - Jianfeng Huang
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Yang Liu
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA
| | - Dongfeng Gu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
- School of Medicine, Southern University of Science and Technology, Shenzhen 518055, China
| | - Fangchao Liu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Xiangfeng Lu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing 100037, China
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Tse G, Lee Q, Chou OHI, Chung CT, Lee S, Chan JSK, Li G, Kaur N, Roever L, Liu H, Liu T, Zhou J. Healthcare Big Data in Hong Kong: Development and Implementation of Artificial Intelligence-Enhanced Predictive Models for Risk Stratification. Curr Probl Cardiol 2024; 49:102168. [PMID: 37871712 DOI: 10.1016/j.cpcardiol.2023.102168] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 10/20/2023] [Indexed: 10/25/2023]
Abstract
Routinely collected electronic health records (EHRs) data contain a vast amount of valuable information for conducting epidemiological studies. With the right tools, we can gain insights into disease processes and development, identify the best treatment and develop accurate models for predicting outcomes. Our recent systematic review has found that the number of big data studies from Hong Kong has rapidly increased since 2015, with an increasingly common application of artificial intelligence (AI). The advantages of big data are that i) the models developed are highly generalisable to the population, ii) multiple outcomes can be determined simultaneously, iii) ease of cross-validation by for model training, development and calibration, iv) huge numbers of useful variables can be analyzed, v) static and dynamic variables can be analyzed, vi) non-linear and latent interactions between variables can be captured, vii) artificial intelligence approaches can enhance the performance of prediction models. In this paper, we will provide several examples (cardiovascular disease, diabetes mellitus, Brugada syndrome, long QT syndrome) to illustrate efforts from a multi-disciplinary team to identify data from different modalities to develop models using territory-wide datasets, with the possibility of real-time risk updates by using new data captured from patients. The benefit is that only routinely collected data are required for developing highly accurate and high-performance models. AI-driven models outperform traditional models in terms of sensitivity, specificity, accuracy, area under the receiver operating characteristic and precision-recall curve, and F1 score. Web and/or mobile versions of the risk models allow clinicians to risk stratify patients quickly in clinical settings, thereby enabling clinical decision-making. Efforts are required to identify the best ways of implementing AI algorithms on the web and mobile apps.
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Affiliation(s)
- Gary Tse
- School of Nursing and Health Studies, Hong Kong Metropolitan University, Hong Kong, China; Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin 300211, China.
| | - Quinncy Lee
- Family Medicine Research Unit, Cardiovascular Analytics Group, PowerHealth Research Institute, Hong Kong, China
| | - Oscar Hou In Chou
- Family Medicine Research Unit, Cardiovascular Analytics Group, PowerHealth Research Institute, Hong Kong, China; Division of Clinical Pharmacology and Therapeutics, Department of Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Cheuk To Chung
- Family Medicine Research Unit, Cardiovascular Analytics Group, PowerHealth Research Institute, Hong Kong, China
| | - Sharen Lee
- Family Medicine Research Unit, Cardiovascular Analytics Group, PowerHealth Research Institute, Hong Kong, China
| | - Jeffrey Shi Kai Chan
- Family Medicine Research Unit, Cardiovascular Analytics Group, PowerHealth Research Institute, Hong Kong, China
| | - Guoliang Li
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Narinder Kaur
- Family Medicine Research Unit, Cardiovascular Analytics Group, PowerHealth Research Institute, Hong Kong, China; School of Cardiovascular Science & Metabolic Health, University of Glasgow, UK
| | - Leonardo Roever
- Department of Clinical Research, Federal University of Uberlândia, Uberlândia, MG 38400384, Brazil
| | - Haipeng Liu
- Research Centre for Intelligent Healthcare, Faculty of Health and Life Sciences, Coventry University, Coventry, UK
| | - Tong Liu
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin 300211, China
| | - Jiandong Zhou
- Division of Health Science, Warwick Medical School, University of Warwick, Coventry, United Kingdom
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Li C, Liu X, Shen P, Sun Y, Zhou T, Chen W, Chen Q, Lin H, Tang X, Gao P. Improving cardiovascular risk prediction through machine learning modelling of irregularly repeated electronic health records. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2024; 5:30-40. [PMID: 38264696 PMCID: PMC10802828 DOI: 10.1093/ehjdh/ztad058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/03/2023] [Accepted: 09/19/2023] [Indexed: 01/25/2024]
Abstract
Aims Existing electronic health records (EHRs) often consist of abundant but irregular longitudinal measurements of risk factors. In this study, we aim to leverage such data to improve the risk prediction of atherosclerotic cardiovascular disease (ASCVD) by applying machine learning (ML) algorithms, which can allow automatic screening of the population. Methods and results A total of 215 744 Chinese adults aged between 40 and 79 without a history of cardiovascular disease were included (6081 cases) from an EHR-based longitudinal cohort study. To allow interpretability of the model, the predictors of demographic characteristics, medication treatment, and repeatedly measured records of lipids, glycaemia, obesity, blood pressure, and renal function were used. The primary outcome was ASCVD, defined as non-fatal acute myocardial infarction, coronary heart disease death, or fatal and non-fatal stroke. The eXtreme Gradient boosting (XGBoost) algorithm and Least Absolute Shrinkage and Selection Operator (LASSO) regression models were derived to predict the 5-year ASCVD risk. In the validation set, compared with the refitted Chinese guideline-recommended Cox model (i.e. the China-PAR), the XGBoost model had a significantly higher C-statistic of 0.792, (the differences in the C-statistics: 0.011, 0.006-0.017, P < 0.001), with similar results reported for LASSO regression (the differences in the C-statistics: 0.008, 0.005-0.011, P < 0.001). The XGBoost model demonstrated the best calibration performance (men: Dx = 0.598, P = 0.75; women: Dx = 1.867, P = 0.08). Moreover, the risk distribution of the ML algorithms differed from that of the conventional model. The net reclassification improvement rates of XGBoost and LASSO over the Cox model were 3.9% (1.4-6.4%) and 2.8% (0.7-4.9%), respectively. Conclusion Machine learning algorithms with irregular, repeated real-world data could improve cardiovascular risk prediction. They demonstrated significantly better performance for reclassification to identify the high-risk population correctly.
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Affiliation(s)
- Chaiquan Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
| | - Xiaofei Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
| | - Peng Shen
- Yinzhou District Center for Disease Control and Prevention, No. 1221 Xueshi Road, Yinzhou District, 315199 Ningbo, China
| | - Yexiang Sun
- Yinzhou District Center for Disease Control and Prevention, No. 1221 Xueshi Road, Yinzhou District, 315199 Ningbo, China
| | - Tianjing Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
| | - Weiye Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
| | - Qi Chen
- Yinzhou District Center for Disease Control and Prevention, No. 1221 Xueshi Road, Yinzhou District, 315199 Ningbo, China
| | - Hongbo Lin
- Yinzhou District Center for Disease Control and Prevention, No. 1221 Xueshi Road, Yinzhou District, 315199 Ningbo, China
| | - Xun Tang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
| | - Pei Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
- Center for Real-world Evidence Evaluation, Peking University Clinical Research Institute, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
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Lu J, Han G, Liu X, Chen B, Peng K, Shi Y, Zhang M, Yang Y, Cui J, Song L, Xu W, Yang H, He W, Zhang Y, Tian Y, Li Y, Li X. Association of high-density lipoprotein cholesterol with all-cause and cause-specific mortality in a Chinese population of 3.3 million adults: a prospective cohort study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2024; 42:100874. [PMID: 38357392 PMCID: PMC10865023 DOI: 10.1016/j.lanwpc.2023.100874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 06/23/2023] [Accepted: 07/23/2023] [Indexed: 02/16/2024]
Abstract
Background High-density lipoprotein cholesterol (HDL-C) has been inversely associated with cardiovascular disease (CVD) risk, but recent evidence suggests that extremely high levels of HDL-C are paradoxically related to increased CVD incidence and mortality. This study aimed to comprehensively examine the associations of HDL-C with all-cause and cause-specific mortality in a Chinese population. Methods The China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) project included 3,397,547 participants aged 35-75 years with a median follow-up of 3.9 years. Baseline HDL-C levels were measured, and mortality data was ascertained from the National Mortality Surveillance System and Vital Registration of Chinese Center for Disease Control and Prevention. Findings This study found U-shaped associations of HDL-C with all-cause, cardiovascular and cancer mortality. When compared with the groups with the lowest risk, the adjusted hazard ratios (95% CIs) for HDL-C <30 mg/dL was 1.23 (1.17-1.29), 1.33 (1.23-1.45) and 1.18 (1.09-1.28) for all-cause, CVD and cancer mortality, respectively. For HDL-C >90 mg/dL, the corresponding HR (95% CIs) was 1.10 (1.05-1.15), 1.09 (1.01-1.18) and 1.11 (1.03-1.19). Similar U-shaped patterns were also found in associations of HDL-C with ischemic heart disease, ischemic stroke, and liver cancer. About 3.25% of all-cause mortality could be attributed to abnormal levels of HDL-C. The major contributor to mortality was ischemic heart disease (16.06 deaths per 100,000 persons, 95% UI: 10.30-22.67) for HDL-C <40 mg/dL and esophageal cancer (2.29 deaths per 100,000 persons, 95% UI: 0.57-4.77) for HDL-C >70 mg/dL. Interpretation Both low and high HDL-C were associated with increased mortality risk. We recommended 50-79 mg/dL as the optimal range of HDL-C among Chinese adults. Individuals with dyslipidemia might benefit from proper management of both low and high HDL-C. Funding The CAMS Innovation Fund for Medical Science (2021-1-I2M-011), the National High Level Hospital Clinical Research Funding (2022-GSP-GG-4), the Ministry of Finance of China and National Health Commission of China, and the 111 Project from the Ministry of Education of China (B16005), the Program for Guangdong Introducing Innovative and Enterpreneurial Teams (2019ZT08Y481), Sanming Project of Medicine in Shenzhen (SZSM201811096), the Young Talent Program of the Academician Fund, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen (YS-2022-006) and Guangdong Basic and Applied Basic Research Foundation (2023A1515010076 & 2021A1515220173).
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Affiliation(s)
- Jiapeng Lu
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Guiyuan Han
- Shenzhen Clinical Research Center of Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Shenzhen, People’s Republic of China
| | - Xiaoying Liu
- Shenzhen Clinical Research Center of Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Shenzhen, People’s Republic of China
| | - Bowang Chen
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Ke Peng
- Shenzhen Clinical Research Center of Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Shenzhen, People’s Republic of China
| | - Yu Shi
- Shenzhen Clinical Research Center of Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Shenzhen, People’s Republic of China
| | - Mei Zhang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Yang Yang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Jianlan Cui
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Lijuan Song
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Wei Xu
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Hao Yang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Wenyan He
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Yan Zhang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Yuan Tian
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Yichong Li
- Shenzhen Clinical Research Center of Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Shenzhen, People’s Republic of China
| | - Xi Li
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
- Central China Sub-center of the National Center for Cardiovascular Diseases, Zhengzhou, People’s Republic of China
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Wu W, Chen Y, Wu K, Zheng H, Chen G, Wang X, Huang Z, Cai Z, Cai Z, Chen Z, Lan Y, Chen S, Wu S, Chen Y. Accumulated exposure to high non-high-density lipoprotein cholesterol increases the risk of cardiovascular diseases in hypertensive individuals: An 11-year prospective cohort study. Clin Exp Hypertens 2023; 45:2264540. [PMID: 37805983 DOI: 10.1080/10641963.2023.2264540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 09/22/2023] [Indexed: 10/10/2023]
Abstract
BACKGROUND The relationship of cumulative non high-density lipoprotein-cholesterol (Cum-non-HDL-C) concentration with the risk of cardiovascular disease (CVD) in individuals with hypertension remains unclear. METHODS In total 27 234 participants for whom three consecutive total cholesterol and HDL-C concentrations were available, and who did not have CVD, comprising 13 617 with hypertension and 13 617 without from 2006 to 2010. Participants were placed into four groups according to Cum-non-HDL-C. Cox proportional hazards models were used to evaluate the relationship between Cum-non-HDL-C and the risk of CVD. RESULTS Over a median 11 years, 1,298 participants with hypertension developed CVD. After adjustment for multiple potential confounding factors, compared with participants with hypertension and Cum-non-HDL-C < 130 mg/dl, the fully adjusted hazard ratios and 95% confidence intervals of CVD associated with Cum-non-HDL-C values of 130-159 mg/dl, 160-189 mg/dl, and ≥ 190 mg/dl were 1.23 (1.01, 1.34), 1.27 (1.04, 1.56), and 1.51 (1.13, 2.01), respectively. Compared with participants without hypertension and a Cum-non-HDL-C < 130 mg/dl, the fully adjusted hazard ratios (95% confidence intervals) for the participants with hypertension and Cum-non-HDL-Cs < 130 mg/dl, 130-159 mg/dl, 160-189 mg/dl, and ≥ 190 mg/dl were 1.84 (1.55, 2.18), 2.16 (1.81, 2.59), 2.17 (1.73, 2.70), and 2.45 (1.12, 3.29), respectively. CONCLUSIONS A consistently high non-HDL-C concentration increases the risk of CVD in individuals with hypertension, as does prolonged exposure to a high non-HDL-C concentration. Thus, the achievement of target blood pressure and non-HDL-C concentrations should help reduce the risk of CVD in individuals with hypertension.
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Affiliation(s)
- Weiqiang Wu
- Department of Cardiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Yanjuan Chen
- Department of Endocrinology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Kuangyi Wu
- Department of Cardiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Huancong Zheng
- Department of Cardiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Guanzhi Chen
- Cardiac Arrhythmia Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | | | - Zegui Huang
- Shantou University Medical College, Shantou, China
| | - Zefeng Cai
- Department of Cardiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Zhiwei Cai
- Department of Cardiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Zhichao Chen
- Department of Cardiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Yulong Lan
- Department of Cardiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Shuohua Chen
- Department of Cardiology, Kailuan General Hospital, Tangshan, China
| | - Shouling Wu
- Department of Cardiology, Kailuan General Hospital, Tangshan, China
| | - Youren Chen
- Department of Cardiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, China
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Hou J, Li M, Han J, Yu S, Jia X, Sun F, Zhang Y. Northern Shanghai Study II: systematic assessment and management of early organ damage and its role in preventing and reducing cardiovascular risk-protocol of a prospective study. BMJ Open 2023; 13:e073423. [PMID: 38159946 PMCID: PMC10759065 DOI: 10.1136/bmjopen-2023-073423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 11/21/2023] [Indexed: 01/03/2024] Open
Abstract
INTRODUCTION Cardiovascular diseases are the leading cause of death and disease burden in China. However, there is a lack of prospective cohort studies suitable for evaluating early organ damage and its role in preventing and reducing cardiovascular risk among Chinese residents. This study intends to establish the first database based on the phenotypes of all early structural and functional damage of cardiovascular organs in Chinese population. Moreover, a digital follow-up mechanism will be formed, a prospective population cohort will be established, a biological sample bank for early cardiovascular organ damage will be established, and an intervention and management system for early damage of cardiovascular organs will be explored. METHODS AND ANALYSIS This study is a prospective cohort study built on the foundation of the Northern Shanghai Study I. People aged 18-75 years are enrolled. After the recruitment, first, corresponding physical measurements and clinical examinations are conducted to collect cardiovascular risk factors and establish the demographic baseline of the study population. Next, the latest equipment is used to evaluate early structural and functional cardiovascular organ damage including heart, macrovessels, microcirculation, renal function and fundus. Meanwhile, the blood, urine, faeces and other biological samples of participants are collected to establish the cardiometabolic and gut microbiota analysis databases. The population is followed up every 2 years. Comprehensive assessment of early organ damage will be used to predict cardiovascular risk, guide people to change lifestyles to achieve early prevention and provide corresponding treatment recommendations. ETHICS AND DISSEMINATION This study was approved by the Shanghai Tenth People's Hospital Institutional Review Board. All participants signed a written consent form. The results of this study will be disseminated in peer-reviewed journals. Ethics approval: SHYS-IEC-5.0/22k148/P01. TRIAL REGISTRATION NUMBER NCT05435898.
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Affiliation(s)
- Jingjing Hou
- Department of Cardiology,Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Moran Li
- Department of Cardiology,Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Jun Han
- Department of Cardiology,Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Shikai Yu
- Department of Cardiology,Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Xinming Jia
- Clinical Medicine Scientific and Technical Innovation Center,Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Fenyong Sun
- Department of Clinical Laboratory Medicine,Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
| | - Yi Zhang
- Department of Cardiology,Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China
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Sheng CS, Wang H, Liu Y, Li Y, Hou T, Qiu M, Lu Y, Sun S, Yang J, Song X, Ning G, Tian J. Long-term effects of blood pressure 130-139/80-89 mmHg on all-cause and cardiovascular mortality among Chinese adults with different glucose metabolism. Cardiovasc Diabetol 2023; 22:353. [PMID: 38129837 PMCID: PMC10740290 DOI: 10.1186/s12933-023-02088-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 12/07/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND This study aimed to investigate the risks of all-cause and cardiovascular mortality associated with blood pressure (BP) levels of 130-139/80-89 mmHg in Chinese adults with different glucose metabolism, during a long-term follow-up of over 20 years. METHODS A prospective population-based cohort of 2,132 adults in Shanghai was established in 2002 and followed for 21 years. The association between BP categories and mortality was assessed, and the risk was further analyzed using multiple Cox regression analysis by combining BP and blood glucose categories. RESULTS The final analysis included 2,004 participants, with 397 all-cause and 166 cardiovascular mortality. The incidence of all-cause and cardiovascular mortality per 1,000 person-years for different BP categories were as follows: BP < 130/80 mmHg (4.5 and 1.3), 130-139/80-89 mmHg (7.7 and 2.9), and ≥ 140/90 mmHg or treated groups (19.9 and 8.7), respectively. After adjusting for age, sex, and other factors, BP ≥ 140/90 mmHg was significantly associated with a higher risk of mortality across different blood glucose categories. However, using BP < 130/80 mmHg and normoglycemia as the reference, a BP of 130-139/80-89 mmHg was significantly associated with higher risks of all-cause (hazard ratio 3.30 [95% confidence interval 1.48-7.38], P < 0.01) and cardiovascular mortality (9.60 [1.93-47.7], P < 0.01) in diabetes, but not in those with normoglycemia or prediabetes. CONCLUSIONS BP of 130-139/80-89 mmHg may lead to a significantly higher risk of all-cause and cardiovascular mortality in Chinese adults with diabetes, but not in those with normoglycemia or prediabetes. This suggests that the targeted BP for people with diabetes should be < 130-139/80-89 mmHg.
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Affiliation(s)
- Chang-Sheng Sheng
- Department of Cardiovascular Medicine, Center for Epidemiological Studies and Clinical Trials, Center for Vascular Evaluation, Shanghai Key Lab of Hypertension, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Haiyan Wang
- Pingliang Community Health Service Center, Yangpu District, Shanghai, China
- Acute infectious disease control Department, Shanghai Hongkou Center for Disease Control and Prevention, Shanghai, China
| | - Yanjun Liu
- College of Food Science and Engineering, Ocean University of China, Qingdao, Shandong Province, China
| | - Yanyun Li
- Division of Chronic Non-Communicable Disease and Injury, Shanghai municipal center for disease control and prevention, Shanghai, 200336, China
| | - TianZhiChao Hou
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Miaoyan Qiu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yao Lu
- Department of Endocrinology, Xinhua Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 200092, China
| | - Siming Sun
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junhan Yang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaomin Song
- Department of Endocrinology and metabolism, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Jingyan Tian
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Cheng Y, Chen J, Zhao Q, Zhang J, Gao J. Association of carotid wall shear stress measured by vector flow mapping technique with ba-PWV: a pilot study. Front Cardiovasc Med 2023; 10:1293106. [PMID: 38144371 PMCID: PMC10748391 DOI: 10.3389/fcvm.2023.1293106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 10/31/2023] [Indexed: 12/26/2023] Open
Abstract
Objective Arterial stiffness is an important tissue biomarker of the progression of atherosclerotic diseases. Brachial-ankle pulse wave velocity (ba-PWV) is a gold standard of arterial stiffness measurement widely used in Asia. Changes in vascular wall shear stress (WSS) lead to artery wall remodeling, which could give rise to an increase in arterial stiffness. The study aimed to explore the association between ba-PWV and common carotid artery (CCA) WSS measured by a newly invented vascular vector flow mapping (VFM) technique. Methods We included 94 subjects free of apparent cardiovascular disease (CVD) and divided them into a subclinical atherosclerosis (SA) group (N = 47) and non subclinical atherosclerosis (NSA) group (N = 47). CCA WSS was measured using the VFM technique. Bivariate correlations between CCA WSS and other factors were assessed with Pearson's, Spearman's, or Kendall's coefficient of correlation, as appropriate. Partial correlation analysis was conducted to examine the influence of age and sex. Multiple linear stepwise regression was used for the analysis of independent determinants of CCA WSS. Receiver operating characteristic (ROC) analysis was performed to find the association between CCA WSS and 10-year CVD risk. Results The overall subjects had a mean age of 47.9 ± 11.2 years, and males accounted for 52.1%. Average systolic CCA WSS was significantly correlated with ba-PWV (r = -0.618, p < 0.001) in the SA group. Multiple linear stepwise regression analysis confirmed that ba-PWV was an independent determinant of average systolic CCA WSS (β = -0.361, p = 0.003). The area under the curve (AUC) of average systolic CCA WSS for 10-year CVD risk ≥10% was 0.848 (p < 0.001) in the SA group. Conclusions Average systolic CCA WSS was significantly correlated with ba-PWV and was associated with 10-year CVD risk ≥10% in the SA group. Therefore, CCA WSS measured by the VFM technique could be used for monitoring and screening subjects with potential CVD risks.
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Affiliation(s)
- Yi Cheng
- Department of Diagnostic Ultrasound, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Jie Chen
- Department of Diagnostic Ultrasound, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Qing Zhao
- Department of Diagnostic Ultrasound, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Jinghan Zhang
- Department of Diagnostic Ultrasound, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Junyi Gao
- Department of Cardiovascular Medicine, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
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Li J, Lu X. Cardiovascular risk assessment: The key path toward precision prevention. Chronic Dis Transl Med 2023; 9:273-276. [PMID: 37915392 PMCID: PMC10617312 DOI: 10.1002/cdt3.90] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/08/2023] [Accepted: 07/13/2023] [Indexed: 11/03/2023] Open
Affiliation(s)
- Jianxin Li
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
| | - Xiangfeng Lu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Key Laboratory of Cardiovascular EpidemiologyChinese Academy of Medical SciencesBeijingChina
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Zuo Y, Chen S, Tian X, Wang P, Wu S, Wang A. Association of Vascular Aging With Cardiovascular Disease in Middle-Aged Chinese People: A Prospective Cohort Study. JACC. ASIA 2023; 3:895-904. [PMID: 38155790 PMCID: PMC10751638 DOI: 10.1016/j.jacasi.2023.07.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 06/22/2023] [Accepted: 07/30/2023] [Indexed: 12/30/2023]
Abstract
Background Whether middle-aged individuals with a greater difference between chronological age and vascular age show a lower cardiovascular disease risk remains to be clarified. Objectives This study sought to examine whether individuals with supernormal vascular aging (VA) have a lower cardiovascular disease risk than do individuals with normal VA. Methods This prospective cohort study included 20,917 middle-aged (40-60 years) participants from the Kailuan Study. VA was defined as the predicted age in a multivariate regression model, including classic cardiovascular risk factors and pulsed wave velocity. The chronological age minus the VA was defined as the Δ-age, and the 10th and 90th percentiles of the Δ-age were used as cutoffs to define early VA and supernormal VA, respectively. The outcome was a composite of myocardial infarction, hospital admission for heart failure, and stroke. The study used Cox proportional hazards regression to examine the association between the VA categories and the incident cardiovascular outcome. Results During the median 4.6-year follow-up period, 584 endpoint events were observed. After adjusting for potential variables, when compared with the normal VA group, the supernormal VA group had a decreased rate of cardiovascular events (HR: 0.47; 95% CI: 0.35-0.64), and the early VA group had an increased rate (HR: 1.90; 95% CI: 1.22-2.95) of cardiovascular events. Conclusions Individuals with supernormal VA are at a lower risk of cardiovascular events, and individuals with early VA are at a higher risk of cardiovascular events than individuals with normal VA. Further characterization may provide novel insight into future preventive strategies against cardiovascular disease.
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Affiliation(s)
- Yingting Zuo
- Department of Clinical Epidemiology, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Shuohua Chen
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Xue Tian
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Penglian Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shouling Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China
| | - Anxin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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130
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He Z, Jia Y, Li J, Cao J, Liu F, Li H, Chen J, Hu D, Shen C, Zhao Y, Liu X, Yu L, Huang J, Lu X, Gu D, Chen S. Fruit and vegetable intake and the risk of arterial hypertension in China: A prospective cohort study. Chronic Dis Transl Med 2023; 9:309-319. [PMID: 37915386 PMCID: PMC10617310 DOI: 10.1002/cdt3.76] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/13/2023] [Accepted: 05/19/2023] [Indexed: 11/03/2023] Open
Abstract
Background Population-based epidemiological evidence regarding the association between fruit and vegetable intake and the incidence of hypertension is inconsistent. This prospective cohort study aimed to investigate the association between fruit and vegetable intake and the risk of new-onset hypertension. Methods Based on the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR), 58,981 Chinese adults without hypertension at baseline were included. Information on fruit and vegetable intake was collected using a food-frequency questionnaire. Cox proportional hazards models were performed to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of incident hypertension. Results During 640,795 person-years of follow-up, 21,008 new cases of hypertension were recorded. Compared with participants in the lowest quintile (Q1) of total fruit and vegetable (TFV) intake, the HRs (95% CIs) of incident hypertension were 0.90 (0.86-0.95), 0.85 (0.81-0.90), 0.82 (0.78-0.86), and 0.83 (0.78-0.88) for the Q2 to Q5 group (p trend < 0.001), respectively. In further analyses categorizing participants according to the recommended intake level (500 g/day), we found that increasing the intake of TFV, even though it was still insufficient for the recommendation, also had a protective effect against the incident hypertension. When considering the intake of fruit or vegetable separately, we found similar trends as the TFV intake. Conclusion These results suggest that a higher intake of fruit and vegetable is beneficial for preventing hypertension in Chinese adults.
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Affiliation(s)
- Zhi He
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
| | - Yanhui Jia
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
| | - Jianxin Li
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
| | - Jie Cao
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
| | - Fangchao Liu
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
| | - Hongfan Li
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
| | - Jichun Chen
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public HealthZhengzhou UniversityZhengzhouHenanChina
- Department of Biostatistics and Epidemiology, School of Public HealthShenzhen UniversityShenzhenGuangdongChina
| | - Chong Shen
- Department of Epidemiology and Biostatistics, Center for Global Health, School of Public HealthNanjing Medical UniversityNanjingJiangsuChina
| | - Yingxin Zhao
- Cardio‐Cerebrovascular Control and Research Center, Institute of Basic MedicineShandong First Medical University (Shandong Academy of Medicine Sciences)JinanShandongChina
| | - Xiaoqing Liu
- Division of EpidemiologyGuangdong Provincial People's Hospital and Cardiovascular InstituteGuangzhouGuangdongChina
| | - Ling Yu
- Department of CardiologyFujian Provincial HospitalFuzhouFujianChina
| | - Jianfeng Huang
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
| | - Xiangfeng Lu
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
| | - Dongfeng Gu
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
| | - Shufeng Chen
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, Fuwai HospitalChinese Academy of Medical Sciences & Peking Union Medical College/National Center for Cardiovascular DiseasesBeijingChina
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Qiu J, Chang Z, Wang K, Chen K, Wang Q, Zhang J, Li J, Yang C, Zhao Y, Zhang Y. The predictive accuracy of coronary heart disease risk prediction models in rural Northwestern China. Prev Med Rep 2023; 36:102503. [PMID: 38116288 PMCID: PMC10728432 DOI: 10.1016/j.pmedr.2023.102503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 11/06/2023] [Accepted: 11/07/2023] [Indexed: 12/21/2023] Open
Abstract
Cardiovascular risk models developed may have limitations when applied to rural Chinese. This study validated and compared the Framingham Risk Score (FRS) and Prediction for Atherosclerotic Cardiovascular Disease Risk in China (PAR) models in predicting 10-year risk of coronary heart disease (CHD) in a rural cohort in Ningxia, China from 2008 to 2019. The FRS and PAR models were validated by estimating predicted events, C index, calibration χ2 and plots. 1381 adults without CHD at baseline were followed up for 9.75 years on average. 168 CHD cases were observed. The FRS and PAR underestimated CHD events by 22 % and 46 % for the total population, while overestimated for males by 152 % and 78 %, respectively. The C index was slightly higher for PAR than FRS. Both models showed weak calibration with chi-square values above 20 (p < 0.001). Bland-Altman plots indicated FRS predicted higher CHD risk than PAR, lacking consistency. Overall, FRS and PAR demonstrated limited performance in predicting 10-year CHD risk in this rural population. PAR had slightly better discrimination than FRS, but require further improvement in calibration and individual risk estimation to suit the rural population in Northwest China.
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Affiliation(s)
- Jiangwei Qiu
- School of Public, Ningxia Medical University, Yinchuan, China
- NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical University, Yinchuan, China
| | - Zhenqi Chang
- School of Public, Ningxia Medical University, Yinchuan, China
| | - Kai Wang
- School of Public, Ningxia Medical University, Yinchuan, China
- The Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan, China
| | - Kexin Chen
- School of Public, Ningxia Medical University, Yinchuan, China
| | - Qingan Wang
- School of Public, Ningxia Medical University, Yinchuan, China
- The Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan, China
| | - Jiaxing Zhang
- School of Public, Ningxia Medical University, Yinchuan, China
- The Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan, China
| | - Juan Li
- School of Public, Ningxia Medical University, Yinchuan, China
| | - Chan Yang
- School of Public, Ningxia Medical University, Yinchuan, China
- Department of Community Nursing, School of Nursing, Ningxia Medical University, Yinchuan, China
| | - Yi Zhao
- School of Public, Ningxia Medical University, Yinchuan, China
- NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical University, Yinchuan, China
- The Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan, China
| | - Yuhong Zhang
- School of Public, Ningxia Medical University, Yinchuan, China
- NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Medical University, Yinchuan, China
- The Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan, China
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Chen D, Zhang H, Wu J, Xue E, Guo P, Tang L, Shao J, Cui N, Wang X, Chen L, Ye Z. Effects of an Individualized mHealth-Based Intervention on Health Behavior Change and Cardiovascular Risk Among People With Metabolic Syndrome Based on the Behavior Change Wheel: Quasi-Experimental Study. J Med Internet Res 2023; 25:e49257. [PMID: 38019579 PMCID: PMC10720605 DOI: 10.2196/49257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/10/2023] [Accepted: 10/10/2023] [Indexed: 11/30/2023] Open
Abstract
BACKGROUND Metabolic syndrome (MetS) is a common public health challenge. Health-promoting behaviors such as diet and physical activity are central to preventing and controlling MetS. However, the adoption of diet and physical activity behaviors has always been challenging. An individualized mobile health (mHealth)-based intervention using the Behavior Change Wheel is promising in promoting health behavior change and reducing atherosclerotic cardiovascular disease (ASCVD) risk. However, the effects of this intervention are not well understood among people with MetS in mainland China. OBJECTIVE We aimed to evaluate the effects of the individualized mHealth-based intervention using the Behavior Change Wheel on behavior change and ASCVD risk in people with MetS. METHODS We conducted a quasi-experimental, nonrandomized study. Individuals with MetS were recruited from the health promotion center of a tertiary hospital in Zhejiang province, China. The study involved 138 adults with MetS, comprising a control group of 69 participants and an intervention group of 69 participants. All participants received health education regarding diet and physical activity. The intervention group additionally received a 12-week individualized intervention through a WeChat mini program and a telephone follow-up in the sixth week of the intervention. Primary outcomes included diet, physical activity behaviors, and ASCVD risk. Secondary outcomes included diet self-efficacy, physical activity self-efficacy, knowledge of MetS, quality of life, and the quality and efficiency of health management services. The Mann-Whitney U test and Wilcoxon signed rank test were primarily used for data analysis. Data analysis was conducted based on the intention-to-treat principle using SPSS (version 25.0; IBM Corp). RESULTS Baseline characteristics did not differ between the 2 groups. Compared with the control group, participants in the intervention group showed statistically significant improvements in diet behavior, physical activity behavior, diet self-efficacy, physical activity self-efficacy, knowledge of MetS, physical health, and mental health after a 12-week intervention (P=.04, P=.001, P=.04, P=.04, P=.001, P=.04, P=.04, and P<.05). The intervention group demonstrated a statistically significant improvement in outcomes from pre- to postintervention evaluations (P<.001, P=.03, P<.001, P=.04, P<.001, P<.001, and P<.001). The intervention also led to enhanced health management services and quality. CONCLUSIONS The individualized mHealth-based intervention using the Behavior Change Wheel was effective in promoting diet and physical activity behaviors in patients with MetS. Nurses and other health care professionals may incorporate the intervention into their health promotion programs.
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Affiliation(s)
- Dandan Chen
- Nursing Department, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Zhang
- Department of Nursing, Guizhou Provincial People's Hospital, Guiyang, China
| | - Jingjie Wu
- Nursing Department, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Erxu Xue
- Nursing Department, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Pingping Guo
- Nursing Department, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Leiwen Tang
- Institute of Nursing Research, Zhejiang University School of Medicine, Hangzhou, China
| | - Jing Shao
- Institute of Nursing Research, Department of Nursing of the Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Nianqi Cui
- School of Nursing, Kunming Medical University, Kunming, China
| | - Xiyi Wang
- School of Nursing, Shanghai Jiao Tong University, Shanghai, China
| | - Liying Chen
- Nursing Department, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhihong Ye
- Nursing Department, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
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133
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Zheng H, Wu K, Wu W, Chen G, Chen Z, Cai Z, Cai Z, Lan Y, Wu S, Chen Y. Relationship between the cumulative exposure to atherogenic index of plasma and ischemic stroke: a retrospective cohort study. Cardiovasc Diabetol 2023; 22:313. [PMID: 37968612 PMCID: PMC10652447 DOI: 10.1186/s12933-023-02044-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 10/25/2023] [Indexed: 11/17/2023] Open
Abstract
BACKGROUND Atherogenic index of plasma (AIP) has been demonstrated as a surrogate marker for ischemic stroke, but there is limited evidence for the effect of long-term elevation of AIP on ischemic stroke. Therefore, we aimed to characterize the relationship between cumulative exposure to AIP and the risk of ischemic stroke. METHODS A total of 54,123 participants in the Kailuan Study who attended consecutive health examinations in 2006, 2008, and 2010 and had no history of ischemic stroke or cancer were included. The time-weighted cumulative AIP (cumAIP) was calculated as a weighted sum of the mean AIP values for each time interval and then normalized to the total duration of exposure (2006-2010). Participants were divided into four groups according to quartile of cumAIP: the Q1 group, ≤-0.50; Q2 group, - 0.50 to - 0.12; Q3 group, - 0.12 to 0.28; and Q4 group, ≥ 0.28. Cox proportional hazard models were used to evaluate the relationship between cumAIP and ischemic stroke by calculating hazard ratios (HRs) and 95% confidence intervals (95% CIs). RESULTS After a median follow-up of 11.03 years, a total of 2,742 new ischemic stroke events occurred. The risk of ischemic stroke increased with increasing quartile of cumAIP. After adjustment for potential confounders, Cox regression models showed that participants in the Q2, Q3, and Q4 groups had significantly higher risks of ischemic stroke than those in the Q1 group. The HRs (95% CIs) for ischemic stroke in the Q2, Q3, and Q4 groups were 1.17 (1.03, 1.32), 1.33 (1.18, 1.50), and 1.45 (1.28, 1.64), respectively. The longer duration of high AIP exposure was significantly associated with increased ischemic stroke risk. CONCLUSIONS High cumulative AIP is associated with a higher risk of ischemic stroke, which implies that the long-term monitoring and maintenance of an appropriate AIP may help prevent such events.
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Affiliation(s)
- Huancong Zheng
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Kuangyi Wu
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Weiqiang Wu
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Guanzhi Chen
- Cardiac Arrhythmia Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zekai Chen
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Zefeng Cai
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | - Zhiwei Cai
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, China
- Shantou University Medical College, Shantou, China
| | - Yulong Lan
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, China
- Centre for Precision Health, Edith Cowan University School of Medical and Health Sciences, Joondalup, Australia
| | - Shouling Wu
- Department of Cardiology, Kailuan General Hospital, Tangshan, China.
| | - Youren Chen
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, China.
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Ding J, Luo Y, Shi H, Chen R, Luo S, Yang X, Xiao Z, Liang B, Yan Q, Xu J, Ji L. Machine learning for the prediction of atherosclerotic cardiovascular disease during 3-year follow up in Chinese type 2 diabetes mellitus patients. J Diabetes Investig 2023; 14:1289-1302. [PMID: 37605871 PMCID: PMC10583655 DOI: 10.1111/jdi.14069] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 07/28/2023] [Accepted: 08/02/2023] [Indexed: 08/23/2023] Open
Abstract
AIMS/INTRODUCTION Clinical guidelines for the management of individuals with type 2 diabetes mellitus endorse the systematic assessment of atherosclerotic cardiovascular disease risk for early interventions. In this study, we aimed to develop machine learning models to predict 3-year atherosclerotic cardiovascular disease risk in Chinese type 2 diabetes mellitus patients. MATERIALS AND METHODS Clinical records of 4,722 individuals with type 2 diabetes mellitus admitted to 94 hospitals were used. The features included demographic information, disease histories, laboratory tests and physical examinations. Logistic regression, support vector machine, gradient boosting decision tree, random forest and adaptive boosting were applied for model construction. The performance of these models was evaluated using the area under the receiver operating characteristic curve. Additionally, we applied SHapley Additive exPlanation values to explain the prediction model. RESULTS All five models achieved good performance in both internal and external test sets (area under the receiver operating characteristic curve >0.8). Random forest showed the highest discrimination ability, with sensitivity and specificity being 0.838 and 0.814, respectively. The SHapley Additive exPlanation analyses showed that previous history of diabetic peripheral vascular disease, older populations and longer diabetes duration were the three most influential predictors. CONCLUSIONS The prediction models offer opportunities to personalize treatment and maximize the benefits of these medical interventions.
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Affiliation(s)
| | - Yingying Luo
- Department of Endocrinology and MetabolismPeking University People's HospitalBeijingChina
| | | | | | | | | | | | | | | | - Jie Xu
- Shanghai AI LaboratoryShanghaiChina
| | - Linong Ji
- Department of Endocrinology and MetabolismPeking University People's HospitalBeijingChina
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135
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Li X, Shi Y, Wei D, Ni W, Zhu N, Yan X. Impact of a high dietary fiber cereal meal intervention on body weight, adipose distribution, and cardiovascular risk among individuals with type 2 diabetes. Front Endocrinol (Lausanne) 2023; 14:1283626. [PMID: 37964962 PMCID: PMC10642937 DOI: 10.3389/fendo.2023.1283626] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Accepted: 10/17/2023] [Indexed: 11/16/2023] Open
Abstract
Objective This study sought to examine the impacts of a high dietary fiber cereal meal in comparison to conventional dietary management for diabetes on body weight, distribution of adipose tissue, and cardiovascular risk among individuals diagnosed with type 2 diabetes (T2DM). Methods A cohort of 120 patients diagnosed with T2DM was enlisted as the study population and divided into two groups using a ratio of 2:1-namely, the W group (n=80) and the U group (n=40). The U group (control) received usual diet, while the W group (intervention) incorporated a high dietary fiber cereal meal in place of their regular staple food in addition to adhering to conventional diabetes dietary recommendations. The high dietary fiber cereal meal was based on whole grains, traditional Chinese medicinal foods, and prebiotics. A subsequent follow-up period of 3 months ensued, during which diverse parameters such as body mass index (BMI),waist-hip ratio (WHR), glycated hemoglobin (HbA1c),fasting blood glucose(FBG),C-peptide levels, blood pressure, blood lipids, high-sensitivity C-reactive protein (hsCRP),10-year cardiovascular disease (CVD) risk, and Lifetime CVD risk were assessed before and after the intervention. Results Among the participants, a total of 107 successfully completed the intervention and follow-up, including 72 individuals from the W group and 35 from the U group. Following the intervention, both cohorts exhibited decrease in BMI, WHR, HbA1c, FBG, blood pressure, and blood lipid levels in contrast to their initial measurements. Remarkably, the improvements in BMI, WHR, HbA1c, FBG, total cholesterol (TC), triglycerides(TG), low-density lipoprotein cholesterol (LDL-C), the ratio of triglyceride to high-density lipoprotein cholesterol (TG/HDL-C), and the ratio of 2-hour C-peptide (2hCP) to fasting C-peptide (FCP) were more marked within the W group, exhibiting statistically significant disparities (P<0.05) in comparison to the U group. Furthermore, the levels of hsCRP declined among individuals in the W group, while the U group experienced an elevation.10-year CVD risk reduction were similar in the two groups. While, Lifetime CVD risk only decreased significantly in the W group. Conclusion The intervention centred on a cereal-based dietary approach showcased favourable outcomes with regard to body weight, adipose distribution, and cardiovascular risk in overweight individuals grappling with T2DM.
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Affiliation(s)
- Xiaofeng Li
- Department of Endocrinology, Metabolic Management Center, Qidong People’s Hospital, Qidong Liver Cancer Institute, Affiliated Qidong Hospital of Nantong University, Jiangsu, China
| | - Yu Shi
- Department of Endocrinology, Metabolic Management Center, Qidong People’s Hospital, Qidong Liver Cancer Institute, Affiliated Qidong Hospital of Nantong University, Jiangsu, China
| | - Dongqin Wei
- Department of Endocrinology, Metabolic Management Center, Qidong People’s Hospital, Qidong Liver Cancer Institute, Affiliated Qidong Hospital of Nantong University, Jiangsu, China
| | - Wenyu Ni
- Department of Endocrinology, Metabolic Management Center, Qidong People’s Hospital, Qidong Liver Cancer Institute, Affiliated Qidong Hospital of Nantong University, Jiangsu, China
| | - Na Zhu
- Department of Remote ECG Diagnostic Center, Qidong People’s Hospital, Qidong Liver Cancer Institute, Affiliated Qidong Hospital of Nantong University, Jiangsu, China
| | - Xinyi Yan
- Department of Endocrinology, Metabolic Management Center, Qidong People’s Hospital, Qidong Liver Cancer Institute, Affiliated Qidong Hospital of Nantong University, Jiangsu, China
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Yang S, Sun D, Sun Z, Yu C, Guo Y, Si J, Sun D, Pang Y, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Pang Z, Schmidt D, Stevens R, Clarke R, Chen J, Chen Z, Lv J, Li L. Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores: evidence from the China Kadoorie Biobank. Chin Med J (Engl) 2023; 136:2476-2483. [PMID: 37200020 PMCID: PMC10586831 DOI: 10.1097/cm9.0000000000002694] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Indexed: 05/19/2023] Open
Abstract
BACKGROUND Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population. METHODS Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training ( n = 28,490) and testing sets ( n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21-I23 and fatal I20-I25) and soft CAD (all fatal or nonfatal I20-I25) were analyzed separately. RESULTS In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19-1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (-0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4-6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model. CONCLUSIONS In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.
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Affiliation(s)
- Songchun Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Dong Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Zhijia Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Jiahui Si
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Iona Y. Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Robin G. Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Zengchang Pang
- Qingdao Center of Disease Control and Prevention, Qingdao, Shandong 266033, China
| | - Dan Schmidt
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Rebecca Stevens
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing 100738, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
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Jia R, Wang Q, Huang H, Yang Y, Chung YF, Liang T. Cardiovascular disease risk models and dementia or cognitive decline: a systematic review. Front Aging Neurosci 2023; 15:1257367. [PMID: 37904838 PMCID: PMC10613491 DOI: 10.3389/fnagi.2023.1257367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 09/11/2023] [Indexed: 11/01/2023] Open
Abstract
Background Health cognitive promotion and protection is a critical topic. With the world's aging population and rising life expectancy, there will be many people living with highly age-related dementia illnesses. Cardiovascular disease (CVD) and dementia share the same risk factors, such as unhealthy lifestyles and metabolic factors. These recognized risks associated with CVD and dementia frequently co-occur. CVD risk models may have a close association with dementia and cognitive decline. So, this systematic review aimed to determine whether CVD risk models were connected with dementia or cognitive decline and compare the predictive ability of various models. Methods PubMed, Web of Science, PsychINFO, Embase, Cochrane Library, CNKI, Sinomed, and WanFang were searched from 1 January 2014 until 16 February 2023. Only CVD risk models were included. We used the Newcastle-Ottawa scale (NOS) for the quality assessment of included cohort studies and the Agency for Healthcare Research and Quality (AHRQ) for cross-sectional studies. The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement's guidelines were followed in this systematic study. Results In all, 9,718 references were screened, of which 22 articles were included. A total of 15 CVD risk models were summarized. Except for the Cardiovascular Health in Ambulatory Care Research Team (CANHEART) health index, the other 14 CVD risk models were associated with dementia and cognitive decline. In comparison, different CVD risk models and domain-specific cognitive function correlation variation depended on cohort characteristics, risk models, cognitive function tests, and study designs. Moreover, it needed to be clarified when comparing the predicting performance of different CVD risk models. Conclusion It is significant for public health to improve disease risk prediction and prevention and mitigate the potential adverse effects of the heart on the brain. More cohort studies are warranted to prove the correlation between CVD risk models and cognitive function. Moreover, further studies are encouraged to compare the efficacy of CVD risk models in predicting cognitive disorders.
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Affiliation(s)
- Ruirui Jia
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Qing Wang
- School of Nursing, Lanzhou University, Lanzhou, China
- School of Nursing, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hengyi Huang
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Yanli Yang
- School of Nursing, Lanzhou University, Lanzhou, China
| | | | - Tao Liang
- School of Nursing, Lanzhou University, Lanzhou, China
- School of Nursing, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Yu B, Hu M, Jiang W, Ma Y, Ye J, Wu Q, Guo W, Sun Y, Zhou M, Xu Y, Wu Z, Wang Y, Lam SM, Shui G, Gu J, Li JZ, Fu Z, Gong Y, Zhou H. Ceramide d18:1/24:1 as a potential biomarker to differentiate obesity subtypes with unfavorable health outcomes. Lipids Health Dis 2023; 22:166. [PMID: 37794463 PMCID: PMC10548646 DOI: 10.1186/s12944-023-01921-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 09/11/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND The criteria for metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) remain controversial. This research aimed to identify a potential biomarker to differentiate the subtypes of obesity. METHODS The study conducted a lipidomic evaluation of ceramide in the serum of 77 Chinese adults who had undergone hyperinsulinemic-euglycemic clamps. These adults were divided into three groups according to the clinical data: normal weight control group (N = 21), MHO (N = 20), and MUO (N = 36). RESULTS The serum Cer d18:1/24:1 level in the MHO group was lower than that in the MUO group. As the Cer d18:1/24:1 level increased, insulin sensitivity decreased, and the unfavorable parameters increased in parallel. Multivariate logistic regression analysis revealed that serum Cer d18:1/24:1 levels were independently correlated with MUO in obesity. Individuals with higher levels of Cer d18:1/24:1 also had an elevated risk of cardiovascular disease. Most ceramide subtype levels increased in obesity compared to normal-weight individuals, but the levels of serum Cer d18:0/18:0 and Cer d18:1/16:0 decreased in obesity. CONCLUSIONS The relationships between ceramide subtypes and metabolic profiles might be heterogeneous in populations with different body weights. Cer d18:1/24:1 could be a biomarker that can be used to differentiate MUO from MHO, and to better predict who will develop unfavorable health outcomes among obese individuals. TRIAL REGISTRATION The First Affiliated Hospital of Nanjing Medical University's Institutional Review Board authorized this study protocol, and all participants provided written informed consent (2014-SR-003) prior to study entry.
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Affiliation(s)
- Baowen Yu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Moran Hu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Wanzi Jiang
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yizhe Ma
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jingya Ye
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Qinyi Wu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Wen Guo
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yan Sun
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Min Zhou
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yiwen Xu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zhoulu Wu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yiwen Wang
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Sin Man Lam
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Guanghou Shui
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Jingyu Gu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - John Zhong Li
- Department of Biochemistry and Molecular Biology, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zhenzhen Fu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Yingyun Gong
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Hongwen Zhou
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
- Department of Biochemistry and Molecular Biology, Nanjing Medical University, Nanjing, Jiangsu, China.
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Xia X, Liu F, Huang K, Chen S, Li J, Cao J, Yang X, Liu X, Shen C, Yu L, Zhao Y, Zhao L, Li Y, Hu D, Huang J, Lu X, Gu D. Egg consumption and risk of coronary artery disease, potential amplification by high genetic susceptibility: a prospective cohort study. Am J Clin Nutr 2023; 118:773-781. [PMID: 37793743 DOI: 10.1016/j.ajcnut.2023.06.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 06/03/2023] [Accepted: 06/08/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Remarkable heterogeneity has been observed among population-based studies on egg consumption and risk of coronary artery disease (CAD). Whether genetic susceptibility serves as a potential explanation for this inconsistency remains unknown. OBJECTIVES We performed a prospective cohort study to investigate the association of egg consumption with incident CAD at different genetic susceptibilities. METHODS We included 34,111 participants without CAD at baseline from the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China. Egg consumption was assessed with food frequency questionnaires. Genetic susceptibility was quantified by a predefined polygenic risk score (PRS) with 540 genetic variants. The hazard ratio (HR) and 95% confidence interval (95% CI) of incident CAD associated with egg consumption and PRS were estimated using the Cox proportional hazards models. RESULTS Over a median 11.7 y of follow-up, 1,128 incident cases of CAD were recorded. Both higher egg consumption and increased PRS were related to higher risk of CAD. When stratified by genetic risk, each increment of 3 eggs/wk was associated with a 5% higher risk of CAD for participants at low to intermediate genetic risk (HR: 1.05; 95% CI: 1.01, 1.09), whereas risk increased to HR 1.10 (95% CI: 1.05, 1.16) for those at high genetic risk; a significant synergistic interaction was also indicated at both multiplicative (Pinteraction = 0.007) and additive (relative excess risk: 0.73; 95% CI: 0.24, 1.22) scales. When the joint effect was examined, in comparison with those at low to intermediate genetic risk and consuming <1 egg/wk, the HR (95% CI) was 2.95 (2.41, 3.62) for participants with high genetic risk and consumption of ≥10 eggs/wk, and the corresponding standardized 10-y CAD rates increased from 1.37% to 4.24%. CONCLUSIONS Genetic predisposition may synergistically interact with egg consumption in relation to increased CAD risk. PRS-stratified recommendations on egg consumption may help formulate personalized nutrition policies.
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Affiliation(s)
- Xue Xia
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China; Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Fangchao Liu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
| | - Keyong Huang
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shufeng Chen
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianxin Li
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie Cao
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xueli Yang
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou, China
| | - Chong Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ling Yu
- Department of Cardiology, Fujian Provincial Hospital, Fuzhou, China
| | - Yingxin Zhao
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, China
| | - Liancheng Zhao
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ying Li
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China; Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, China
| | - Jiangfeng Huang
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiangfeng Lu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China.
| | - Dongfeng Gu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China; School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China.
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Zhou X, Ke Z, Sun F, Li F, You Z, Zhang J, Gao Y, Zhu Z, Tong W. Effect of Bariatric Surgery on Metabolic Syndrome in Chinese Patients with Low Body Mass Index: a Propensity Score Matching Study. Obes Surg 2023; 33:3051-3061. [PMID: 37561268 DOI: 10.1007/s11695-023-06765-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/15/2023] [Accepted: 07/25/2023] [Indexed: 08/11/2023]
Abstract
BACKGROUND Bariatric surgery (BS) is known to improve the components of metabolic syndrome (MS) in patients with obesity. However, few studies have evaluated the effect of BS on patients with MS at low BMI levels. The study aims to assess the effect of BS on MS in patients with low BMI by comparing BS with medical therapy (MT). METHODS A total of 271 patients with MS who underwent BS and MT at a single institution were reviewed in this retrospective cohort study. A 1:1 propensity score matching was performed for the BS and MT groups with BMI<35 kg/m2. We analyzed the 5 years effect of BS versus MT on the remission of MS, its components, atherosclerotic cardiovascular disease (ASCVD) risk, and medication used. RESULTS Patients in the MT group showed a decrease in the prevalence of MS to 62% at the 1st year and 10% at the 5th year. In the BS group, MS prevalence in patients with BMI<35 kg/m2 decreased to 30% and 9% at the 1st and 5th year, whereas in patients with BMI≥35 kg/m2 was 26% and 7%, respectively. The 10-year ASCVD risk and the lifetime ASCVD were significantly decreased 5 years after BS in patients with BMI<35 kg/m2. The number and daily drug dose of hypoglycemic drugs, antihypertensive medications, and lipid-lowering drugs were reduced from baseline in both BS and MT groups. CONCLUSION Bariatric surgery significantly improves MS remission rates and long-term cardiovascular risk in Chinese patients with metabolic syndrome and a BMI <35 kg/m2.
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Affiliation(s)
- Xunmei Zhou
- Department of Endocrinology, University-Town Hospital of Chongqing Medical University, Chongqing, 401331, China
- Department of Hypertension and Endocrinology, Center for Hypertension and Metabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing, 400042, China
| | - Zhigang Ke
- Department of General Surgery, Daping Hospital, Army Medical University, Chongqing, 400042, China
| | - Fang Sun
- Department of Hypertension and Endocrinology, Center for Hypertension and Metabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing, 400042, China
| | - Fan Li
- Department of General Surgery, Daping Hospital, Army Medical University, Chongqing, 400042, China
| | - Zaichun You
- Department of General Medicine, Second Affiliated Hospital of Army Medical University, Chongqing, 400037, China
| | - Jian Zhang
- Department of General Medicine, Xinmiao Central Hospital, Fuling District, Chongqing, 408114, China
| | - Yu Gao
- Department of General Surgery, Daping Hospital, Army Medical University, Chongqing, 400042, China
| | - Zhiming Zhu
- Department of Hypertension and Endocrinology, Center for Hypertension and Metabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing, 400042, China.
| | - Weidong Tong
- Department of General Surgery, Daping Hospital, Army Medical University, Chongqing, 400042, China.
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Li Y, Zhang Y, Xiao K, Si J, Zhang H, Sun L, Miao Z, Zhao T, Sun J, Sun X, Liu Z, Gao J, Zhao J, Chu X, Li J. The incidence of subclinical atherosclerosis in subjects with low and moderate cardiovascular risk. Clin Cardiol 2023; 46:1260-1267. [PMID: 37522647 PMCID: PMC10577528 DOI: 10.1002/clc.24087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 06/21/2023] [Accepted: 06/27/2023] [Indexed: 08/01/2023] Open
Abstract
BACKGROUND The cardiovascular risk models and subclinical atherosclerotic indicators are both recommended for cardiovascular risk stratification. The accordance between the incidence of subclinical atherosclerosis and subjects with low and moderate cardiovascular risk is unclear. HYPOTHESIS Subjects with low and moderate cardiovascular risk have a lower incidence of subclinical atherosclerosis compared with subjects with high risk. METHODS Brachial-ankle pulse wave velocity (BaPWV) and brachial flow-mediated dilation (BFMD) were measured in 421 subjects without a history of atherosclerotic cardiovascular disease (ASCVD) from October 2016 to January 2020. All subjects were classified into low, moderate, and high risk based on Framingham and China-par risk models respectively. RESULTS Mean age was 57.05 ± 9.35 years and 248 (58.9%) were male. In subjects with low, moderate, and high risk assessed by Framingham and China-par risk models, the percentage of abnormal BaPWV ( > 1400 cm/s) was 42.9%, 70.1%, 85.7%, and 40.4%, 71.4%, 89.7%, respectively. Meanwhile, the percentage of abnormal BFMD ( ≤ 7%) was 43.8%, 68.5%, 77.3%, and 44.9%,72.1%, and 76.6%. According to Framingham-based high-risk categories, positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity for BaPWV abnormality were 85.7%, 39.4%, 36.1%, and 87.5%, respectively. For BFMD abnormality, the values were 77.3%, 40.1%, 34.1%, and 81.8%, respectively. According to China-par high-risk categories, the values for BaPWV abnormality were 89.7%, 43.8%, 45.6%, and 89.0%, respectively. For BFMD abnormality, the values were 76.6%, 41.3%, 40.7%, and 77%, respectively. In multivariate analysis, age and blood pressure were the independent predictors for subclinical atherosclerosis in subjects with low-moderate risk. CONCLUSIONS More than one-half of subjects with low and moderate risk already have detectable subclinical atherosclerosis, indicating higher cardiovascular risk beyond the traditional stratification.
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Affiliation(s)
- Yan Li
- Department of Geriatrics, Xuanwu Hospital, Capital Medical UniversityNational Clinical Research Center for Geriatric DiseasesBeijingChina
| | - Yinghua Zhang
- Department of CardiologyChui Yang Liu Hospital affiliated to Tsinghua UniversityBeijingChina
| | - Keling Xiao
- Department of Geriatrics, Xuanwu Hospital, Capital Medical UniversityNational Clinical Research Center for Geriatric DiseasesBeijingChina
| | - Jin Si
- Department of Geriatrics, Xuanwu Hospital, Capital Medical UniversityNational Clinical Research Center for Geriatric DiseasesBeijingChina
| | - Haoyu Zhang
- Department of Geriatrics, Xuanwu Hospital, Capital Medical UniversityNational Clinical Research Center for Geriatric DiseasesBeijingChina
| | - Lijie Sun
- Department of Geriatrics, Xuanwu Hospital, Capital Medical UniversityNational Clinical Research Center for Geriatric DiseasesBeijingChina
| | - Zupei Miao
- Department of Geriatrics, Xuanwu Hospital, Capital Medical UniversityNational Clinical Research Center for Geriatric DiseasesBeijingChina
| | - Ting Zhao
- Department of Geriatrics, Xuanwu Hospital, Capital Medical UniversityNational Clinical Research Center for Geriatric DiseasesBeijingChina
| | - Jinghao Sun
- Department of Geriatrics, Xuanwu Hospital, Capital Medical UniversityNational Clinical Research Center for Geriatric DiseasesBeijingChina
| | - Xipeng Sun
- Department of Cardiology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Zhi Liu
- Department of Cardiology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Jing Gao
- Department of Cardiology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Jing Zhao
- Health Management Center, Xuanwu hospitalCapital Medical UniversityBeijingChina
| | - Xi Chu
- Health Management Center, Xuanwu hospitalCapital Medical UniversityBeijingChina
| | - Jing Li
- Department of Geriatrics, Xuanwu Hospital, Capital Medical UniversityNational Clinical Research Center for Geriatric DiseasesBeijingChina
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Liu B, Liu X, Sun C, Zhuo Z, Wei S, Liu Z, Zhang S, Chen Y, Tian Y, Kang N, Hou J, Wang C. Association of at-home and out-of-home eating frequency with the estimated 10-year arteriosclerotic cardiovascular disease risk in rural population: the Henan Rural Cohort Study. Eur J Nutr 2023; 62:2929-2938. [PMID: 37405440 DOI: 10.1007/s00394-023-03200-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 06/23/2023] [Indexed: 07/06/2023]
Abstract
PURPOSE Insufficient evidence currently exists regarding the relationship between eating frequency and arteriosclerotic cardiovascular disease (ASCVD). Thus, the objective of this study was to explore the association of at-home eating (AHE) and out-of-home eating (OHE) frequency with 10-year ASCVD risk. METHODS A total of 23,014 participants were included from the Henan Rural Cohort Study. A face-to-face questionnaire was used to acquire data on the frequency of OHE and AHE. The relationship of OHE and AHE frequency with 10-year ASCVD risk was evaluated by logistic regression. Mediation analysis was conducted to evaluate whether BMI mediated the association of OHE and AHE frequency with 10-year ASCVD risk. RESULTS The adjusted OR and 95% CI of 10-year ASCVD risk for participants who ate out 7 or more times a week was 2.012 (1.666, 2.429) compared with participants who had OHE 0 times. Compared to those who had AHE ≤ 11 times, the adjusted OR and 95% CI for the participants eating every meal at home (21 times) was 0.611 (0.486, 0.769). The relationship of OHE and AHE frequency with 10-year ASCVD risk was mediated by BMI, and the proportion of BMI explained was 25.3% and 36.6%. CONCLUSIONS The OHE frequency was associated with increased 10-year ASCVD risk, while AHE was related to decreased 10-year ASCVD risk, and BMI may play a partial mediating role in the relationship. Implementing health promotion strategies that promote AHE and discourage frequent OHE may prove to be an effective approach to preventing and controlling ASCVD. TRIAL REGISTRATION NUMBER ChiCTR-OOC-15006699 (2015-07-06).
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Affiliation(s)
- Beibei Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Chunyang Sun
- Department of Preventive Medicine, School of Medicine, Henan University of Chinese Medicine, Zhengzhou, Henan, People's Republic of China
| | - Zhuang Zhuo
- School of Life Science, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Shouzheng Wei
- Department of Pediatrics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Zihan Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Sen Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Yifei Chen
- Department of Preventive Medicine, School of Medicine, Henan University of Chinese Medicine, Zhengzhou, Henan, People's Republic of China
| | - Yuan Tian
- Department of Preventive Medicine, School of Medicine, Henan University of Chinese Medicine, Zhengzhou, Henan, People's Republic of China
| | - Ning Kang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
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Li B, Wen F, Liu K, Xie Y, Zhang F, Li P, Sun Y, Qu A, Yang X, Zhang L. The mediation effect of lipids, blood pressure and BMI between air pollutant mixture and atherosclerotic cardiovascular disease: The CHCN-BTH cohort study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 264:115491. [PMID: 37729805 DOI: 10.1016/j.ecoenv.2023.115491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/11/2023] [Accepted: 09/14/2023] [Indexed: 09/22/2023]
Abstract
BACKGROUND The combine effect of air pollutant mixture on atherosclerotic cardiovascular disease (ASCVD) remain undefined. This study aims to explore the association between long-term exposure of air pollutants and ASCVD, focusing on the mediating role of lipids, blood pressure and BMI. METHODS This study was based on the CHCN-BTH cohort study. The annual concentrations of air pollutants and PM2.5 constituents were sourced from in the Tracking Air Pollution in China (TAP) and ChinaHighAirPollutants (CHAP) datasets from 2014 to 2019. A Cox mixed-effects model was used to investigate the associations between long-term exposure of air pollutants and ASCVD. The combined impact of the air pollutant mixture was assessed using Quantile g-Computation. Stratified, sensitivity, and mediation analyses were conducted. RESULTS A total of 27,134 participants aged 18-80 were recruited in the present study. We found that each IQR increase of PM2.5, PM1, NO2, O3, BC, SO42-, and OM were significantly associated with the incidence of ASCVD, the hazard ratios (HRs) and 95 % confidence interval (CI) were 1.55 (1.35, 1.78), 1.46 (1.27, 1.67), 1.30 (1.21, 1.39), 1.66 (1.41,1.95), 2.14 (1.63, 2.83), 1.65 (1.25, 2.17) and 1.92(1.52, 2.45), respectively. The combined effect of air pollutant mixture on ASCVD was 1.79 (1.46, 2.20), PM2.5 contributed 83.3 % to this combined effect. Mediation effect models suggested that air pollutants and ASCVD might be mediated through SBP, DBP, HDL-C, LDL-C, hsCRP and BMI (mediation proportion range from 1.3 % to 26.1 %), Notably, HDL-C played mediation roles of 11.3 % (7.0 %, 18.4), 26.1 % (17.7 %, 38.1 %) and 25.4 % (15.4, 47.7 %) in the effects of long-term exposure to PM2.5, PM1 and OM on ASCVD, respectively. CONCLUSIONS Long-term, high-level air pollutant exposure was significantly associated with an elevated risk of ASCVD, particularly for PM2.5. Blood pressure, lipids and BMI, especially HDL-C, may mediate the effects of air pollutants exposure on ASCVD.
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Affiliation(s)
- Bingxiao Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Fuyuan Wen
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Kuo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Yunyi Xie
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Fengxu Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Pandi Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Yuan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Aibin Qu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xiaojun Yang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Ling Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
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LI JJ, ZHAO SP, ZHAO D, LU GP, PENG DQ, LIU J, CHEN ZY, GUO YL, WU NQ, YAN SK, WANG ZW, GAO RL. 2023 China Guidelines for Lipid Management. J Geriatr Cardiol 2023; 20:621-663. [PMID: 37840633 PMCID: PMC10568545 DOI: 10.26599/1671-5411.2023.09.008] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2023] Open
Abstract
Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death among urban and rural residents in China, and elevated low-density lipoprotein cholesterol (LDL-C) is a risk factor for ASCVD. Considering the increasing burden of ASCVD, lipid management is of the utmost importance. In recent years, research on blood lipids has made breakthroughs around the world, hence a revision of China guidelines for lipid management is imperative, especially since the target lipid levels in the general population vary in respect to the risk of ASCVD. The level of LDL-C, which can be regarded as appropriate in a population without frisk factors, can be considered abnormal in people at high risk of developing ASCVD. As a result, the "Guidelines for the prevention and treatment of dyslipidemia" were adapted into the "China Guidelines for Lipid Management" (henceforth referred to as the new guidelines) by an Experts' committee after careful deliberation. The new guidelines still recommend LDL-C as the primary target for lipid control, with CVD risk stratification to determine its target value. These guidelines recommend that moderate intensity statin therapy in adjunct with a heart-healthy lifestyle, be used as an initial line of treatment, followed by cholesterol absorption inhibitors or/and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, as necessary. The new guidelines provide guidance for lipid management across various age groups, from children to the elderly. The aim of these guidelines is to comprehensively improve the management of lipids and promote the prevention and treatment of ASCVD by guiding clinical practice.
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Affiliation(s)
- Jian-Jun LI
- National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Shui-Ping ZHAO
- The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Dong ZHAO
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Guo-Ping LU
- Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Dao-Quan PENG
- The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jing LIU
- Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Zhen-Yue CHEN
- Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yuan-Lin GUO
- National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Na-Qiong WU
- National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Sheng-Kai YAN
- Affiliated Hospital of Zunyi Medical University, School of Laboratory Medicine of Zunyi Medical University, Zunyi, Guizhou, China
| | - Zeng-Wu WANG
- National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Run-Lin GAO
- National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
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145
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Wang S, Zhao G, Zhang C, Kang N, Liao W, Wang C, Xie F. Association of Fine Particulate Matter Constituents with the Predicted 10-Year Atherosclerotic Cardiovascular Disease Risk: Evidence from a Large-Scale Cross-Sectional Study. TOXICS 2023; 11:812. [PMID: 37888663 PMCID: PMC10611010 DOI: 10.3390/toxics11100812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 09/22/2023] [Accepted: 09/24/2023] [Indexed: 10/28/2023]
Abstract
Little is known concerning the associations of fine particulate matter (PM2.5) and its constituents with atherosclerotic cardiovascular disease (ASCVD). A total of 31,162 participants enrolled from the Henan Rural Cohort were used to specify associations of PM2.5 and its constituents with ASCVD. Hybrid machine learning was utilized to estimate the 3-year average concentration of PM2.5 and its constituents (black carbon [BC], nitrate [NO3-], ammonium [NH4+], inorganic sulfate [SO42-], organic matter [OM], and soil particles [SOIL]). Constituent concentration, proportion, and residual models were utilized to examine the associations of PM2.5 constituents with 10-year ASCVD risk and to identify the most hazardous constituent. The isochronous substitution model (ISM) was employed to analyze the substitution effect between PM2.5 constituents. We found that each 1 μg/m3 increase in PM2.5, BC, NH4+, NO3-, OM, SO42-, and SOIL was associated with a 3.5%, 49.3%, 19.4%, 10.5%, 21.4%, 14%, and 28.5% higher 10-year ASCVD risk, respectively (all p < 0.05). Comparable results were observed in proportion and residual models. The ISM found that replacing BC with other constituents will generate the greatest health benefits. The results indicated that long-term exposure to PM2.5 and its constituents were associated with increased risks of ASCVD, with BC being the most attributable constituent.
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Affiliation(s)
- Sheng Wang
- Key Laboratory of Tobacco Chemistry, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450003, China; (S.W.); (G.Z.)
| | - Ge Zhao
- Key Laboratory of Tobacco Chemistry, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450003, China; (S.W.); (G.Z.)
| | - Caiyun Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China; (C.Z.); (N.K.); (W.L.)
| | - Ning Kang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China; (C.Z.); (N.K.); (W.L.)
| | - Wei Liao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China; (C.Z.); (N.K.); (W.L.)
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China; (C.Z.); (N.K.); (W.L.)
| | - Fuwei Xie
- Key Laboratory of Tobacco Chemistry, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450003, China; (S.W.); (G.Z.)
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146
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Tao S, Yu L, Yang D, Yao R, Zhang L, Huang L, Shao M. Development and validation of a clinical prediction model for detecting coronary heart disease in middle-aged and elderly people: a diagnostic study. Eur J Med Res 2023; 28:375. [PMID: 37749613 PMCID: PMC10521501 DOI: 10.1186/s40001-023-01233-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 07/16/2023] [Indexed: 09/27/2023] Open
Abstract
OBJECTIVE To develop and validate a multivariate prediction model to estimate the risk of coronary heart disease (CHD) in middle-aged and elderly people and to provide a feasible method for early screening and diagnosis in middle-aged and elderly CHD patients. METHODS This study was a single-center, retrospective, case-control study. Admission data of 932 consecutive patients with suspected CHD were retrospectively assessed from September 1, 2020 to December 31, 2021 in the Department of Integrative Cardiology at China-Japan Friendship Hospital. A total of 839 eligible patients were included in this study, and 588 patients were assigned to the derivation set and 251 as the validation set at a 7:3 ratio. Clinical characteristics of included patients were compared between derivation set and validation set by univariate analysis. The least absolute shrinkage and selection operator (Lasso) regression analysis method was performed to avoid collinearity and identify key potential predictors. Multivariate logistic regression analysis was used to construct a clinical prediction model with identified predictors for clinical practice. Bootstrap validation was used to test performance and eventually we obtained the actual model. And the Hosmer-Lemeshow test was carried out to evaluate the goodness-fit of the constructed model. The area under curve (AUC) of receiver operating characteristic (ROC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were plotted and utilized with validation set to comprehensively evaluate the predictive accuracy and clinical value of the model. RESULTS A total of eight indicators were identified as risk factors for the development of CHD in middle-aged and elderly people by univariate analysis. Of these candidate predictors, four key parameters were defined to be significantly related to CHD by Lasso regression analysis, including age (OR 1.034, 95% CI 1.002 ~ 1.067, P = 0.040), hemoglobin A1c (OR 1.380, 95% CI 1.078 ~ 1.768, P = 0.011), ankle-brachial index (OR 0.078, 95% CI 0.012 ~ 0.522, P = 0.009), and brachial artery flow-mediated vasodilatation (OR 0.848, 95% CI 0.726 ~ 0.990, P = 0.037). The Hosmer-Lemeshow test showed a good calibration performance of the clinical prediction model (derivation set, χ2 = 7.865, P = 0.447; validation set, χ2 = 11.132, P = 0.194). The ROCs of the nomogram in the derivation set and validation set were 0.722 and 0.783, respectively, suggesting excellent predictive power and suitable performance. The clinical prediction model presented a greater net benefit and clinical impact based on DCA and CIC analysis. CONCLUSION Overall, the development and validation of the multivariate model combined the laboratory and clinical parameters of patients with CHD, which could be beneficial to the individualized prediction of middle-aged and elderly people, and helped to facilitate clinical assessments and decisions during treatment and management of CHD.
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Affiliation(s)
- Shiyi Tao
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Lintong Yu
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Deshuang Yang
- Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, China
| | - Ruiqi Yao
- Department of Internal Medicine, Shenzhen Nanshan Chinese Medicine Hospital, Guangdong, China
| | - Lanxin Zhang
- Department of Oncology, Guang'anmenHospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Li Huang
- Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, China
| | - Mingjing Shao
- Department of Integrative Cardiology, China-Japan Friendship Hospital, Beijing, China.
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147
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Wu W, Chen G, Wu K, Zheng H, Chen Y, Wang X, Huang Z, Cai Z, Cai Z, Chen Z, Lan Y, Chen S, Wu S, Chen Y. Cumulative exposure to high remnant-cholesterol concentrations increases the risk of cardiovascular disease in patients with hypertension: a prospective cohort study. Cardiovasc Diabetol 2023; 22:258. [PMID: 37735420 PMCID: PMC10515262 DOI: 10.1186/s12933-023-01984-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 09/06/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND The relationship of cumulative remnant-cholesterol (Cum-RC) concentration with the risk of cardiovascular disease (CVD) in patients with hypertension remains unclear. METHODS We studied data for 28,698 individuals for whom three consecutive total cholesterol, high-density lipoprotein-cholesterol (HDL-C), and triglyceride concentrations were available, and who did not have CVD (14,349 with hypertension and 14,349 without), that was collected between 2006 and 2010. Participants with hypertension were placed into four groups based on Cum-RC quartile: a Q1 group (< 26.40 mg/dl), a Q2 group (26.40-39.56 mg/dl), a Q3 group (39.57-54.65 mg/dl), and a Q4 group (≥ 54.66 mg/dl). Cox proportional hazards models were used to evaluate the relationship between Cum-RC and the risk of CVD. RESULTS Over a median 10.9 (interquartile range, 10.5-11.3) years, 1,444 participants with hypertension developed CVD. After adjustment for multiple potential confounding factors, and compared with the Q1 Cum-RC group of the participants with hypertension, the adjusted hazard ratios for CVD for the Q2-Q4 groups were 1.07(0.92,1.26), 1.08(0.91,1.28), and 1.26(1.03,1.54) (P = 0.0405); those for myocardial infarction were 1.51(1.00,2.31), 2.02(1.22,3.27), and 2.08(1.41,3.28) (P < 0.0001); and those for ischemic stroke were 1.02(0.84,1.24), 1.04(0.86,1.25), and 1.29(1.02,1.62), respectively (P = 0.0336). However, no significant relationship was found between Cum-RC and the risk of hemorrhage stroke. At the same Cum-RC, the risk of CVD was significantly higher in participants with hypertension than in those without. CONCLUSIONS A consistently high remnant-cholesterol concentration increases the risk of CVD in individuals with hypertension. Therefore, the achievement of blood pressure and RC concentration targets should help reduce the risk of CVD in individuals with hypertension.
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Affiliation(s)
- Weiqiang Wu
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, 69 Dongxia North RD, Shantou, 515000, China
- Shantou University Medical College, Shantou, China
| | - Guanzhi Chen
- Cardiac Arrhythmia Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kuangyi Wu
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, 69 Dongxia North RD, Shantou, 515000, China
- Shantou University Medical College, Shantou, China
| | - Huancong Zheng
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, 69 Dongxia North RD, Shantou, 515000, China
- Shantou University Medical College, Shantou, China
| | - Yanjuan Chen
- Department of Endocrinology, Second Affiliated Hospital of Shantou University Medical College, Shantou, China
| | | | - Zegui Huang
- Shantou University Medical College, Shantou, China
| | - Zefeng Cai
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, 69 Dongxia North RD, Shantou, 515000, China
| | - Zhiwei Cai
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, 69 Dongxia North RD, Shantou, 515000, China
- Shantou University Medical College, Shantou, China
| | - Zhichao Chen
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, 69 Dongxia North RD, Shantou, 515000, China
| | - Yulong Lan
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, 69 Dongxia North RD, Shantou, 515000, China
| | - Shuohua Chen
- Department of Cardiology, Kailuan General Hospital, 57 Xinhua East RD, Tangshan, 063000, China
| | - Shouling Wu
- Department of Cardiology, Kailuan General Hospital, 57 Xinhua East RD, Tangshan, 063000, China.
| | - Youren Chen
- Department of Cardiology, Second Affiliated Hospital of Shantou University Medical College, 69 Dongxia North RD, Shantou, 515000, China.
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Li J, Tang W, Li S, He C, Dai Y, Feng S, Zeng C, Yang T, Meng Q, Meng J, Pan Y, Deji S, Zhang J, Xie L, Guo B, Lin H, Zhao X. Ambient PM2.5 and its components associated with 10-year atherosclerotic cardiovascular disease risk in Chinese adults. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 263:115371. [PMID: 37643506 DOI: 10.1016/j.ecoenv.2023.115371] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 08/11/2023] [Accepted: 08/12/2023] [Indexed: 08/31/2023]
Abstract
BACKGROUND Exposure to particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) may increase the risk of 10-year atherosclerotic cardiovascular disease (ASCVD) risk. While PM2.5 is comprised of various components, the evidence on the correlation of its components with 10-year ASCVD risk and which component contributes most remains limited. METHODS Data were derived from the baseline assessments of China Multi-Ethnic Cohort (CMEC). In total, 69,722 individuals aged 35-74 years were included into this study. The annual average concentration of PM2.5 and its components (black carbon, ammonium, nitrate, sulfate, organic matter, soil particles, and sea salt) were estimated by satellite remote sensing and chemical transport models. The ASCVD risk of individuals was calculated by the equations from the China-PAR Project (prediction for ASCVD risk in China). The relationship between single exposure to PM2.5 and its components and predicted 10-year ASCVD risk was assessed using the logistic regression model. The effect of joint exposure was estimated, and the most significant contributor was identified using the weighted quantile sum approach. RESULTS Totally 69,722 participants were included, of which 95.8 % and 4.2 % had low and high 10-year ASCVD risk, respectively. Per standard deviation increases in the 3-year average concentration of PM2.5 mass (odds ratio [OR] 1.23, 95 % confidence interval [CI]: 1.12-1.35), black carbon (1.21, 1.11-1.33), ammonium (1.21, 1.10-1.32), nitrate (1.25, 1.14-1.38), organic matter (1.29, 1.18-1.42), sulfate (1.17, 1.07-1.28), and soil particles (1.15, 1.04-1.26) were related to high 10-year ASCVD risk. The overall effect (1.19, 1.11-1.28) of the PM2.5 components was positively associated with 10-year ASCVD risk, and organic matter had the most contribution to this relationship. Female participants were more significantly impacted by PM2.5, black carbon, ammonium, nitrate, organic matter, sulfate, and soil particles compared to others. CONCLUSION Long-term exposure to PM2.5 mass, black carbon, ammonium, nitrate, organic matter, sulfate, and soil particles were positively associated with high 10-year ASCVD risk, while sea salt exhibited a protective effect. Moreover, the organic matter might take primary responsibility for the relationship between PM2.5 and 10-year ASCVD risk. Females were more susceptible to the adverse effect.
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Affiliation(s)
- Jiawei Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Wenge Tang
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
| | - Sicheng Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Congyuan He
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yucen Dai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Shiyu Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chunmei Zeng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Tingting Yang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 550025, China
| | - Qiong Meng
- Department of Epidemiology and Health Statistics, School of Public Health, Kunming Medical University, Kunming, Yunnan 850000, China
| | - Jiantong Meng
- Chengdu Center for Disease Control & Prevention, Chengdu, Sichuan 610041, China
| | | | - Suolang Deji
- Tibet Center for Disease Control and Prevention CN, Lhasa 850000, China
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Linshen Xie
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
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Guo Z, Chen Y, Zhang Y, Ding C, Li M, Xu L, Jin J. Associations among risk perception, health efficacy, and health behaviors for cardiovascular disease: an application of risk perception attitude framework. Front Cardiovasc Med 2023; 10:1201789. [PMID: 37771673 PMCID: PMC10525708 DOI: 10.3389/fcvm.2023.1201789] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 08/25/2023] [Indexed: 09/30/2023] Open
Abstract
Background There is currently a pervasive prevalence of cardiovascular disease (CVD) risk worldwide and an inadequate amount of action is being taken to promote healthy lifestyle habits. The risk perception attitude (RPA) framework, which classifies individuals based on their risk perception and efficacy belief, enables us to predict their preventive behaviors. We applied the RPA framework to analyze CVD prevention behaviors among Chinese adults and extended its application to CVD objective risk. Methods A cross-sectional survey was performed in two sites in Zhejiang Province, from March to August 2022, which contained self-reported CVD risk perception, objective CVD risk, efficacy belief, physical activity, healthy diet, and covariates. We used the RPA framework to categorize participants into four groups, then analysis was conducted to estimate inter-group differences in healthy behaviors. We further conducted a hierarchical logistic regression analysis with individuals' health behaviors as the dependent variable, using three blocks of independent variables. Results Among 739 participants, healthy physical activity and healthy diet had significant differences among four RPA groups, post hoc tests clarified that the proportion of respondents with healthy PA in the responsive group (61.6%) was significantly higher than that in the other three groups. Risk perception and efficacy belief significantly predicted health behavior against CVD; the relationship between absolute CVD risk and health behavior was moderated by efficacy belief. Conclusions Early CVD risk screening is crucial, but tailored support and a proper understanding of personal risk are essential to promote healthy behaviors. Developing communication and behavioral counseling intervention strategies on the basis of the RPA framework has the potential to promote healthy behaviors for CVD prevention.
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Affiliation(s)
- Zhiting Guo
- Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine (SAHZU), Hangzhou, China
| | - Yun Chen
- Public Health Department, Changxing County People’s Hospital, Huzhou, China
| | - Yuping Zhang
- Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine (SAHZU), Hangzhou, China
| | - Chuanqi Ding
- Emergency Department, Changxing County People’s Hospital, Huzhou, China
| | - Mei Li
- Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine (SAHZU), Hangzhou, China
| | - Linyan Xu
- Nursing Department, Lishui University School of Medicine, Lishui, China
| | - Jingfen Jin
- Nursing Department, The Second Affiliated Hospital of Zhejiang University School of Medicine (SAHZU), Hangzhou, China
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150
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Pei G, Liu R, Wang L, He C, Fu C, Wei Q. Monocyte to high-density lipoprotein ratio is associated with mortality in patients with coronary artery diseases. BMC Cardiovasc Disord 2023; 23:451. [PMID: 37697241 PMCID: PMC10496218 DOI: 10.1186/s12872-023-03461-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 08/19/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND Whether the monocyte to high-density lipoprotein ratio (MHR) is associated with the prognosis of coronary artery disease (CAD) is inconclusive. METHODS Patients with CAD were enrolled and their data were collected. Blood was sampled within 24 h after admission. Multivariate Cox regression analysis was performed to determine the relationship between the MHR and all-cause mortality as well as complications during hospitalization. RESULTS We included 5371 patients in our cohort study. Among them, 114 (2.12%) patients died in hospital. MHR was independently associated with all-cause mortality (hazard ratio [HR], 1.81; 95% confidence interval [CI] 1.35, 2.42), cardiovascular mortality (1.69; 1.17, 2.45) and non-cardiovascular mortality (2.04; 1.27, 3.28). This association was only observed in patients with hypertension (P for interaction = 0.003). Patients with higher MHR levels also have a higher risk of complications, including infection, pneumonia, electrolyte disturbance, gastrointestinal bleeding, multiple organ dysfunction syndrome, and disturbance of consciousness. The receiver operating characteristic (ROC) analysis showed that the MHR had higher prognostic values than monocytes and high-density lipoprotein. CONCLUSION MHR was an independent predictor of all-cause mortality and in-hospital complications in patients with CAD, especially in patients with hypertension.
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Affiliation(s)
- Gaiqin Pei
- Department of Rehabilitation Medicine and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, PR China
- Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, Sichuan, China
| | - Rui Liu
- Department of Rehabilitation Medicine and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, PR China
- Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, Sichuan, China
| | - Lu Wang
- Department of Rehabilitation Medicine and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, PR China
- Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, Sichuan, China
| | - Chengqi He
- Department of Rehabilitation Medicine and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, PR China
- Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, Sichuan, China
| | - Chenying Fu
- West China Hospital, National Clinical Research Center for Geriatrics, Sichuan University, Chengdu, Sichuan, China.
- Aging and Geriatric Mechanism Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Quan Wei
- Department of Rehabilitation Medicine and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, PR China.
- Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, Sichuan, China.
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