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Liu J, Wu G, Zhang C, Ruan J, Wang D, Zhang M, Wang L, Yang Y, Li X, Wang Y, Hui R, Zou Y, Kang L, Wang J, Song L. Improvement in sudden cardiac death risk prediction by the enhanced American College of Cardiology/American Heart Association strategy in Chinese patients with hypertrophic cardiomyopathy. Heart Rhythm 2020; 17:1658-1663. [PMID: 32311532 DOI: 10.1016/j.hrthm.2020.04.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 03/21/2020] [Accepted: 04/02/2020] [Indexed: 01/29/2023]
Abstract
BACKGROUND The lack of validated and effective sudden cardiac death (SCD) risk prediction methods is the biggest barrier to perform the lifesaving treatment with a prophylactic implantable cardioverter-defibrillator in Chinese patients with hypertrophic cardiomyopathy (HCM). OBJECTIVE This study aimed to evaluate the efficacy of 3 existing SCD risk prediction methods recommended by the 2011 American College of Cardiology Foundation and American Heart Association (ACCF/AHA) guideline, the 2014 European Society of Cardiology (ESC) guideline, and the 2019 enhanced American College of Cardiology (ACC)/AHA strategy in Chinese patients with HCM. METHODS The present study consisted of 1369 consecutive adult patients with HCM without a history of SCD events. The primary end point was a composite of SCD and equivalent events, namely, resuscitation from cardiac arrest and appropriate implantable cardioverter-defibrillator shock therapy for ventricular tachycardia or fibrillation. RESULTS During follow-up of 3.2 ± 2.4 years, 39 patients reached SCD end points, of whom 26 (66.7%) were correctly predicted as those at a high risk of SCD by using methods recommended by the 2019 enhanced ACC/AHA strategy, 20 (51.3%) by the 2011 ACCF/AHA guideline, but only 5 (12.8%) by the 2014 ESC guideline. The 2019 enhanced ACC/AHA strategy showed a higher C-statistic (0.647) for SCD prediction than did the 2011 ACCF/AHA guideline (0.598) and 2014 ESC guideline (0.605) and resulted in the correct reclassification of SCD risk when compared with the 2011 ACCF/AHA guideline (net reclassification index 0.113; P = .074) and 2014 ESC guideline (net reclassification index 0.245; P = .038). CONCLUSION The 2019 enhanced ACC/AHA strategy showed better predictive performance for SCD risk stratification in Chinese patients with HCM, with a notably high sensitivity.
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Affiliation(s)
- Jie Liu
- 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
| | - Guixin Wu
- 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
| | - Ce Zhang
- 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
| | - Jieyun Ruan
- 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
| | - Dong Wang
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Mo Zhang
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Limei Wang
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Yaoyao Yang
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Xinrong Li
- The National Engineering Research Centre for Miniaturized Detection Systems, Shaanxi Lifegen Co. Ltd, Shaanxi, China
| | - Yilu Wang
- Intensive Care Unit, Emergency General Hospital, Beijing, China
| | - Rutai Hui
- 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
| | - Yubao Zou
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Lianming Kang
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
| | - Jizheng Wang
- 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.
| | - Lei Song
- 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; Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
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352
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Dynamic Cerebral Autoregulation in Preclinical Atherosclerotic Cardiovascular Disease. J Stroke Cerebrovasc Dis 2020; 29:104810. [PMID: 32291129 DOI: 10.1016/j.jstrokecerebrovasdis.2020.104810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 03/06/2020] [Accepted: 03/09/2020] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVE The influence of atherosclerotic cardiovascular disease (ASCVD) on cerebral blood flow control is not well known. The aim of this study was to investigate the association between cardiovascular function and dynamic cerebral autoregulation (dCA) in patients with preclinical ASCVD. METHODS A total of 44 participants aged 26-76 years were divided into low- and high-risk groups according to the China assessment of ASCVD risk. The cardiac function was assessed by echocardiography. The beat-to-beat blood pressure and cerebral blood flow velocity were measured at rest. Spectral and transfer function analyses were used to calculate cerebral and systemic hemodynamic variability and to estimate dCA metrics. RESULTS There were no group differences in beat-to-beat heart rate, blood pressure, and cerebral blood flow velocity variability nor the ejection fraction, E/A and E'/A'. The dCA phase at very low frequency was reduced in the high-risk group (P = .03). Moreover, the dCA phase and E'/A' were negatively correlated with age, and dCA phase was positively correlated with E'/A' within the high-risk group (r2 = .517, P < .01). CONCLUSIONS These findings suggest that advancing age, particularly in the high-risk ASCVD group, impairs cerebral blood flow control and cardiac diastolic function which are correlated with each other and may interplay under the effects of ASCVD risk factors.
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353
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Li Q, Lin F, Gao Z, Huang F, Zhu P. Chinese ASCVD risk equations rather than pooled cohort equations are better to identify macro- and microcirculation abnormalities. BMC Cardiovasc Disord 2020; 20:145. [PMID: 32204696 PMCID: PMC7092674 DOI: 10.1186/s12872-020-01425-0] [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: 05/24/2019] [Accepted: 03/12/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND We hypothesized that discriminating the early subclinical organ damage would serve as a great opportunity for prevention against atherosclerotic cardiovascular disease (ASCVD). Brachial-ankle pulse wave velocity (baPWV), low retinal vascular fractal dimension, and albuminuria are surrogates of subclinical vascular changes. METHODS The aim of this study was to use Pooled Cohort Equations (PCE) and ASCVD risk equations derived from "Prediction for ASCVD Risk in China project (CHINA-PAR)" to observe the prevalence of macro- and microcirculation abnormalities. A total of 2166 subjects were involved. Characteristics were investigated using questionnaire and physical examinations. We calculated the urine albumin to creatinine ratio (UACR). The baPWV was measured using a fully automatic arteriosclerosis detector. The retinal vascular fractal dimension was measured by a semiautomated computer-based program. The 10-year ASCVD risk was estimated using the PCE and CHINA-PAR model. RESULTS The cut-off values for the elevated baPWV were 2.82 and 2.92% in the PCE model and CHINA-PAR model, respectively, with nearly 85% sensitivity and an average specificity of 74%. For low retinal fractal dimension, at the cut-off point of 3.8%, we acquired an acceptable sensitivity of 66.27-68.24% and specificity of 62.57-67.45%. All the C-statistics presented a significant improvement from the PCE model to the CHINA-PAR model (P < 0.05). For all categories-net reclassification improvement (NRI) values were significant and clearly varied (0.329, 0.183, and 0.104, respectively) depending on the cut-off set at 3%. CONCLUSION Our study demonstrated that the CHINA-PAR equations rather than PCE could provide better identification of macro- and microcirculation abnormalities. A lower cut-off point for the subclinical vascular changes may be selected in a population from southeast China.
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Affiliation(s)
- Qiaowei Li
- Department of Geriatric Medicine, Fujian Provincial Hospital, Fujian Provincial Center for Geriatrics, Fujian Provincial Key Laboratory of Geriatric Disease, Shengli Clinical Medical College of Fujian Medical University, 134 East Street, Fuzhou, 350001, Fujian, China
| | - Fan Lin
- Department of Geriatric Medicine, Fujian Provincial Hospital, Fujian Provincial Center for Geriatrics, Fujian Provincial Key Laboratory of Geriatric Disease, Shengli Clinical Medical College of Fujian Medical University, 134 East Street, Fuzhou, 350001, Fujian, China
| | - Zhonghai Gao
- Department of ophthalmology, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
| | - Feng Huang
- Department of Geriatric Medicine, Fujian Provincial Hospital, Fujian Provincial Center for Geriatrics, Fujian Provincial Key Laboratory of Geriatric Disease, Shengli Clinical Medical College of Fujian Medical University, 134 East Street, Fuzhou, 350001, Fujian, China.
| | - Pengli Zhu
- Department of Geriatric Medicine, Fujian Provincial Hospital, Fujian Provincial Center for Geriatrics, Fujian Provincial Key Laboratory of Geriatric Disease, Shengli Clinical Medical College of Fujian Medical University, 134 East Street, Fuzhou, 350001, Fujian, China.
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354
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Yang L, Wu H, Jin X, Zheng P, Hu S, Xu X, Yu W, Yan J. Study of cardiovascular disease prediction model based on random forest in eastern China. Sci Rep 2020; 10:5245. [PMID: 32251324 PMCID: PMC7090086 DOI: 10.1038/s41598-020-62133-5] [Citation(s) in RCA: 144] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 02/28/2020] [Indexed: 12/13/2022] Open
Abstract
Cardiovascular disease (CVD) is the leading cause of death worldwide and a major public health concern. CVD prediction is one of the most effective measures for CVD control. In this study, 29930 subjects with high-risk of CVD were selected from 101056 people in 2014, regular follow-up was conducted using electronic health record system. Logistic regression analysis showed that nearly 30 indicators were related to CVD, including male, old age, family income, smoking, drinking, obesity, excessive waist circumference, abnormal cholesterol, abnormal low-density lipoprotein, abnormal fasting blood glucose and else. Several methods were used to build prediction model including multivariate regression model, classification and regression tree (CART), Naïve Bayes, Bagged trees, Ada Boost and Random Forest. We used the multivariate regression model as a benchmark for performance evaluation (Area under the curve, AUC = 0.7143). The results showed that the Random Forest was superior to other methods with an AUC of 0.787 and achieved a significant improvement over the benchmark. We provided a CVD prediction model for 3-year risk assessment of CVD. It was based on a large population with high risk of CVD in eastern China using Random Forest algorithm, which would provide reference for the work of CVD prediction and treatment in China.
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Affiliation(s)
- Li Yang
- Zhejiang Provincial Center for Cardiovascular Disease Control and Prevention, Zhejiang Hospital, Hangzhou, 310013, China
- Key Laboratory of Public Health Safety, Ministry of Education, Health Communication Institute, Fudan University, 138 Yixueyuan Road, Shanghai, 200032, China
| | - Haibin Wu
- Ewell Technology Co., Ltd, Tower D of Oriental Communication Technology City, Hangzhou, 310000, China
| | - Xiaoqing Jin
- Chinese Acupuncture Department, Zhejiang Hospital, Hangzhou, 310013, China
| | - Pinpin Zheng
- Key Laboratory of Public Health Safety, Ministry of Education, Health Communication Institute, Fudan University, 138 Yixueyuan Road, Shanghai, 200032, China
| | - Shiyun Hu
- Zhejiang Provincial Center for Cardiovascular Disease Control and Prevention, Zhejiang Hospital, Hangzhou, 310013, China
| | - Xiaoling Xu
- Zhejiang Provincial Center for Cardiovascular Disease Control and Prevention, Zhejiang Hospital, Hangzhou, 310013, China
| | - Wei Yu
- Zhejiang Provincial Center for Cardiovascular Disease Control and Prevention, Zhejiang Hospital, Hangzhou, 310013, China
| | - Jing Yan
- Zhejiang Provincial Center for Cardiovascular Disease Control and Prevention, Zhejiang Hospital, Hangzhou, 310013, China.
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355
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Xia X, Liu F, Yang X, Li J, Chen J, Liu X, Cao J, Shen C, Yu L, Zhao Y, Wu X, Zhao L, Li Y, Huang J, Lu X, Gu D. Associations of egg consumption with incident cardiovascular disease and all-cause mortality. SCIENCE CHINA-LIFE SCIENCES 2020; 63:1317-1327. [PMID: 32170624 DOI: 10.1007/s11427-020-1656-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 02/27/2020] [Indexed: 10/24/2022]
Abstract
Eggs are nutrient-dense while also loaded with abundant cholesterol, thus making the public hesitant about their consumption. We conducted the study to investigate if egg consumption is associated with incident cardiovascular disease (CVD) and all-cause mortality. Using the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China, we included 102,136 adults free of CVD and assessed their egg consumption with food-frequency questionnaires. CVD endpoints and all-cause mortality were confirmed during follow-ups by interviewing participants or their proxies and checking hospital records/death certificates. The HRs (95% CIs) were calculated using the cohort-stratified Cox regression models. During 777,163 person-years of follow-up, we identified 4,848 incident CVD and 5,511 deaths. U-shaped associations of egg consumption with incident CVD and all-cause mortality were observed. Compared with consumption of 3-<6/week, the multivariable-adjusted HRs (95% CIs) of <1/week and ≥10/week for incident CVD were 1.22 (1.11 to 1.35) and 1.39 (1.28 to 1.52), respectively. The corresponding HRs (95% CIs) for all-cause mortality were 1.29 (1.18 to 1.41) and 1.13 (1.04 to 1.24). Our findings identified that both low and high consumption were associated with increased risk of incident CVD and all-cause mortality, highlighting that moderate egg consumption of 3-<6/week should be recommended for CVD prevention in China.
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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, 100037, 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
| | - Xueli Yang
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, 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
| | - Jichun Chen
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100037, China
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou, 510080, 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
| | - Chong Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Ling Yu
- Department of Cardiology, Fujian Provincial Hospital, Fuzhou, 350014, China
| | - Yingxin Zhao
- Shandong First Medical University, Jinan, 271016, 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
| | - 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
| | - 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
| | - 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.
| | - 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.
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356
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Xia S, Du X, Guo L, Du J, Arnott C, Lam CSP, Huffman MD, Arima H, Yuan Y, Zheng Y, Wu S, Guang X, Zhou X, Lin H, Cheng X, Anderson CS, Dong J, Ma C. Sex Differences in Primary and Secondary Prevention of Cardiovascular Disease in China. Circulation 2020; 141:530-539. [PMID: 32065775 DOI: 10.1161/circulationaha.119.043731] [Citation(s) in RCA: 74] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
BACKGROUND Despite improvements in diagnostic and therapeutic interventions to combat cardiovascular disease (CVD) in recent decades, there are significant ongoing access gaps and sex disparities in prevention that have not been adequately quantified in China. METHODS A representative, cross-sectional, community-based survey of adults (aged ≥45 years) was conducted in 7 geographic regions of China between 2014 and 2016. Logistic regression models were used to determine sex differences in primary and secondary CVD prevention, and any interaction by age, education level, and area of residence. Data are presented as adjusted odds ratios (ORs) and 95% CIs. RESULTS Of 47 841 participants (61.3% women), 5454 (57.2% women) had established CVD and 9532 (70.5% women) had a high estimated 10-year CVD risk (≥10%). Only 48.5% and 48.6% of women and 39.3% and 59.8% of men were on any kind of blood pressure (BP)-lowering medication, lipid-lowering medication, or antiplatelet therapy for primary and secondary prevention, respectively. Women with established CVD were significantly less likely than men to receive BP-lowering medications (OR, 0.79 [95% CI, 0.65-0.95]), lipid-lowering medications (OR, 0.69 [95% CI, 0.56-0.84]), antiplatelets (OR, 0.53 [95% CI, 0.45-0.62]), or any CVD prevention medication (OR, 0.62 [95% CI, 0.52-0.73]). Women with established CVD, however, had better BP control (OR, 1.31 [95% CI, 1.14-1.50]) but less well-controlled low-density lipoprotein cholesterol (OR, 0.66 [95% CI, 0.57-0.76]), and were less likely to smoke (OR, 13.89 [95% CI, 11.24-17.15]) and achieve physical activity targets (OR, 1.92 [95% CI, 1.61-2.29]). Conversely, women with high CVD risk were less likely than men to have their BP, low-density lipoprotein cholesterol, and bodyweight controlled (OR, 0.46 [95% CI, 0.38-0.55]; OR, 0.60 [95% CI, 0.52-0.69]; OR, 0.55 [95% CI, 0.48-0.63], respectively), despite a higher use of BP-lowering medications (OR, 1.21 [95% CI, 1.01-1.45]). Younger patients (<65 years) with established CVD were less likely to be taking CVD preventive medications, but there were no sex differences by area of residence or education level. CONCLUSIONS Large and variable gaps in primary and secondary CVD prevention exist in China, particularly for women. Effective CVD prevention requires an improved overall nationwide strategy and a special emphasis on women with established CVD, who have the greatest disparity and the most to benefit.
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Affiliation(s)
- Shijun Xia
- Beijing Anzhen Hospital, Capital Medical University, China (S.X., X.D., L.G., J. Dong, C.M.)
| | - Xin Du
- Beijing Anzhen Hospital, Capital Medical University, China (S.X., X.D., L.G., J. Dong, C.M.).,Heart Health Research Centre, Beijing, China (X.D., C.S.A.).,The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, Australia (X.D., C.A., C.S.P.L., M.D.H., C.S.A.)
| | - Lizhu Guo
- Beijing Anzhen Hospital, Capital Medical University, China (S.X., X.D., L.G., J. Dong, C.M.)
| | - Jing Du
- Beijing Centre for Disease Prevention and Control, China (J. Du)
| | - Clare Arnott
- Heart Health Research Centre, Beijing, China (X.D., C.S.A.).,The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, Australia (X.D., C.A., C.S.P.L., M.D.H., C.S.A.).,Cardiology Department (C.A.), Royal Prince Alfred Hospital, Sydney, Australia.,Sydney Medical School, University of Sydney, Australia (C.A.)
| | - Carolyn S P Lam
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, Australia (X.D., C.A., C.S.P.L., M.D.H., C.S.A.).,National Heart Centre Singapore and Duke-National University of Singapore (C.S.P.L.).,University Medical Centre Groningen, The Netherlands (C.S.P.L.)
| | - Mark D Huffman
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, Australia (X.D., C.A., C.S.P.L., M.D.H., C.S.A.).,Northwestern University Feinberg School of Medicine, Chicago, IL (M.D.H.)
| | - Hisatomi Arima
- Department of Preventive Medicine and Public Health, Faculty of Medicine, Fukuoka University, Japan (H.A.)
| | - Yiqiang Yuan
- The Seventh People's Hospital of Zhengzhou, Henan Province, China (Y.Y.)
| | - Yang Zheng
- Department of Cardiology, The First Hospital of Jilin University, Changchun, China (Y.Z.)
| | - Shulin Wu
- Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China (S.W.)
| | - Xuefeng Guang
- Department of Cardiology, Yanan Hospital of Kunming, Kunming, Yunnan Province, China (X.G.)
| | - Xianhui Zhou
- Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumchi, Xinjiang Uyghur Autonomous Region, China (X.Z.)
| | - Hongbo Lin
- Yinzhou District Centre for Disease Control and Prevention, Ningbo, Zhejiang Province, China (H.L.)
| | - Xiaoshu Cheng
- Cardiovascular Department, The Second Affiliated Hospital of Nanchang University, Jiangxi Province, China (X.C.)
| | - Craig S Anderson
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, Australia (X.D., C.A., C.S.P.L., M.D.H., C.S.A.).,Neurology Department (C.S.A.), Royal Prince Alfred Hospital, Sydney, Australia.,The George Institute China at Peking University Health Science Centre, China (C.S.A.)
| | - Jianzeng Dong
- Beijing Anzhen Hospital, Capital Medical University, China (S.X., X.D., L.G., J. Dong, C.M.).,The First Affiliated Hospital of Zhengzhou University, Henan Province, China (J. Dong)
| | - Changsheng Ma
- Beijing Anzhen Hospital, Capital Medical University, China (S.X., X.D., L.G., J. Dong, C.M.)
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Liu S, Fang F, Fan G. Potassium selenocyanoacetate reduces the blood triacylglycerol and atherosclerotic plaques in high-fat-dieted mice. Cardiovasc Diagn Ther 2020; 9:561-567. [PMID: 32038945 DOI: 10.21037/cdt.2019.12.05] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Controlling blood lipid levels at the early stage of cardiovascular disease is a major focus of global disease prevention studies on atherosclerosis. The aim of our study was to investigate the effects of potassium selencyanoacetate on the blood lipid profiles and the formation of atherosclerotic plaques in mice fed with a high-fat diet. Methods Forty ApoE-/- male mice aged 8-10 weeks were randomly divided into the treatment group (n=20) and control group (n=20). The mice in the treatment group were given the high-fat diet supplemented with potassium selencyanoacetate (4.63 mg/kg/day) through a gavage, whereas the control group were fed with a same high-fat diet with 1.5 mL of normal saline only. After 16 weeks, the mice were euthanized using inhalation anesthetic methods. The aortas were isolated and stained with oil red O to observe the formation of plaques. Blood samples were collected from each animal to examine the levels of total cholesterol (TC), triacylglycerol (TG), HDL cholesterol (HDL-Ch), LDL cholesterol (LDL-Ch), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and plasma urea. Results The percentage of the atherosclerotic plaques area was significantly lower in the treatment group than the control group (P=0.017). The levels of TG, ALT, AST, and plasma urea were significantly lower in the treatment group than the control group (all P<0.05). However, the levels of TC, HDL-Ch, and LDL-Ch were not significantly different between two groups (all P>0.05). Conclusions Potassium selencyanoacetate could safely reduce the TG level and high-fat-diet induced atherosclerotic plaques in mice, which could be used as a potential drug to prevent cardiovascular atherosclerotic diseases.
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Affiliation(s)
- Shaoqin Liu
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Fang Fang
- Department of Cardiology, Central War Zone General Hospital of the Chinese People's Liberation Army, Wuhan 430061, China
| | - Guanghui Fan
- School of Public Health, Southern Medical University, Guangzhou 510515, China.,Department of Cardiology, Central War Zone General Hospital of the Chinese People's Liberation Army, Wuhan 430061, China.,Affiliated Wuhan Medical College of Southern Medical University, Wuhan 430061, China
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358
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A Nomogram Based on Apelin-12 for the Prediction of Major Adverse Cardiovascular Events after Percutaneous Coronary Intervention among Patients with ST-Segment Elevation Myocardial Infarction. Cardiovasc Ther 2020; 2020:9416803. [PMID: 32099583 PMCID: PMC7026703 DOI: 10.1155/2020/9416803] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 01/03/2020] [Accepted: 01/14/2020] [Indexed: 12/18/2022] Open
Abstract
Objective This study aimed to establish a clinical prognostic nomogram for predicting major adverse cardiovascular events (MACEs) after primary percutaneous coronary intervention (PCI) among patients with ST-segment elevation myocardial infarction (STEMI). Methods Information on 464 patients with STEMI who performed PCI procedures was included. After removing patients with incomplete clinical information, a total of 460 patients followed for 2.5 years were randomly divided into evaluation (n = 324) and validation (n = 324) and validation ( Results Apelin-12 change rate, apelin-12 level, age, pathological Q wave, myocardial infarction history, anterior wall myocardial infarction, Killip's classification > I, uric acid, total cholesterol, cTnI, and the left atrial diameter were independently associated with MACEs (all P < 0.05). After incorporating these 11 factors, the nomogram achieved good concordance indexes of 0.758 (95%CI = 0.707–0.809) and 0.763 (95%CI = 0.689–0.837) in predicting MACEs in the evaluation and validation cohorts, respectively, and had well-fitted calibration curves. The decision curve analysis (DCA) revealed that the nomogram was clinically useful. Conclusions We established and validated a novel nomogram that can provide individual prediction of MACEs for patients with STEMI after PCI procedures in a Chinese population. This practical prognostic nomogram may help clinicians in decision making and enable a more accurate risk assessment.
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359
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Gao E, Hou J, Zhou Y, Ma J, Li T, Zhang J, Wang L, Chen W, Yuan J. Mediation effect of platelet indices on the association of daytime nap duration with 10-year ASCVD risk. Platelets 2020; 32:82-89. [PMID: 32009507 DOI: 10.1080/09537104.2020.1719055] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Daytime nap is associated with the risk of atherosclerotic cardiovascular disease (ASCVD). However, the contribution of platelet to the association of daytime nap with ASCVD remains unclear. We analyzed the mediation effect of abnormal platelet indices on the association between daytime nap and 10-year ASCVD risk. The participants of this study were 2445 adults aged 30 to 74 years without ASCVD from the baseline Wuhan residents (n = 3053) of the Wuhan-Zhuhai (WHZH) Cohort Study. Participants completed the questionnaire and physical examination (including blood pressure, height, weight, and blood biochemical indicators). We assessed the association of daytime nap or nocturnal sleep duration with 10-year ASCVD risk and mediation effects of platelet indices on the associations using generalized linear models (GLM). Individuals with daytime nap duration of 30 or 60 min had a 1.37- (95%CI: 1.05, 1.78) or 1.44- (95%CI: 1.17, 1.78) fold increased risk of 10-year ASCVD compared with non-nappers. As compared with non-nappers, MPV values or MPV/PLT ratio mediated 15.29% or 6.18% of the association of daytime nap duration of 30 min with 10-year ADCVD risk as well as 19.21% or 7.61% of the association of daytime nap duration of 60 min with 10-year ADCVD risk (all p < .05). Platelet might partially contribute to increased 10-year ASCVD risk in individuals with daytime nap duration of 30 or 60 min.
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Affiliation(s)
- Erwei Gao
- Department of Occupational and Environmental Health, Huazhong University of Science and Technology , Wuhan, PR. China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology , Wuhan, PR. China
| | - Jian Hou
- Department of Occupational and Environmental Health, Huazhong University of Science and Technology , Wuhan, PR. China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology , Wuhan, PR. China
| | - Yun Zhou
- Department of Occupational and Environmental Health, Huazhong University of Science and Technology , Wuhan, PR. China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology , Wuhan, PR. China
| | - Jixuan Ma
- Department of Occupational and Environmental Health, Huazhong University of Science and Technology , Wuhan, PR. China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology , Wuhan, PR. China
| | - Tian Li
- Department of Occupational and Environmental Health, Huazhong University of Science and Technology , Wuhan, PR. China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology , Wuhan, PR. China
| | - Jiafei Zhang
- Department of Occupational and Environmental Health, Huazhong University of Science and Technology , Wuhan, PR. China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology , Wuhan, PR. China
| | - Lu Wang
- Department of Occupational and Environmental Health, Huazhong University of Science and Technology , Wuhan, PR. China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology , Wuhan, PR. China
| | - Weihong Chen
- Department of Occupational and Environmental Health, Huazhong University of Science and Technology , Wuhan, PR. China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology , Wuhan, PR. China
| | - Jing Yuan
- Department of Occupational and Environmental Health, Huazhong University of Science and Technology , Wuhan, PR. China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology , Wuhan, PR. China
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360
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Long-Term Exposure to Fine Particulate Matter and Cardiovascular Disease in China. J Am Coll Cardiol 2020; 75:707-717. [DOI: 10.1016/j.jacc.2019.12.031] [Citation(s) in RCA: 86] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 11/25/2019] [Accepted: 12/10/2019] [Indexed: 11/20/2022]
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361
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Liu Q, Liu FC, Huang KY, Li JX, Yang XL, Wang XY, Chen JC, Liu XQ, Cao J, Shen C, Yu L, Lu FH, Wu XP, Zhao LC, Li Y, Hu DS, Lu XF, Huang JF, Gu DF. Beneficial effects of moderate to vigorous physical activity on cardiovascular disease among Chinese adults. J Geriatr Cardiol 2020; 17:85-95. [PMID: 32165881 PMCID: PMC7051870 DOI: 10.11909/j.issn.1671-5411.2020.02.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 01/25/2020] [Accepted: 02/10/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND In China, lack of evidence remains a significant challenge for the national initiative to promote physical activity (PA). We aimed to quantify the beneficial effects of meeting or maintaining the recommended PA level [150 minutes per week (min/wk) of moderate PA or 75 min/wk of vigorous PA or an equivalent combination] on incident cardiovascular disease (CVD) among Chinese population. METHODS We included 100,560 participants without history of CVD from three cohorts in the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD events and its subtypes, including stroke, coronary heart disease, heart failure, and CVD death. RESULTS During a median follow-up of 7.3 years (range: 6-15 years), 777,163 person-years and 4693 incident CVD events were observed. Compared with participants who were inactive at baseline, the multivariable adjusted HR (95% CI) of developing CVD was 0.74 (0.69-0.79) for those who met recommended moderate to vigorous physical activity (MVPA) level at baseline. Furthermore, the risk of CVD incidence was reduced with increment of MVPA (P trend < 0.001), and the HR (95% CI) of highly-active versus inactive category was 0.62 (0.56-0.68). Compared with individuals who were inactive both at the baseline and follow-up, those keeping active over the period of follow-up had a substantial lower risk of incident CVD with the HR (95% CI) of 0.57 (0.43-0.77). CONCLUSIONS The findings demonstrated that meeting and maintaining the recommended MVPA level could reduce the cardiovascular risk. Wider adoption of the PA recommendations would have considerable health impacts to the Chinese population.
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Affiliation(s)
- Qiong Liu
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fang-Chao Liu
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ke-Yong Huang
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jian-Xin Li
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xue-Li Yang
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xin-Yan Wang
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ji-Chun Chen
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiao-Qing Liu
- Division of Epidemiology, Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou, China
| | - Jie Cao
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- 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
| | - Ling Yu
- Department of Cardiology, Fujian Provincial Hospital, Fuzhou, China
| | - Fang-Hong Lu
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, China
| | - Xian-Ping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Lian-Cheng Zhao
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, 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, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dong-Sheng Hu
- Department of Prevention Medicine, Shenzhen University School of Medicine, Shenzhen, China
| | - Xiang-Feng Lu
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jian-Feng Huang
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dong-Feng Gu
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
- 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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362
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Wang J, Chia Y, Chen C, Park S, Hoshide S, Tomitani N, Kabutoya T, Shin J, Turana Y, Soenarta AA, Tay JC, Buranakitjaroen P, Nailes J, Van Minh H, Siddique S, Sison J, Sogunuru GP, Sukonthasarn A, Teo BW, Verma N, Zhang Y, Wang T, Kario K. What is new in the 2018 Chinese hypertension guideline and the implication for the management of hypertension in Asia? J Clin Hypertens (Greenwich) 2020; 22:363-368. [DOI: 10.1111/jch.13803] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 11/20/2019] [Indexed: 01/17/2023]
Affiliation(s)
- Ji‐Guang Wang
- Department of Hypertension Centre for Epidemiological Studies and Clinical Trials The Shanghai Institute of Hypertension Shanghai Key Laboratory of Hypertension Ruijin Hospital Shanghai Jiaotong University School of Medicine Shanghai China
| | - Yook‐Chin Chia
- Department of Medical Sciences School of Healthcare and Medical Sciences Sunway University Bandar Sunway Ehsan Malaysia
- Department of Primary Care Medicine Faculty of Medicine University of Malaya Kuala Lumpur Malaysia
| | - Chen‐Huan Chen
- Department of Medicine School of Medicine National Yang‐Ming University Taipei Taiwan
| | - Sungha Park
- Division of Cardiology Yonsei Health System Cardiovascular Hospital Seoul Korea
| | - Satoshi Hoshide
- Division of Cardiovascular Medicine Department of Medicine Jichi Medical University School of Medicine Tochigi Japan
| | - Naoko Tomitani
- Division of Cardiovascular Medicine Department of Medicine Jichi Medical University School of Medicine Tochigi Japan
| | - Tomoyuki Kabutoya
- Division of Cardiovascular Medicine Department of Medicine Jichi Medical University School of Medicine Tochigi Japan
| | - Jinho Shin
- Faculty of Cardiology Service Hanyang University Medical Center Seoul Korea
| | - Yuda Turana
- Faculty of Medicine and Health Sciences Atma Jaya Catholic University of Indonesia Jakarta Indonesia
| | - Arieska Ann Soenarta
- Department of Cardiology and Vascular Medicine Faculty of Medicine University of Indonesia‐National Cardiovascular Center Jakarta Indonesia
| | - Jam Chin Tay
- Department of General Medicine Tan Tock Seng Hospital Singapore Singapore
| | - Peera Buranakitjaroen
- Department of Medicine Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand
| | - Jennifer Nailes
- University of the East Ramon Magsaysay Memorial Medical Center Inc. Quezon City Philippines
| | - Huynh Van Minh
- Department of Internal Medicine University of Medicine and Pharmacy Hue University Hue Vietnam
| | | | - Jorge Sison
- Section of CardiologyDepartment of MedicineMedical Center Manila Manila Philippines
| | - Guru Prasad Sogunuru
- MIOT International Hospital Chennai India
- College of Medical Sciences Kathmandu University Bharatpur Nepal
| | - Apichard Sukonthasarn
- Cardiology Division Department of Internal Medicine Faculty of Medicine Chiang Mai University Chiang Mai Thailand
| | - Boon Wee Teo
- Division of Nephrology Department of Medicine Yong Loo Lin School of Medicine Singapore Singapore
| | - Narsingh Verma
- Department of Physiology King George's Medical University Lucknow India
| | - Yu‐Qing Zhang
- Divisions of Hypertension and Heart Failure Chinese Academy of Medical Sciences and Peking Union Medical College Fu Wai Hospital Beijing China
| | - Tzung‐Dau Wang
- Department of Internal Medicine National Taiwan University College of Medicine Taipei City Taiwan
| | - Kazuomi Kario
- Division of Cardiovascular Medicine Department of Medicine Jichi Medical University School of Medicine Tochigi Japan
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363
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Wang H, Wang L, Sun N, Yao Y, Hao L, Xu L, Greenwald SE. Quantitative Comparison of the Performance of Piezoresistive, Piezoelectric, Acceleration, and Optical Pulse Wave Sensors. Front Physiol 2020; 10:1563. [PMID: 32009976 PMCID: PMC6971205 DOI: 10.3389/fphys.2019.01563] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 12/12/2019] [Indexed: 11/16/2022] Open
Abstract
The accurate measurement of the arterial pulse wave is beneficial to clinical health assessment and is important for the effective diagnosis of many types of cardiovascular disease. A variety of sensors have been developed for the non-invasive detection of these waves, but the type of sensor has an impact on the measurement results. Therefore, it is necessary to compare and analyze the signals obtained under a range of conditions using various pulse sensors to aid in making an informed choice of the appropriate type. From the available types we have selected four: a piezoresistive strain gauge sensor (PESG) and a piezoelectric Millar tonometer (the former with the ability to measure contact force), a circular film acceleration sensor, and an optical reflection sensor. Pulse wave signals were recorded from the left radial, carotid, femoral, and digital arteries of 60 subjects using these four sensors. Their performance was evaluated by analyzing their susceptibilities to external factors (contact force, measuring site, and ambient light intensity) and by comparing their stability and reproducibility. Under medium contact force, the peak-to-peak amplitude of the signals was higher than that at high and low force levels and the variability of signal waveform was small. The optical sensor was susceptible to ambient light. Analysis of the intra-class correlation coefficients (ICCs) of the pulse wave parameters showed that the tonometer and accelerometer had good stability (ICC > 0.80), and the PESG and optical sensor had moderate stability (0.46 < ICC < 0.86). Intra-observer analysis showed that the tonometer and accelerometer had good reproducibility (ICC > 0.75) and the PESG and optical sensor had moderate reproducibility (0.42 < ICC < 0.91). Inter-observer analysis demonstrated that the accelerometer had good reproducibility (ICC > 0.85) and the three other sensors had moderate reproducibility (0.52 < ICC < 0.96). We conclude that the type of sensor and measurement site affect pulse wave characteristics and the careful selection of appropriate sensor and measurement site are required according to the research and clinical need. Moreover, the influence of external factors such as contact pressure and ambient light should be fully taken into account.
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Affiliation(s)
- Hongju Wang
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
| | - Lu Wang
- School of Computer Science and Engineering, Northeastern University, Shenyang, China
| | - Nannan Sun
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
| | - Yang Yao
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
| | - Liling Hao
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
| | - Lisheng Xu
- College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, China
- Neusoft Research of Intelligent Healthcare Technology, Co. Ltd., Shenyang, China
| | - Stephen E. Greenwald
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
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364
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Zhang H, Qin L, Sheng CS, Niu Y, Gu H, Lu S, Yang Z, Tian J, Su Q. ASCVD risk stratification modifies the effect of HbA1c on cardiovascular events among patients with type 2 diabetes mellitus with basic to moderate risk. BMJ Open Diabetes Res Care 2020; 8:8/1/e000810. [PMID: 31958299 PMCID: PMC6954758 DOI: 10.1136/bmjdrc-2019-000810] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 11/28/2019] [Accepted: 12/08/2019] [Indexed: 01/19/2023] Open
Abstract
OBJECTIVE To investigate the association between hemoglobin A1c (HbA1c) 7.0%-8.0% and cardiovascular disease (CVD) risk among Chinese patients with type 2 diabetes mellitus (T2DM) with different baseline 10-year atherosclerotic CVD (ASCVD) risk stratification. RESEARCH DESIGN AND METHODS A prospective population-based cohort of 10 060 adults aged 40-70 years in Chongming District of Shanghai was established in 2011. These participants were followed up for 3.25 years and CVD information was recorded. We investigated this association between HbA1c categories and incident CVD stratified by the 10-year ASCVD risk using multiple Cox regression analysis among 1880 patients with T2DM without CVD history. CVD events were defined as cardiovascular death, non-fatal myocardial infarction or non-fatal stroke. RESULTS The corresponding incidence of CVD per 1000 person-years for the HbA1c≤6.5%, 6.6%-6.9%, 7.0%-8.0% and >8.0% groups were 12.5, 21.8, 22.9 and 28.9, respectively. The HbA1c>8.0% group was significantly associated with a higher CVD risk in patients with T2DM. The HbA1c 7.0%-8.0% group was significantly associated with a higher CVD risk in patients with T2DM with moderate baseline ASCVD risk (HR 2.48; 95% CI 1.15 to 5.32). CONCLUSION HbA1c of 7.0%-8.0% may result in a significantly higher CVD risk among patients with T2DM with moderate baseline ASCVD risk, which support the use of HbA1c combined with baseline ASCVD risk assessment to determine future glucose-lowering treatment decisions among patients with T2DM with basic to moderate risk.
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Affiliation(s)
- Hongmei Zhang
- Department of Endocrinology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Li Qin
- Department of Endocrinology, Chongming Branch, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Chang-Sheng Sheng
- Center for Epidemiological Studies and Clinical Trials and Center for Vascular Evaluation, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yixin Niu
- Department of Endocrinology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Hongxia Gu
- Department of Endocrinology, Chongming Branch, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shuai Lu
- Department of Endocrinology, Chongming Branch, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Zhen Yang
- Department of Endocrinology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jingyan Tian
- State Key Laboratory of Medical Genomics, Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrinology and Metabolism, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Qing Su
- Department of Endocrinology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
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365
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Huang K, Liang F, Yang X, Liu F, Li J, Xiao Q, Chen J, Liu X, Cao J, Shen C, Yu L, Lu F, Wu X, Zhao L, Wu X, Li Y, Hu D, Huang J, Liu Y, Lu X, Gu D. Long term exposure to ambient fine particulate matter and incidence of stroke: prospective cohort study from the China-PAR project. BMJ 2019; 367:l6720. [PMID: 31888885 PMCID: PMC7190010 DOI: 10.1136/bmj.l6720] [Citation(s) in RCA: 121] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/27/2019] [Indexed: 01/23/2023]
Abstract
OBJECTIVE To study the effect of long term exposure to ambient fine particulate matter of diameter ≤2.5 μm (PM2.5) on the incidence of total, ischemic, and hemorrhagic stroke among Chinese adults. DESIGN Population based prospective cohort study. SETTING Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project carried out in 15 provinces across China. PARTICIPANTS 117 575 Chinese men and women without stroke at baseline in the China-PAR project. MAIN OUTCOME MEASURES Incidence of total, ischemic, and hemorrhagic stroke. RESULTS The long term average PM2.5 level from 2000 to 2015 at participants' residential addresses was 64.9 μg/m3, ranging from 31.2 μg/m3 to 97.0 μg/m3. During 900 214 person years of follow-up, 3540 cases of incident stroke were identified, of which 63.0% (n=2230) were ischemic and 27.5% (n=973) were hemorrhagic. Compared with the first quarter of exposure to PM2.5 (<54.5 μg/m3), participants in the highest quarter (>78.2 μg/m3) had an increased risk of incident stroke (hazard ratio 1.53, 95% confidence interval 1.34 to 1.74), ischemic stroke (1.82, 1.55 to 2.14), and hemorrhagic stroke (1.50, 1.16 to 1.93). For each increase of 10 μg/m3 in PM2.5 concentration, the increased risks of incident stroke, ischemic stroke, and hemorrhagic stroke were 13% (1.13, 1.09 to 1.17), 20% (1.20, 1.15 to 1.25), and 12% (1.12, 1.05 to 1.20), respectively. Almost linear exposure-response relations between long term exposure to PM2.5 and incident stroke, overall and by its subtypes, were observed. CONCLUSIONS This study provides evidence from China that long term exposure to ambient PM2.5 at relatively high concentrations is positively associated with incident stroke and its major subtypes. These findings are meaningful for both environmental and health policy development related to air pollution and stroke prevention, not only in China, but also in other low and middle income countries.
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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, 167 Beilishi Road, Xicheng District, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
| | - Fengchao Liang
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, Beijing 100037, China
| | - Xueli Yang
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, Beijing 100037, China
| | - Fangchao Liu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, Beijing 100037, China
| | - Jianxin Li
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, Beijing 100037, China
| | - Qingyang Xiao
- School of Environment, Tsinghua University, Beijing, China
| | - Jichun Chen
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, Beijing 100037, China
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou, China
| | - Jie Cao
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, Beijing 100037, 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
| | - Fanghong Lu
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, China
| | - Xianping Wu
- Center for Chronic and Noncommunicable Disease Control and Prevention, Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Liancheng Zhao
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, Beijing 100037, China
| | - Xigui Wu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, 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, 167 Beilishi Road, Xicheng District, Beijing 100037, China
| | - Dongsheng Hu
- Department of Prevention Medicine, Shenzhen University School of Medicine, Shenzhen, China
| | - Jianfeng Huang
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, Beijing 100037, China
| | - Yang Liu
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Xiangfeng Lu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, Beijing 100037, China
| | - Dongfeng Gu
- Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Road, Xicheng District, Beijing 100037, China
- Key Laboratory of Cardiovascular Epidemiology, Chinese Academy of Medical Sciences, Beijing, China
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Xu F, Zhu J, Sun N, Wang L, Xie C, Tang Q, Mao X, Fu X, Brickell A, Hao Y, Sun C. Development and validation of prediction models for hypertension risks in rural Chinese populations. J Glob Health 2019; 9:020601. [PMID: 31788232 PMCID: PMC6875679 DOI: 10.7189/jogh.09.020601] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Background Various hypertension predictive models have been developed worldwide; however, there is no existing predictive model for hypertension among Chinese rural populations. Methods This is a 6-year population-based prospective cohort in rural areas of China. Data was collected in 2007-2008 (baseline survey) and 2013-2014 (follow-up survey) from 8319 participants ranging in age from 35 to 74 years old. Specified gender hypertension predictive models were established based on multivariate Cox regression, Artificial Neural Network (ANN), Naive Bayes Classifier (NBC), and Classification and Regression Tree (CART) in the training set. External validation was conducted in the testing set. The estimated models were assessed by discrimination and calibration, respectively. Results During the follow-up period, 432 men and 604 women developed hypertension in the training set. Assessment for established models in men suggested men office-based model (M1) was better than others. C-index of M1 model in the testing set was 0.771 (95% confidence Interval (CI) = 0.750, 0.791), and calibration χ2 = 6.3057 (P = 0.7090). In women, women office-based model (W1) and ANN were better than the other models assessed. The C-indexes for the W1 model and the ANN model in the testing set were 0.765 (95% CI = 0.746, 0.783) and 0.756 (95% CI = 0.737, 0.775) and the calibrations χ2 were 6.7832 (P = 0.1478) and 4.7447 (P = 0.3145), respectively. Conclusions Not all machine-learning models performed better than the traditional Cox regression models. The W1 and ANN models for women and M1 model for men have better predictive performance which could potentially be recommended for predicting hypertension risk among rural populations.
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Affiliation(s)
- Fei Xu
- Department of Social Medicine and Health Management, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Jicun Zhu
- Department of Social Medicine and Health Management, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Nan Sun
- Department of Management Information Systems, Terry College of Business, University of Georgia, Athens, Georgia, USA
| | - Lu Wang
- Department of Social Medicine and Health Management, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Chen Xie
- Department of Social Medicine and Health Management, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Qixin Tang
- Department of Social Medicine and Health Management, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xiangjie Mao
- Department of Social Medicine and Health Management, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xianzhi Fu
- Department of Social Medicine and Health Management, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Anna Brickell
- College of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Yibin Hao
- People's Hospital of Zhengzhou, Zhengzhou, Henan, PR China
| | - Changqing Sun
- Department of Social Medicine and Health Management, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
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367
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Casey DE, Thomas RJ, Bhalla V, Commodore-Mensah Y, Heidenreich PA, Kolte D, Muntner P, Smith SC, Spertus JA, Windle JR, Wozniak GD, Ziaeian B. 2019 AHA/ACC Clinical Performance and Quality Measures for Adults With High Blood Pressure: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures. J Am Coll Cardiol 2019; 74:2661-2706. [PMID: 31732293 PMCID: PMC7673043 DOI: 10.1016/j.jacc.2019.10.001] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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368
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Casey DE, Thomas RJ, Bhalla V, Commodore-Mensah Y, Heidenreich PA, Kolte D, Muntner P, Smith SC, Spertus JA, Windle JR, Wozniak GD, Ziaeian B. 2019 AHA/ACC Clinical Performance and Quality Measures for Adults With High Blood Pressure: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures. Circ Cardiovasc Qual Outcomes 2019; 12:e000057. [PMID: 31714813 PMCID: PMC7717926 DOI: 10.1161/hcq.0000000000000057] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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369
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Gu X, Li Y, Chen S, Yang X, Liu F, Li Y, Li J, Cao J, Liu X, Chen J, Shen C, Yu L, Huang J, Lam TH, Fang X, He Y, Zhang X, Lu X, Wu S, Gu D. Association of Lipids With Ischemic and Hemorrhagic Stroke: A Prospective Cohort Study Among 267 500 Chinese. Stroke 2019; 50:3376-3384. [PMID: 31658904 DOI: 10.1161/strokeaha.119.026402] [Citation(s) in RCA: 96] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background and Purpose- Previous results on the association between lipids and stroke were controversial. We investigated the association of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C ), high-density lipoprotein cholesterol (HDL-C), and triglyceride with stroke. Methods- Six cohort studies in China with 267 500 participants were included. Cox proportional hazards regression models and restricted cubic spline analyses were used to estimate hazard ratios and 95% CIs and explore linear and nonlinear relationships of lipids and stroke, respectively. Results- The median follow-up duration ranged from 6 to 19 years. During 2 295 881 person-years, 8072 people developed stroke. Multivariable adjusted hazard ratios (95% CIs) per 1 mmol/L increase in TC, LDL-C, triglyceride were 1.08 (1.05-1.11), 1.08 (1.04-1.11), 1.07 (1.05-1.09) for ischemic stroke, respectively. Compared with participants with TC 160-199.9 mg/dL, hazard ratios (95% CIs) were 1.43 (1.11-1.85) for hemorrhagic stroke in those with TC <120 mg/dL. Compared with participants with HDL-C 50 to 59.9 mg/dL, hazard ratios (95% CIs) were 1.23 (1.12-1.35), 1.13 (1.04-1.22) for ischemic stroke, and 1.28 (1.10-1.49), 1.17 (1.03-1.33) for hemorrhagic stroke in those with HDL-C <40 and 40 to 49.9 mg/dL, respectively. Restricted cubic spline analyses showed linear relationships of TC and LDL-C, and nonlinear relationships of HDL-C and triglyceride with ischemic stroke (all P<0.001). Hemorrhagic stroke showed linear relationships with TC and HDL-C (P=0.029 and <0.001 respectively), but no relationship with LDL-C and triglyceride (all P>0.05). Conclusions- TC, LDL-C, and triglyceride showed positive associations with ischemic stroke. The risk of hemorrhagic stroke was higher when TC was lower than 120 mg/dL. LDL-C and triglyceride showed no association with hemorrhagic stroke. The risks of ischemic and hemorrhagic stroke might be higher when HDL-C was lower than 50 mg/dL.
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Affiliation(s)
- Xiaoying Gu
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
| | - Yunzhi Li
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
| | - Shuohua Chen
- Department of Cardiology, Kailuan Hospital, Hebei United University, Tangshan, China (S.C., S.W.)
| | - Xueli Yang
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
| | - Fangchao Liu
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
| | - Ying Li
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
| | - Jianxin Li
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
| | - Jie Cao
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou, China (X. Liu)
| | - Jichun Chen
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
| | - Chong Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, China (C.S.)
| | - Ling Yu
- Department of Cardiology, Fujian Provincial People's Hospital, Fuzhou, China (L.Y.)
| | - Jianfeng Huang
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
| | - Tai-Hing Lam
- School of Public Health, University of Hong Kong, China (T.-H.L.)
| | - Xianghua Fang
- Evidence-based Medical Center, Xuanwu Hospital, Capital Medical University, Beijing, China (X.F.)
| | - Yao He
- Institute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Diseases, Chinese PLA General Hospital, Beijing, China (Y.H.)
| | - Xinhua Zhang
- Beijing Hypertension League Institute, China (X.Z.)
| | - Xiangfeng Lu
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
| | - Shouling Wu
- Department of Cardiology, Kailuan Hospital, Hebei United University, Tangshan, China (S.C., S.W.)
| | - Dongfeng Gu
- From the 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 (X.G., Yunzhi Li, X.Y., F.L., Ying Li, J.L., J. Cao, J. Chen, J.H., X. Lu, D.G.)
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370
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Liu J, Lu X, Chen L, Huo Y. Expert consensus on the management of hypertension in the young and middle-aged Chinese population. Int J Clin Pract 2019; 73:e13426. [PMID: 31573725 DOI: 10.1111/ijcp.13426] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Accepted: 09/21/2019] [Indexed: 11/30/2022] Open
Abstract
Hypertension, defined as blood pressure (BP) ≥140/90 mmHg, is one of the most common, yet reversible, risk factors for cardiovascular disease (CVD). Globally, 9.40 million people died from hypertension in 2010, accounting for 17.8% of total deaths; disability-adjusted life years (DALYs) caused by hypertension were 170 million person-years, or 7.0% of the total global DALYs.1 Data from China showed that hypertension accounted for 24.6% of all deaths, and 12.0% of total DALYs,2 and the direct medical cost of hypertension in China has reached 36.6 billion yuan per year.3.
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Affiliation(s)
- Jing Liu
- Peking University People's Hospital Ringgold standard institution, Department of Cardiology, Beijing, China
| | - Xinzheng Lu
- The First Affiliated Hospital of Nanjing Medical University, Department of Cardiology, Nanjing, China
| | - Luyuan Chen
- Guangdong General Hospital Ringgold standard institution, Deparment of Cardiology, Guangzhou, China
| | - Yong Huo
- Peking University People's Hospital Ringgold standard institution, Department of Cardiology, Beijing, China
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371
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Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, Himmelfarb CD, Khera A, Lloyd-Jones D, McEvoy JW, Michos ED, Miedema MD, Muñoz D, Smith SC, Virani SS, Williams KA, Yeboah J, Ziaeian B. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2019; 74:e177-e232. [PMID: 30894318 PMCID: PMC7685565 DOI: 10.1016/j.jacc.2019.03.010] [Citation(s) in RCA: 1073] [Impact Index Per Article: 178.8] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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372
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Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, Himmelfarb CD, Khera A, Lloyd-Jones D, McEvoy JW, Michos ED, Miedema MD, Muñoz D, Smith SC, Virani SS, Williams KA, Yeboah J, Ziaeian B. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2019; 140:e596-e646. [PMID: 30879355 PMCID: PMC7734661 DOI: 10.1161/cir.0000000000000678] [Citation(s) in RCA: 1697] [Impact Index Per Article: 282.8] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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373
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Xing X, Yang X, Liu F, Li J, Chen J, Liu X, Cao J, Shen C, Yu L, Lu F, Wu X, Zhao L, Li Y, Hu D, Lu X, Gu D. Predicting 10-Year and Lifetime Stroke Risk in Chinese Population. Stroke 2019; 50:2371-2378. [DOI: 10.1161/strokeaha.119.025553] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background and Purpose—
Risk assessment is essential for the primary prevention of stroke. However, the current available tools derived from Chinese populations are insufficient for individualized 10-year and lifetime stroke risk prediction. Our study aims to develop and validate personalized 10-year and lifetime stroke risk equations incorporating 4 large Chinese cohorts.
Methods—
We used 2 prospective cohorts of 21 320 participants with similar survey protocols as the derivation cohort to develop sex-specific 10-year and lifetime stroke risk equations. Two other independent cohorts with 14 123 and 70 838 participants were used for external validation. In addition, the performance of the 10-year stroke risk equations among participants aged ≥55 years was compared with the new Framingham Stroke Risk Profile.
Results—
The sex-specific equations for predicting 10-year stroke risk had C statistics being 0.810 for men and 0.810 for women, with calibration χ
2
being 15.0 (
P
=0.092) and 7.8 (
P
=0.550), respectively. The lifetime stroke risk equations also showed C statistics around 0.800 and calibration χ
2
below 20 for both sexes. In the validation cohorts, we found good agreement between the observed and predicted stroke probabilities for both the 10-year and lifetime stroke risk equations. Further compared with the new Framingham Stroke Risk Profile, our 10-year stroke risk equations displayed better prediction capability. In addition, based on lifetime stroke risk assessment, 5.7% of study participants aged 35 to 49 years old were further reclassified as high risk, who were initially categorized as low 10-year risk.
Conclusions—
We developed a well-performed tool for predicting personalized 10-year and lifetime stroke risk among the Chinese adults, which will facilitate the further identification of high-risk individuals and community-based stroke prevention in China.
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Affiliation(s)
- Xiaolong Xing
- From the Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.X., X.Y., F. Liu, J.L., J. Cao, J. Chen, L.Z., Y.L., X. Lu, D.G.)
| | - Xueli Yang
- From the Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.X., X.Y., F. Liu, J.L., J. Cao, J. Chen, L.Z., Y.L., X. Lu, D.G.)
| | - Fangchao Liu
- From the Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.X., X.Y., F. Liu, J.L., J. Cao, J. Chen, L.Z., Y.L., X. Lu, D.G.)
| | - Jianxin Li
- From the Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.X., X.Y., F. Liu, J.L., J. Cao, J. Chen, L.Z., Y.L., X. Lu, D.G.)
| | - Jichun Chen
- From the Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.X., X.Y., F. Liu, J.L., J. Cao, J. Chen, L.Z., Y.L., X. Lu, D.G.)
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People’s Hospital and Cardiovascular Institute, Guangzhou, China (X.L.)
| | - Jie Cao
- From the Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.X., X.Y., F. Liu, J.L., J. Cao, J. Chen, L.Z., Y.L., X. Lu, D.G.)
| | - Chong Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, China (C.S.)
| | - Ling Yu
- Department of Cardiology, Fujian Provincial People’s Hospital, Fuzhou, China (L.Y.)
| | - Fanghong Lu
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, China (F. Lu)
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China (X.W.)
| | - Liancheng Zhao
- From the Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.X., X.Y., F. Liu, J.L., J. Cao, J. Chen, L.Z., Y.L., X. Lu, D.G.)
| | - Ying Li
- From the Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.X., X.Y., F. Liu, J.L., J. Cao, J. Chen, L.Z., Y.L., X. Lu, D.G.)
| | - Dongsheng Hu
- Department of Prevention Medicine, Shenzhen University School of Medicine, China (D.H.)
| | - Xiangfeng Lu
- From the Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.X., X.Y., F. Liu, J.L., J. Cao, J. Chen, L.Z., Y.L., X. Lu, D.G.)
| | - Dongfeng Gu
- From the Department of Epidemiology, Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.X., X.Y., F. Liu, J.L., J. Cao, J. Chen, L.Z., Y.L., X. Lu, D.G.)
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374
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Identification and validation of four hub genes involved in the plaque deterioration of atherosclerosis. Aging (Albany NY) 2019; 11:6469-6489. [PMID: 31449494 PMCID: PMC6738408 DOI: 10.18632/aging.102200] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 08/12/2019] [Indexed: 01/17/2023]
Abstract
In recent years, intense research has been conducted to explore the diagnostic value of mRNA expression differences in atherosclerosis (AS). Nevertheless, because various technology platforms are applied and sample sizes are small, the results are inconsistent among the studies. We conducted a comprehensive analysis of a total of 161 tissue samples from 4 published studies after evaluating 230 datasets from the Gene Expression Omnibus and ArrayExpress. Adopting the newly published robust rank aggregation approach, combined with Kyoto Encyclopedia of Genes and Genomes pathway analysis, Gene Ontology functional enrichment analysis, and protein-protein interaction network construction, we identified four significantly upregulated genes (CCL4, CCL18, MMP9 and SPP1) for diagnosing AS, even in the advanced stage. Then, we performed gene set enrichment analysis to identify the pathways that were most affected by altered mRNA expression in atherosclerotic plaques. We found that four hub genes cooperatively targeted lipid metabolism and inflammatory immune-related pathways and validated their high expression levels in ruptured plaques by qRT-PCR, western blot analysis and immunohistochemical staining. In summary, our study showed that these genes can be used as interventional targets for plaque progression, and the results suggested we should focus on small changes in these key indicators in the clinical setting.
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375
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Yang L, Guo W, Zeng D, Ma L, Lai X, Fang Q, Guo H, Zhang X. Heart rate variability mediates the association between polycyclic aromatic hydrocarbons exposure and atherosclerotic cardiovascular disease risk in coke oven workers. CHEMOSPHERE 2019; 228:166-173. [PMID: 31029962 DOI: 10.1016/j.chemosphere.2019.04.101] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 04/02/2019] [Accepted: 04/13/2019] [Indexed: 06/09/2023]
Abstract
Polycyclic aromatic hydrocarbons (PAHs) metabolites was related to heart rate variability (HRV) reduction and atherosclerotic cardiovascular disease (ASCVD), and ASCVD was also affected by HRV. However, the mediating role of HRV in the association between PAHs exposure and ASCVD risk was largely unknown. We aimed to investigate whether the relation of PAHs exposure with ASCVD risk was mediated by HRV among coke oven workers. A total of 1100 subjects with complete data were qualified in the current study. We measured 12 urinary PAHs metabolites by gas chromatography-mass spectrometry (GC-MS) and HRV indices by 3-channel digital Holter monitors. The associations between urinary PAHs metabolites, HRV indices, and ASCVD risk were explored using generalized linear models or multivariate logistic regression models. A mediation analysis was conducted to examine the role of HRV on the association between PAHs exposure and ASCVD risk. We found that urinary 1-hydroxynaphthalene (1-OHNa), 2-OHNa, and total PAH metabolites (ΣOH-PAH) were dose-responsive associated with increased risk of ASCVD. Compared with lowest quartile, the adjusted odds ratio (OR) for ASCVD risk in the highest quartile were 2.36 for 1-OHNa, 6.58 for 2-OHNa, and 1.60 for ΣOH-PAH (all Ptrend<0.05). In addition, significant dose-dependent relationships were found across 2-OHNa quartiles with decreasing HRV indices, which in turn, were positively associated with elevated risk of ASCVD (all Ptrend<0.05). Mediation analyses indicated that HRV mediate 2.7%-4.3% of the association between 2-OHNa exposure and higher ASCVD risk. Our data suggested that occupational exposure to PAHs may increase ASCVD risk, which was partially mediated by HRV.
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Affiliation(s)
- Liangle Yang
- Department of Occupational and Environmental Health and Ministry of Education Key Lab for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenting Guo
- Department of Occupational and Environmental Health and Ministry of Education Key Lab for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Dan Zeng
- Institute of Industrial Health, Wuhan Iron & Steel (Group) Corporation, Wuhan, 430070, China
| | - Lin Ma
- Department of Occupational and Environmental Health and Ministry of Education Key Lab for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuefeng Lai
- Department of Occupational and Environmental Health and Ministry of Education Key Lab for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qin Fang
- Department of Occupational and Environmental Health and Ministry of Education Key Lab for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Huan Guo
- Department of Occupational and Environmental Health and Ministry of Education Key Lab for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health and Ministry of Education Key Lab for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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376
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Wang Z, Hao G, Wang X, Chen Z, Zhang L, Zhang Z, Hu H, Weintraub WS, Gao R, for the China hypertension survey investigators. Clinical outcomes and economic impact of the 2017 ACC/AHA guidelines on hypertension in China. J Clin Hypertens (Greenwich) 2019; 21:1212-1220. [PMID: 31267666 PMCID: PMC8030413 DOI: 10.1111/jch.13609] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2019] [Revised: 05/08/2019] [Accepted: 05/25/2019] [Indexed: 11/28/2022]
Abstract
The 2017 guidelines on the diagnosis and treatment of high blood pressure in adults were published by the American College of Cardiology and the American Heart Association. The impact on clinical outcomes and costs needs to be estimated prior to adopting these guidelines in China. Data from a nationally representative sample in China were analyzed. The prevalence and treatment were calculated based on the criteria of the 2017 guidelines and 2018 Chinese guidelines among participants aged ≥35 years old. Direct medical costs, as well as the averted disability adjusted of life years and cost saving from cardiovascular disease events prevented by controlling hypertension, were also estimated. The prevalence and treatment rate of hypertension were 32.0% and 43.4% according to the 2018 Chinese guidelines. Based on the 2017 guidelines, another 24.5% of the adult population (estimated 168.1 million) would be classified as having hypertension; of whom, about 32.1 million would need to be pharmaceutically treated to reach the current treatment rate of 43.4%. As a result, an estimated additional 42.7 billion US dollars of the direct medical cost would be required for lifetime therapy. By preventing cardiovascular events, the new guidelines would reduce lifetime costs by 3.77 billion US dollars, while preventing 1.41 million disability adjusted of life years lost. Application of the 2017 guidelines in China will substantially increase the prevalence of hypertension and produce a large increase in therapy costs, although it would prevent cardiovascular disease events and save disability adjusted of life years.
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Affiliation(s)
- Zengwu Wang
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai HospitalPeking Union Medical College & Chinese Academy of Medical SciencesBeijingChina
| | - Guang Hao
- Department of Epidemiology, School of MedicineJinan UniversityGuangzhouChina
| | - Xin Wang
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai HospitalPeking Union Medical College & Chinese Academy of Medical SciencesBeijingChina
| | - Zuo Chen
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai HospitalPeking Union Medical College & Chinese Academy of Medical SciencesBeijingChina
| | - Linfeng Zhang
- Division of Prevention and Community Health, National Center for Cardiovascular Disease, National Clinical Research Center of Cardiovascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai HospitalPeking Union Medical College & Chinese Academy of Medical SciencesBeijingChina
| | - Zugui Zhang
- Christiana Care Health SystemNewarkDelawareUSA
| | - Hao Hu
- China Health Technology Assessment Center, National Health Development Research CenterNational Health and Family Planning CommissionBeijingChina
| | | | - Runlin Gao
- Department of Cardiology, Fuwai HospitalPeking Union Medical College & Chinese Academy of Medical SciencesBeijingChina
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377
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Yang S, Xia YP, Luo XY, Chen SL, Li BW, Ye ZM, Chen SC, Mao L, Jin HJ, Li YN, Hu B. Exosomal CagA derived from Helicobacter pylori-infected gastric epithelial cells induces macrophage foam cell formation and promotes atherosclerosis. J Mol Cell Cardiol 2019; 135:40-51. [PMID: 31352044 DOI: 10.1016/j.yjmcc.2019.07.011] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Revised: 07/16/2019] [Accepted: 07/24/2019] [Indexed: 12/11/2022]
Abstract
BACKGROUND Seroepidemiological studies have highlighted a positive relation between CagA-positive Helicobacter pylori (H. pylori), atherosclerosis and related clinic events. However, this link has not been well validated. The present study was designed to explore the role of H. pylori PMSS1 (a CagA-positive strain that can translocate CagA into host cells) and exosomal CagA in the progression of atherosclerosis. METHODS To evaluate whether H. pylori accelerates or even induces atherosclerosis, H. pylori-infected C57/BL6 mice and ApoE-/- mice were maintained under different dietary conditions. To identify the role of H. pylori-infected gastric epithelial cells-derived exosomes (Hp-GES-EVs) and exosomal CagA in atherosclerosis, ApoE-/- mice were given intravenous or intraperitoneal injections of saline, GES-EVs, Hp-GES-EVs, and recombinant CagA protein (rCagA). FINDINGS CagA-positive H. pylori PMSS1 infection does not induce but promotes macrophage-derived foam cell formation and augments atherosclerotic plaque growth and instability in two animal models. Meanwhile, circulating Hp-GES-EVs are taken up in aortic plaque, and CagA is secreted in Hp-GES-EVs. Furthermore, the CagA-containing EVs and rCagA exacerbates macrophage-derived foam cell formation and lesion development in vitro and in vivo, recapitulating the pro-atherogenic effects of CagA-positive H. pylori. Mechanistically, CagA suppresses the transcription of cholesterol efflux transporters by downregulating the expression of transcriptional factors PPARγ and LXRα and thus enhances foam cell formation. INTERPRETATION These results may provide new insights into the role of exosomal CagA in the pathogenesis of CagA-positive H. pylori infection-related atherosclerosis. It is suggested that preventing and eradicating CagA-positive H. pylori infection could reduce the incidence of atherosclerosis and related events.
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Affiliation(s)
- Shuai Yang
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuan-Peng Xia
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xue-Ying Luo
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shao-Li Chen
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bo-Wei Li
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zi-Ming Ye
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Department of Neurology, The First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, China
| | - Sheng-Cai Chen
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ling Mao
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hui-Juan Jin
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ya-Nan Li
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bo Hu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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378
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Jiang Y, Ni W. Economic Evaluation of the 2016 Chinese Guideline and Alternative Risk Thresholds of Initiating Statin Therapy for the Management of Atherosclerotic Cardiovascular Disease. PHARMACOECONOMICS 2019; 37:943-952. [PMID: 30875022 DOI: 10.1007/s40273-019-00791-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
OBJECTIVE The 2016 Chinese guidelines for the management of dyslipidemia recommended mixed rules that centered around a 10% 10-year risk threshold to initiate statins for the primary prevention of atherosclerotic cardiovascular disease (ASCVD). The present study aimed to evaluate the cost-effectiveness of the guideline statin-initiation strategy and alternative strategies. METHODS A decision analytic model using discrete event simulation with event probabilities based on a validated ASCVD risk prediction tool for Chinese was constructed. Risk factor inputs were from the dataset of a nationally representative survey of middle-aged and elderly Chinese. Data of statin treatment effectiveness were from a published meta-analysis. Other key input data were identified from the literature or relevant databases. The strategies we evaluated were the guideline strategy, a 15% 10-year risk threshold strategy and a 20% 10-year risk threshold strategy. After excluding any extended dominance strategies, the incremental costs per quality-adjusted life year (QALY) gained of each strategy was calculated. RESULTS The 20% 10-year risk threshold strategy was an extended dominance option. The incremental costs per QALY gained from the 15% 10-year risk threshold strategy compared with no treatment and the guideline strategy compared with the 15% 10-year risk threshold strategy were CN¥69,309 and CN¥154,944, respectively. The results were robust in most sensitivity analyses. CONCLUSIONS The guideline strategy and the 15% 10-year risk threshold strategy are optimal when using the three times and the two times the gross domestic product per capita willingness-to-pay standards, respectively.
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Affiliation(s)
- Yawen Jiang
- Department of Pharmaceutical and Health Economics, University of Southern California, USC Schaeffer Center, 635 Downey Way, Verna and Peter Dauterive Hall (VPD), Suite 210, Los Angeles, CA, 90089-3333, USA.
| | - Weiyi Ni
- Department of Pharmaceutical and Health Economics, University of Southern California, USC Schaeffer Center, 635 Downey Way, Verna and Peter Dauterive Hall (VPD), Suite 210, Los Angeles, CA, 90089-3333, USA
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379
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Su X, Luo M, Tang X, Luo Y, Zheng X, Peng D. Goals of non-high density lipoprotein cholesterol need to be adjusted in Chinese acute coronary syndrome patients: Findings from the CCC-ACS project. Clin Chim Acta 2019; 496:48-54. [PMID: 31255567 DOI: 10.1016/j.cca.2019.06.022] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 06/19/2019] [Accepted: 06/26/2019] [Indexed: 01/17/2023]
Abstract
BACKGROUND Guidelines recommended non-high density lipoprotein cholesterol (non-HDL-C) as a co-primary target, and set non-HDL-C goals as 30 mg/dl higher than low-density lipoprotein cholesterol (LDL-C) goals. However, the value is largely uncertain in Chinese patients. METHODS We assigned non-HDL-C values at the same percentiles correspondent to LDL-C goals for patients from the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome (CCC-ACS) Project. We calculated the differences between non-HDL-C and LDL-C and proposed appropriate adding values according to LDL-C and TG concentrations. RESULTS Among 73,495 patients, 17.7% used lipid-lowering agents before admission. Of these, 27.2% achieved LDL-C <70 mg/dl while 39.4% achieved non-HDL-C <100 mg/dl. The mean difference between non-HDL-C and LDL-C was 23.2 mg/dl, which could be affected by LDL-C and TG concentrations. Importantly, of patients with LDL-C concentrations ≤100 mg/dl, the mean differences were 19.1 mg/dl in patients with TG ≤150 mg/dl and 24.6 mg/dl in patients with TG >150 mg/dl. CONCLUSIONS There are significant differences between LDL-C and non-HDL-C in Chinese ACS patients. For secondary prevention, on average, the adding values should be 20 mg/dl for patients with TG ≤150 mg/dl and 25 mg/dl for patients with TG >150 mg/dl when LDL-C goals of 70 mg/dl is achieved.
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Affiliation(s)
- Xin Su
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Mengdie Luo
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Xiaoyu Tang
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Yonghong Luo
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Xiaoyan Zheng
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Daoquan Peng
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
| | -
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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380
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Xu Y, Ma X, Xiong Q, Zhang X, Shen Y, Bao Y. Osteocalcin value to identify subclinical atherosclerosis over atherosclerotic cardiovascular disease (ASCVD) risk score in middle-aged and elderly Chinese asymptomatic men. Clin Chem Lab Med 2019; 56:1962-1969. [PMID: 29777608 DOI: 10.1515/cclm-2018-0320] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 04/18/2018] [Indexed: 01/02/2023]
Abstract
BACKGROUND Our study examined whether osteocalcin contributed to identifying carotid intima-media thickness (C-IMT) over the atherosclerotic cardiovascular disease (ASCVD) risk score. METHODS We recruited 618 middle-aged and elderly men from communities in Shanghai. Serum osteocalcin levels were determined using an electrochemiluminescence immunoassay. C-IMT was measured by ultrasonography. RESULTS The study included 245 men with low ASCVD risk and 373 men with moderate-to-high ASCVD risk. Serum osteocalcin levels were lower in the moderate-to-high risk vs. low risk men (p=0.042). Multivariate stepwise regression analysis showed that body mass index (BMI) and glycated hemoglobin were predictors for reduced osteocalcin levels (both p<0.001). Among all subjects, the proportion with an elevated C-IMT was higher in the low-osteocalcin group than in the high-osteocalcin group (p=0.042), and the significance of this result was greater when considering only subjects with a moderate-to-high ASCVD risk (p=0.011). The recognition rate of elevated C-IMT was superior with both low osteocalcin and moderate-to-high ASCVD risk vs. either parameter alone (p<0.001 and p=0.015, respectively). Osteocalcin was independently and inversely associated with elevated C-IMT after adjusting for the 10-year ASCVD risk score (p=0.004). The negative relationship remained statistically significant in subjects with a moderate-to-high ASCVD risk in particular (standardized β=-0.104, p=0.044). CONCLUSIONS In middle-aged and elderly men, serum osteocalcin levels strengthen identifying subclinical atherosclerosis over ASCVD risk score, especially among subjects with a moderate-to-high ASCVD risk.
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Affiliation(s)
- Yiting Xu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, P.R. China
| | - Xiaojing Ma
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, P.R. China
| | - Qin Xiong
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, P.R. China
| | - Xueli Zhang
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, P.R. China
| | - Yun Shen
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, P.R. China
| | - Yuqian Bao
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, P.R. China
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381
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Fan J, Gao ST, Wang LJ, Qian ZL, Zhou ZQ, Liu XZ. Association of Three Simple Insulin Resistance Indexes with Prehypertension in Normoglycemic Subjects. Metab Syndr Relat Disord 2019; 17:374-379. [PMID: 31211636 DOI: 10.1089/met.2019.0029] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Background: Insulin resistance (IR) is the common pathophysiology of prehypertension and prediabetes. Recognition of IR in one of the two disease states is critical for carrying out preventive strategies of another disease state. This study aimed to explore which simple IR indexes were significantly associated with prehypertension in subjects with normoglycemia. Methods: A total of 108,370 adults without elevated fasting plasma glucose and hypertension were included in this study. The three simple IR indexes [triglycerides to high-density lipoprotein cholesterol ratio, the product of fasting triglycerides and glucose, and metabolic score for IR (METS-IR)] were calculated. Partial correlation was used to analyze the correlation between the three indicators and blood pressure (BP) levels, and logistic regression analysis was used to explore their association with prehypertension. Results: Among the three indicators, only METS-IR had positive correlations with systolic and diastolic blood pressure levels. Furthermore, METS-IR was also significantly associated with prehypertension, irrespective of the categorization of waist circumference (WC). The odds ratios of the highest quartile were 2.223 (95% confidence interval [CI]: 2.044-2.417) in all subjects, 2.022 (95% CI: 1.501-2.725) in elevated WC subgroup, and 1.815 (95% CI: 1.620-2.034) in normal WC subgroup. Conclusions: METS-IR was associated with prehypertension in normoglycemic Chinese subjects, which bypasses the impact of WC and might be valuable for the management of prehypertension and the prevention of prediabetes in different ethnic groups.
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Affiliation(s)
- Jie Fan
- General Management Office, Zhejiang Police College, Hangzhou, Zhejiang, China
| | - Song Ting Gao
- Guali Town Community Health Service Center, Xiaoshan District, Hangzhou, Zhejiang, China
| | - Li Jun Wang
- Directly Affiliated Convalescence Area, Hangzhou Aeronautical Sanatorium of Chinese Air Force, Hangzhou, Zhejiang, China
| | - Zhong Li Qian
- Directly Affiliated Convalescence Area, Hangzhou Aeronautical Sanatorium of Chinese Air Force, Hangzhou, Zhejiang, China
| | - Ze Quan Zhou
- Directly Affiliated Convalescence Area, Hangzhou Aeronautical Sanatorium of Chinese Air Force, Hangzhou, Zhejiang, China
| | - Xing Zhen Liu
- Directly Affiliated Convalescence Area, Hangzhou Aeronautical Sanatorium of Chinese Air Force, Hangzhou, Zhejiang, China
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382
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Damen JA, Pajouheshnia R, Heus P, Moons KGM, Reitsma JB, Scholten RJPM, Hooft L, Debray TPA. Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis. BMC Med 2019; 17:109. [PMID: 31189462 PMCID: PMC6563379 DOI: 10.1186/s12916-019-1340-7] [Citation(s) in RCA: 148] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 05/07/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND The Framingham risk models and pooled cohort equations (PCE) are widely used and advocated in guidelines for predicting 10-year risk of developing coronary heart disease (CHD) and cardiovascular disease (CVD) in the general population. Over the past few decades, these models have been extensively validated within different populations, which provided mounting evidence that local tailoring is often necessary to obtain accurate predictions. The objective is to systematically review and summarize the predictive performance of three widely advocated cardiovascular risk prediction models (Framingham Wilson 1998, Framingham ATP III 2002 and PCE 2013) in men and women separately, to assess the generalizability of performance across different subgroups and geographical regions, and to determine sources of heterogeneity in the findings across studies. METHODS A search was performed in October 2017 to identify studies investigating the predictive performance of the aforementioned models. Studies were included if they externally validated one or more of the original models in the general population for the same outcome as the original model. We assessed risk of bias for each validation and extracted data on population characteristics and model performance. Performance estimates (observed versus expected (OE) ratio and c-statistic) were summarized using a random effects models and sources of heterogeneity were explored with meta-regression. RESULTS The search identified 1585 studies, of which 38 were included, describing a total of 112 external validations. Results indicate that, on average, all models overestimate the 10-year risk of CHD and CVD (pooled OE ratio ranged from 0.58 (95% CI 0.43-0.73; Wilson men) to 0.79 (95% CI 0.60-0.97; ATP III women)). Overestimation was most pronounced for high-risk individuals and European populations. Further, discriminative performance was better in women for all models. There was considerable heterogeneity in the c-statistic between studies, likely due to differences in population characteristics. CONCLUSIONS The Framingham Wilson, ATP III and PCE discriminate comparably well but all overestimate the risk of developing CVD, especially in higher risk populations. Because the extent of miscalibration substantially varied across settings, we highly recommend that researchers further explore reasons for overprediction and that the models be updated for specific populations.
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Affiliation(s)
- Johanna A Damen
- Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands. .,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O. Box 85500, Str. 6.131, 3508, GA, Utrecht, The Netherlands.
| | - Romin Pajouheshnia
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O. Box 85500, Str. 6.131, 3508, GA, Utrecht, The Netherlands
| | - Pauline Heus
- Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O. Box 85500, Str. 6.131, 3508, GA, Utrecht, The Netherlands
| | - Karel G M Moons
- Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O. Box 85500, Str. 6.131, 3508, GA, Utrecht, The Netherlands
| | - Johannes B Reitsma
- Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O. Box 85500, Str. 6.131, 3508, GA, Utrecht, The Netherlands
| | - Rob J P M Scholten
- Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O. Box 85500, Str. 6.131, 3508, GA, Utrecht, The Netherlands
| | - Lotty Hooft
- Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O. Box 85500, Str. 6.131, 3508, GA, Utrecht, The Netherlands
| | - Thomas P A Debray
- Cochrane Netherlands, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O. Box 85500, Str. 6.131, 3508, GA, Utrecht, The Netherlands
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383
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Huang K, Yang X, Liang F, Liu F, Li J, Xiao Q, Chen J, Liu X, Cao J, Shen C, Yu L, Lu F, Wu X, Zhao L, Wu X, Li Y, Hu D, Huang J, Liu Y, Lu X, Gu D. Long-Term Exposure to Fine Particulate Matter and Hypertension Incidence in China. Hypertension 2019; 73:1195-1201. [PMID: 31067193 PMCID: PMC6656583 DOI: 10.1161/hypertensionaha.119.12666] [Citation(s) in RCA: 91] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The risk of incident hypertension associated with long-term exposure to fine particulate matter (PM2.5) was still unclear by studies conducted in North America and Europe, and this relationship has rarely been quantified at higher ambient concentrations typically found in developing countries. We aimed to investigate the association between PM2.5 and incident hypertension using the large-scale prospective cohorts in China. We included 59 456 participants without hypertension aged ≥18 years from the China-PAR (Prediction for Atherosclerotic Cardiovascular Disease Risk in China) project. Data on ambient PM2.5 at participants' residential address were obtained during 2004 to 2015 using a satellite-based spatial-temporal model. Hazard ratios and 95% CIs were calculated for incident hypertension using stratified Cox proportional hazards models with adjustment of potential confounders. The findings indicated that average PM2.5 concentration from 2004 to 2015 at study participants' address was 77.7 μg/m3. During the follow-up of 364 947 person-years, we identified 13 981 incident hypertension cases. Compared with the lowest quartile exposure of PM2.5, participants in the highest quartile had an increased risk of incident hypertension with a hazard ratio (95% CI) of 1.77 (1.56-2.00). Each 10 μg/m3 increment of PM2.5 concentration could increase 11% risk of hypertension (hazard ratio, 1.11; 95% CI, 1.05-1.17). This cohort study provided the first evidence from China that long-term exposure to PM2.5 was independently associated with incident hypertension at relatively high ambient concentrations. Stringent strategies on PM2.5 pollution control are warranted to improve the air quality and contribute to the reduction of disease burden of hypertension in China.
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Affiliation(s)
- Keyong Huang
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Xueli Yang
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Fengchao Liang
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Fangchao Liu
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Jianxin Li
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Qingyang Xiao
- Department of Environmental Health, Rollins School of
Public Health, Emory University, Atlanta, Georgia 30322, USA
| | - Jichun Chen
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial
People’s Hospital and Cardiovascular Institute, Guangzhou 510080,
China
| | - Jie Cao
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Chong Shen
- Department of Epidemiology and Biostatistics, School of
Public Health, Nanjing Medical University, Nanjing 211166, 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, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Xigui Wu
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Ying Li
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Dongsheng Hu
- Department of Prevention Medicine, Shenzhen University
School of Medicine, Shenzhen 518060, China
| | - Jianfeng Huang
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Yang Liu
- Department of Environmental Health, Rollins School of
Public Health, Emory University, Atlanta, Georgia 30322, USA
| | - Xiangfeng Lu
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
| | - Dongfeng Gu
- Department of Epidemiology, Key Laboratory of
Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular
Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100037, China
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Liang F, Yang X, Liu F, Li J, Xiao Q, Chen J, Liu X, Cao J, Shen C, Yu L, Lu F, Wu X, Zhao L, Wu X, Li Y, Hu D, Huang J, Liu Y, Lu X, Gu D. Long-term exposure to ambient fine particulate matter and incidence of diabetes in China: A cohort study. ENVIRONMENT INTERNATIONAL 2019; 126:568-575. [PMID: 30852444 DOI: 10.1016/j.envint.2019.02.069] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 02/25/2019] [Accepted: 02/26/2019] [Indexed: 05/09/2023]
Abstract
BACKGROUND Diabetes caused substantial economic and health burden worldwide. However, the associations between air pollution and diabetes incidence were rarely reported in the developing countries, especially in China with relatively high PM2.5 concentrations. OBJECTIVES A cohort-based study was conducted to assess the diabetes incidence associated with long-term exposure to ambient PM2.5. METHODS We collected individual health data and risk factors from the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR Project) from 15 provinces over China. Diabetes was defined as fasting glucose levels ≥7.0 mmol/L at the follow-ups and/or the use of insulin or oral hypoglycemic agents and/or diagnosed medical history of diabetes during 2004 to 2015. Individual-level PM2.5 exposures were estimated from satellite-based PM2.5 concentrations (10 km spatial resolution) during the study period. Cox proportional hazards models with random intercepts of each cohort and region were employed to estimate the diabetes incidence attributable to PM2.5, after the adjustment for age, gender, body mass index, smoking status, education, work-related physical activity level, hypertension, urbanicity, county-level averaged years of education, and long-term levels of temperature and relative humidity. RESULTS A total of 88,397 subjects were analyzed with 580,928 person-years of follow-up after 2004, among which 6439 new cases of diabetes were observed. The mean age of the subjects was 51.7 years at baseline. For an increase of 10 μg/m3 in long-term PM2.5 exposure, the multivariable-adjusted percent increase in the diabetes incidence was estimated to be 15.66% (95% confidence interval: 6.42%, 25.70%). The adverse effects of PM2.5 were larger among females, rural subjects, non-smokers, normotensives, subjects younger than 65 years and subjects with body mass index <25 kg/m2. CONCLUSIONS Our findings provided evidence for the association of long-term exposure to PM2.5 with diabetes incidence in China. A sustained improvement of air quality will benefit the reduction for diabetes epidemic in China.
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Affiliation(s)
- Fengchao Liang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Xueli Yang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Fangchao Liu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Jianxin Li
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Qingyang Xiao
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Jichun Chen
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou 510080, China
| | - Jie Cao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Chong Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, 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
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Xigui Wu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Ying Li
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Dongsheng Hu
- Department of Prevention Medicine, Shenzhen University School of Medicine, Shenzhen 518060, China
| | - Jianfeng Huang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Yang Liu
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA.
| | - Xiangfeng Lu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
| | - Dongfeng Gu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
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385
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Tang X, Zhang D, He L, Wu N, Si Y, Cao Y, Huang S, Li N, Li J, Dou H, Gao P, Hu Y. Performance of atherosclerotic cardiovascular risk prediction models in a rural Northern Chinese population: Results from the Fangshan Cohort Study. Am Heart J 2019; 211:34-44. [PMID: 30831332 DOI: 10.1016/j.ahj.2019.01.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 01/26/2019] [Indexed: 12/16/2022]
Abstract
BACKGROUND Performance of Pooled Cohort Equations (PCEs) for atherosclerotic cardiovascular disease (ASCVD) risks varied across populations. Whether the recently developed Prediction for ASCVD Risk in China (China-PAR) model could accurately predict cardiovascular risks in real practice remains unclear. METHODS A population-based cohort study in rural Beijing in the "stroke belt" in North China was used to externally validate PCE and China-PAR models for 5-year ASCVD risk prediction. Expected 5-year prediction risk using China-PAR model was compared with PCE (white). The models were assessed for calibration, discrimination, and reclassification. RESULTS Among 11,169 adults aged 40 to 79 years over a median 6.44 years of follow-up, 1,921 participants developed a first ASCVD event during total 70,951 person-years. China-PAR model fairly predicted ASCVD risk in men but overestimated by 29.4% risk in women (calibration χ2 = 81.4, P < .001). Underestimations were shown by PCE as 76.2% in men and 88.2% in women with poor calibration (both P < .001). However, discrimination was similar in both models: C-statistics in men were 0.685 (95% CI 0.660-0.710) for China-PAR and 0.675 (95% CI 0.649-0.701) for PCE; C-statistics in women were 0.711 (95% CI 0.694-0.728) for China-PAR and 0.714 (95% CI 0.697-0.731) for PCE. Moreover, China-PAR did not substantially improve accuracy of reclassification compared with PCE. CONCLUSIONS China-PAR outperformed PCE in 5-year ASCVD risk prediction in this rural Northern Chinese population at average population risk level, fairly predicted risk in men, but overestimated risk in women; however, China-PAR did not meaningfully improve the accuracy of discrimination and reclassification at individual risk level.
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386
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Sun GZ, Ye N, Wu SJ, Zhou Y, Sun YX. 10-year ASCVD risk is positively correlated with depressive symptoms in a large general population. BMC Psychiatry 2019; 19:125. [PMID: 31027490 PMCID: PMC6486683 DOI: 10.1186/s12888-019-2114-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 04/11/2019] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND To explore the potential correlation between 10-year atherosclerotic cardiovascular disease (ASCVD) risk and depressive symptoms in a general population. METHODS A cross-sectional study involving 11,956 permanent residents of Liaoning Province in China ≥35 years of age was conducted. Depressive symptoms were assessed with the Patient Health Questionnaire-9 (PHQ-9) while 10-year ASCVD risk was calculated using the tool suitable for China. RESULTS Males had significantly higher 10-year ASCVD risk than females (14.2 ± 10.7% vs. 9.3 ± 9.1%; P < 0.001) but lower PHQ-9 score (2.34 ± 3.13 vs. 3.63 ± 4.02; P < 0.001). The mean PHQ-9 score increased significantly with advancing 10-year ASCVD risk category in both males (from 2.03 to 2.61; P for trend < 0.001) and females (from 3.04 to 4.61; P for trend < 0.001), and the increasing trend was more apparent in females (P < 0.001). Pearson correlation analyses showed that 10-year ASCVD risk positively correlated with PHQ-9 score in both sexes (Ps < 0.001). In multivariate linear regression analyses adjusting for confounding risk factors, the independent associations of 10-year ASCVD risk with PHQ-9 score were all significant in the total (β = 2.61; P < 0.001), male (β = 1.64; P = 0.001), and female subjects (β = 3.71; P < 0.001). Further, the interaction analysis proved the impacts of 10-year ASCVD risk on PHQ-9 score were more apparent in females than males (Ps < 0.001). CONCLUSIONS The 10-year ASCVD risk was positively associated with depressive symptoms in both males and females, which was more apparent in the latter. These findings provided some novel data about the value of 10-year ASCVD risk in estimating depressive symptoms.
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Affiliation(s)
- Guo-Zhe Sun
- grid.412636.4Department of Cardiovascular Medicine, The First Hospital of China Medical University, 155 Nanjing Street, Heping, Shenyang, 110001 Liaoning China
| | - Ning Ye
- grid.412636.4Department of Cardiovascular Medicine, The First Hospital of China Medical University, 155 Nanjing Street, Heping, Shenyang, 110001 Liaoning China
| | - Shao-Jun Wu
- grid.412636.4Department of Cardiovascular Medicine, The First Hospital of China Medical University, 155 Nanjing Street, Heping, Shenyang, 110001 Liaoning China
| | - Ying Zhou
- grid.412636.4Department of Cardiovascular Medicine, The First Hospital of China Medical University, 155 Nanjing Street, Heping, Shenyang, 110001 Liaoning China
| | - Ying-Xian Sun
- Department of Cardiovascular Medicine, The First Hospital of China Medical University, 155 Nanjing Street, Heping, Shenyang, 110001, Liaoning, China.
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387
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Molecular basis of neurophysiological and antioxidant roles of Szechuan pepper. Biomed Pharmacother 2019; 112:108696. [DOI: 10.1016/j.biopha.2019.108696] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Revised: 02/14/2019] [Accepted: 02/14/2019] [Indexed: 01/18/2023] Open
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388
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Xin Y, Zhao Y, Chen X, Li J, Liu Z, Cao X, Sun Y, Hu W. Derivation and Evaluation of the Ischemic Risk Model in High-Risk Chinese Patients Undergoing Percutaneous Coronary Intervention for Acute Coronary Syndrome. Clin Ther 2019; 41:754-765. [PMID: 30935669 DOI: 10.1016/j.clinthera.2019.03.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 02/04/2019] [Accepted: 03/05/2019] [Indexed: 02/05/2023]
Abstract
PURPOSE Coronary artery disease is the top cause of death among the Chinese population. With the establishment of a Chinese prediction model, it is urgent to assess factors related to the prognosis of patients with acute coronary syndrome at extremely high risk. METHODS In this retrospective study, we enrolled 601 patients assessed as being of extremely high risk, according to specific criteria from the China-PAR (Prediction for Atherosclerotic Cardiovascular Disease Risk) project, and investigated various clinical parameters using Cox multivariate analysis to establish a risk nomogram. C-index and calibration curves were involved to assess the internal identification. By using the all-cause death risk model, we stratified patients by risk level and compared the effects of clopidogrel and ticagrelor on end points. FINDINGS We identified several factors, including body mass index, angiopathy, smoking status, β-blocker usage, history of myocardial infarction, total number of stents, and usage of antiplatelet agents, related to ischemic end points, all-cause death, cardiovascular events, and cardiac death. A C-index of >0.7 and the calibration curve demonstrated good concordance. In a subsequent analysis, we used the all-cause death model to stratify patients by risk level, and compared the effects of clopidogrel and ticagrelor. In the subgroup with a 2-year death rate of >50%, ticagrelor showed a positive effect (P = 0.045), but in the subgroup with a 2-year death rate of <50%, the difference between clopidogrel and ticagrelor was not significant. Considering the duration of effect of antiplatelet agents, we also compared these 2 agents at 1-year follow up, with ticagrelor showing no advantage. IMPLICATIONS We determined the probability of ischemic risk in patients at extremely high ischemic risk and developed new risk models for this specific group. Ticagrelor, compared with clopidogrel, may improve the prognosis of patients at high risk for death after 2 years.
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Affiliation(s)
- Yanguo Xin
- Department of Cardiology, West China Hospital, Sichuan University, Chengdu, China; Department of Cardiology, The First Affiliated Hospital, China Medical University, Shenyang, China
| | - Yinan Zhao
- Department of Neurology, The First Affiliated Hospital, China Medical University, Shenyang, China
| | - Xin Chen
- Department of Cardiology, Fuling Central Hospital, Chongqing, China
| | - Junli Li
- Department of Cardiology, West China Hospital, Sichuan University, Chengdu, China
| | - Zhiyue Liu
- Department of Cardiology, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaofan Cao
- Department of Cardiology, The First Affiliated Hospital, China Medical University, Shenyang, China
| | - Yingxian Sun
- Department of Cardiology, The First Affiliated Hospital, China Medical University, Shenyang, China
| | - Wenyu Hu
- Department of Cardiology, The First Affiliated Hospital, China Medical University, Shenyang, China.
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389
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390
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Cai J, Cheng J, Li H, Lin WJ, Li Y, Zhuo X, Huang X, Simone CB, Aronow WS, Chow ELW, Tang Y. A nomogram for the prediction of cerebrovascular disease among patients with brain necrosis after radiotherapy for nasopharyngeal carcinoma. Radiother Oncol 2019; 132:34-41. [PMID: 30825967 DOI: 10.1016/j.radonc.2018.11.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 11/05/2018] [Accepted: 11/07/2018] [Indexed: 11/21/2022]
Abstract
BACKGROUND AND PURPOSE This study sought to develop and validate a nomogram to predict cerebrovascular disease (CVD) among patients with brain necrosis after radiotherapy for nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS A total of 346 eligible patients with brain necrosis after radiotherapy for NPC were divided into a training set (n = 231) and a validation set (n = 115). A multivariate Cox proportional hazards regression model was used to select the significant variables for CVD prediction in the training set. Then, a nomogram was developed based on the regression model. The performance of the nomogram was assessed with respect to discrimination and calibration. All patients were classified into high- or low-risk groups based on the risk scores derived from the nomogram. Moreover, a decision curve analysis was performed with the combined training and validation sets to evaluate the clinical usefulness of the nomogram. RESULTS Four significant predictors were identified: hypertension, statin treatment, serum level of high-density lipoprotein, and interval between radiotherapy and brain necrosis. The nomogram incorporating these four predictors showed favorable calibration and discrimination regarding the training set, with a C-index of 0.763 (95% CI, 0.694 to 0.832), which was confirmed using the validation set (C-index 0.768; 95% CI, 0.675 to 0.861). Furthermore, the nomogram successfully stratified patients into high- and low-risk groups. The decision curve indicated that our nomogram was clinically useful. CONCLUSION The nomogram showed favorable predictive accuracy for CVD among patients with brain necrosis after radiotherapy for NPC and might aid in clinical decision making.
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Affiliation(s)
- Jinhua Cai
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Jinping Cheng
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Honghong Li
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Wei-Jye Lin
- Medical Research Center of Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Yi Li
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Xiaohuang Zhuo
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Xiaolong Huang
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Charles B Simone
- Department of Radiation Oncology, University of Maryland Medical Center, Baltimore, USA
| | - Wilbert S Aronow
- Department of Medicine, Westchester Medical Center and New York Medical College, New York, USA
| | - Edward L W Chow
- Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Yamei Tang
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China; Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, People's Republic of China.
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391
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Zhu C, Wang B, Xiao L, Guo Y, Zhou Y, Cao L, Yang S, Chen W. Mean platelet volume mediated the relationships between heavy metals exposure and atherosclerotic cardiovascular disease risk: A community-based study. Eur J Prev Cardiol 2019; 27:830-839. [PMID: 30776917 DOI: 10.1177/2047487319830536] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Heavy metals were related to increased risk of atherosclerotic cardiovascular disease (ASCVD). However, potential mechanisms under such associations remain unclear. We aimed to investigate the mediating role of mean platelet volume in the associations between heavy metals exposure and 10-year ASCVD risk. METHOD Urinary heavy metals and mean platelet volume were measured in 3081 adults from the Wuhan-Zhuhai cohort in China. The associations between urinary heavy metals, mean platelet volume and 10-year ASCVD risk were separately analyzed through generalized linear models and logistic regression models. Mediation analyses were conducted to assess the role of mean platelet volume in the associations between urinary heavy metals and 10-year ASCVD risk. RESULTS After adjusting for potential confounders, 10-year ASCVD risk was positively associated with urinary iron (odds ratio (OR) = 1.142, 95% confidence interval (1.038-1.256)), copper (OR = 1.384 (1.197-1.601)), zinc (OR = 1.520 (1.296-1.783)), cadmium (OR = 1.153 (0.990, 1.342)) and antimony (OR = 1.452 (1.237-1.704)), and negatively related with urinary barium (OR = 0.905 (0.831-0.985)). Also, we found significant dose-response relationships between urinary iron, zinc, antimony and mean platelet volume, as well as between mean platelet volume and 10-year ASCVD risk (all pfor trends < 0.05). Furthermore, mediation analyses indicated that mean platelet volume mediated 17.55%, 6.15% and 7.38% of the associations between urinary iron, zinc, antimony and 10-year ASCVD risk, respectively (all pvalue < 0.05). CONCLUSIONS Elevated concentrations of urinary iron, copper, zinc, cadmium and antimony were associated with increased risk of 10-year ASCVD. Mean platelet volume partially mediated the associations of urinary iron, zinc and antimony with 10-year ASCVD risk.
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Affiliation(s)
- Chunmei Zhu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lili Xiao
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yanjun Guo
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yun Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Limin Cao
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shijie Yang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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392
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Wang X, Yang X, Li J, Liu F, Chen J, Liu X, Cao J, Shen C, Yu L, Lu F, Wu X, Zhao L, Wu X, Li Y, Hu D, Huang J, Lu X, Gu D. Impact of healthy lifestyles on cancer risk in the Chinese population. Cancer 2019; 125:2099-2106. [PMID: 30748010 DOI: 10.1002/cncr.31971] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 12/06/2018] [Accepted: 12/17/2018] [Indexed: 12/13/2022]
Affiliation(s)
- Xinyan Wang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
| | - Xueli Yang
- Key Laboratory of Cardiovascular Epidemiology & 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 & 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 & Department of Epidemiology Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
| | - Jichun Chen
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology 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
| | - Jie Cao
- Key Laboratory of Cardiovascular Epidemiology & 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
| | - Ling Yu
- Department of Cardiology Fujian Provincial People’s Hospital Fuzhou China
| | - Fanghong Lu
- Cardio‐Cerebrovascular Control and Research Center Institute of Basic Medicine, Shandong Academy of Medical Sciences Jinan China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention Chengdu China
| | - Liancheng Zhao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
| | - Xigui Wu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology 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 Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
| | - Dongsheng Hu
- Department of Prevention Medicine Shenzhen University School of Medicine Shenzhen China
| | - Jianfeng Huang
- Key Laboratory of Cardiovascular Epidemiology & 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 & Department of Epidemiology 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 Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
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393
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Ihm SH, Bakris G, Sakuma I, Sohn IS, Koh KK. Controversies in the 2017 ACC/AHA Hypertension Guidelines: Who Can Be Eligible for Treatments Under the New Guidelines? - An Asian Perspective. Circ J 2018; 83:504-510. [PMID: 30606943 DOI: 10.1253/circj.cj-18-1293] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Until the 2017 ACC/AHA Hypertension Guidelines were released, the target blood pressure (BP) for adults with hypertension (HTN) was 140/90 mmHg in most of the guidelines. The new 2018 ESC/ESH, Canadian, Korean, Japan, and Latin American hypertension guidelines have maintained the <140/90 mmHg for the primary target in the general population and encourage reduction to <130/80 if higher risk. This is more in keeping with the 2018 American Diabetes Association guidelines. However, the 2017 ACC/AHA guidelines classify HTN as BP ≥130/80 mmHg and generally recommend target BP levels below 130/80 mmHg for hypertensive patients independently of comorbid disease or age. Although the new guidelines mean that more people (nearly 50% of adults) will be diagnosed with HTN, the cornerstone of therapy is still lifestyle management unless BP cannot be lowered to this level; thus, more people will require BP-lowering medications. To date, there have been many controversies about the definition of HTN and the target BP. Targeting an intensive systolic BP goal can increase the adverse effects of multiple medications and the cardiovascular disease risk by excessively lowering diastolic BP, especially in patients with high risk, including those with diabetes, chronic kidney disease, heart failure, and coronary artery disease, and the elderly. In this review, we discuss these issues, particularly regarding the optimal target BP.
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Affiliation(s)
- Sang-Hyun Ihm
- Department of Internal Medicine, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea
| | - George Bakris
- Department of Medicine, Comprehensive Hypertension Center, Section of Endocrinology, Diabetes, and Metabolism, University of Chicago Medicine
| | - Ichiro Sakuma
- Cardiovascular Medicine, Hokko Memorial Clinic.,Health Science University of Hokkaido
| | - Il Suk Sohn
- Department of Cardiology, Cardiovascular Center, Kyung Hee University Hospital at Gangdong
| | - Kwang Kon Koh
- Department of Cardiovascular Medicine, Heart Center, Gachon University Gil Medical Center.,Gachon Cardiovascular Research Institute
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394
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Yang X, Gu D. Response by Yang and Gu to Letter Regarding Article, "Predicting the 10-Year Risks of Atherosclerotic Cardiovascular Disease in Chinese Population: The China-PAR Project (Prediction for ASCVD Risk in China)". Circulation 2018; 135:e822-e823. [PMID: 28348098 DOI: 10.1161/circulationaha.117.027318] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Xueli Yang
- From Department of Epidemiology, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dongfeng Gu
- From Department of Epidemiology, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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395
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Tse G, Roever L, Wong MCS, Liu T. Cardiovascular risk assessment tools in non-Western populations. Int J Cardiol 2018; 272:331-332. [PMID: 30115420 DOI: 10.1016/j.ijcard.2018.08.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Revised: 08/01/2018] [Accepted: 08/09/2018] [Indexed: 11/15/2022]
Affiliation(s)
- Gary Tse
- Department of Medicine and Therapeutics, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong, China; Li Ka Shing Institute of Health Sciences, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong, China
| | - Leonardo Roever
- Department of Clinical Research, Federal University of Uberlândia, Uberlândia, MG, Brazil
| | - Martin C S Wong
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - 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.
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396
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Lloyd-Jones DM, Braun LT, Ndumele CE, Smith SC, Sperling LS, Virani SS, Blumenthal RS. Use of Risk Assessment Tools to Guide Decision-Making in the Primary Prevention of Atherosclerotic Cardiovascular Disease: A Special Report From the American Heart Association and American College of Cardiology. Circulation 2018; 139:e1162-e1177. [PMID: 30586766 DOI: 10.1161/cir.0000000000000638] [Citation(s) in RCA: 222] [Impact Index Per Article: 31.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Risk assessment is a critical step in the current approach to primary prevention of atherosclerotic cardiovascular disease. Knowledge of the 10-year risk for atherosclerotic cardiovascular disease identifies patients in higher-risk groups who are likely to have greater net benefit and lower number needed to treat for both statins and antihypertensive therapy. Current US prevention guidelines for blood pressure and cholesterol management recommend use of the pooled cohort equations to start a process of shared decision-making between clinicians and patients in primary prevention. The pooled cohort equations have been widely validated and are broadly useful for the general US clinical population. But, they may systematically underestimate risk in patients from certain racial/ethnic groups, those with lower socioeconomic status or with chronic inflammatory diseases, and overestimate risk in patients with higher socioeconomic status or who have been closely engaged with preventive healthcare services. If uncertainty remains for patients at borderline or intermediate risk, or if the patient is undecided after a patient-clinician discussion with consideration of risk enhancing factors (eg, family history), additional testing with measurement of coronary artery calcium can be useful to reclassify risk estimates and improve selection of patients for use or avoidance of statin therapy. This special report summarizes the rationale and evidence base for quantitative risk assessment, reviews strengths and limitations of existing risk scores, discusses approaches for refining individual risk estimates for patients, and provides practical advice regarding implementation of risk assessment and decision-making strategies in clinical practice.
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397
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Use of Risk Assessment Tools to Guide Decision-Making in the Primary Prevention of Atherosclerotic Cardiovascular Disease: A Special Report From the American Heart Association and American College of Cardiology. J Am Coll Cardiol 2018; 73:3153-3167. [PMID: 30423392 DOI: 10.1016/j.jacc.2018.11.005] [Citation(s) in RCA: 174] [Impact Index Per Article: 24.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Risk assessment is a critical step in the current approach to primary prevention of atherosclerotic cardiovascular disease. Knowledge of the 10-year risk for atherosclerotic cardiovascular disease identifies patients in higher-risk groups who are likely to have greater net benefit and lower number needed to treat for both statins and antihypertensive therapy. Current U.S. prevention guidelines for blood pressure and cholesterol management recommend use of the pooled cohort equations to start a process of shared decision-making between clinicians and patients in primary prevention. The pooled cohort equations have been widely validated and are broadly useful for the general U.S. clinical population. But, they may systematically underestimate risk in patients from certain racial/ethnic groups, those with lower socioeconomic status or with chronic inflammatory diseases, and overestimate risk in patients with higher socioeconomic status or who have been closely engaged with preventive healthcare services. If uncertainty remains for patients at borderline or intermediate risk, or if the patient is undecided after a patient-clinician discussion with consideration of risk enhancing factors (e.g., family history), additional testing with measurement of coronary artery calcium can be useful to reclassify risk estimates and improve selection of patients for use or avoidance of statin therapy. This special report summarizes the rationale and evidence base for quantitative risk assessment, reviews strengths and limitations of existing risk scores, discusses approaches for refining individual risk estimates for patients, and provides practical advice regarding implementation of risk assessment and decision-making strategies in clinical practice.
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398
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The Evolving Cardiovascular Disease Risk Scores for Persons with Diabetes Mellitus. Curr Cardiol Rep 2018; 20:126. [PMID: 30310997 DOI: 10.1007/s11886-018-1069-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
PURPOSE OF REVIEW We briefly introduce the concept and use of cardiovascular disease (CVD) risk scores and review the methodology for CVD risk score development and validation in patients with diabetes. We also discuss CVD risk scores for diabetic patients that have been developed in different countries. RECENT FINDINGS Patients with diabetes have a gradient of CVD risk that needs to be accurately assessed. Numerous CVD risk scores for diabetic patients have been created in various settings. The methods to develop risk scores are highly diverse and each choice has its own pros and cons. A well-constructed risk score for diabetic patients may be advocated by guidelines and adopted by healthcare providers to help determine preventive strategies. New risk factors are being investigated in order to improve the predictive accuracy of current risk scores. A suitable CVD risk score for the diabetes population should be accurate, low-cost, and beneficial to outcome. While the performance (accuracy) has all been internally validated, validation on external populations is still needed. Cost-effectiveness and clinical trials demonstrating improvement in outcomes are limited and should be the target of future research.
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399
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Wang H, Wang S, Sun G, Chen Y, Sun Y. Could subclinical organ damage markers improve atherosclerotic cardiovascular disease risk assessment in general Chinese population? Int J Cardiol 2018; 268:229. [DOI: 10.1016/j.ijcard.2018.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Accepted: 03/02/2018] [Indexed: 11/16/2022]
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400
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Tian J, Sheng CS, Sun W, Song X, Wang H, Li Q, Li W, Wang W. Effects of High Blood Pressure on Cardiovascular Disease Events Among Chinese Adults With Different Glucose Metabolism. Diabetes Care 2018; 41:1895-1900. [PMID: 30002198 DOI: 10.2337/dc18-0918] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 06/14/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To investigate cardiovascular disease (CVD) risks caused by blood pressure (BP) of 130-139/80-89 mmHg among Chinese adults with different glucose metabolism. RESEARCH DESIGN AND METHODS A prospective population-based cohort of 2,132 adults in Shanghai was established in 2002, and CVD information was collected during 10.9 years of follow-up. After assessing the association between BP categories and incident CVD, we analyzed the risk for CVD by blood glucose categories and BP categories combined by using multiple Cox regression analysis among 1,419 participants at follow-up. RESULTS The corresponding incidence of CVD per 1,000 person-years for the BP <130/80 mmHg, 130-139/80-89 mmHg, and ≥140/90 mmHg or treated groups were 3.0, 6.0, and 13.9, respectively. After adjusting for age, sex, and other factors, BP ≥140/90 mmHg was significantly associated with a higher CVD risk in general (hazard ratio 2.68 [95% CI 1.36-5.25]) and in various blood glucose categories (normoglycemia 2.59, prediabetes 3.03, diabetes mellitus [DM] 4.98). However, BP of 130-139/80-89 mmHg was significantly associated with a higher CVD risk in an estimated baseline 10-year atherosclerotic CVD (ASCVD) risk ≥10% (3.82 [1.42-9.78]) or DM (3.54 [1.05-11.88]) but not in the general population or for a baseline 10-year ASCVD risk <10%, normoglycemia, or prediabetes. CONCLUSIONS BP of 130-139/80-89 mmHg may result in a significantly higher CVD risk in Chinese adults with an estimated 10-year ASCVD risk ≥10% or DM but not in those with normoglycemia or prediabetes.
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Affiliation(s)
- Jingyan Tian
- Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrinology and Metabolism, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Chang-Sheng Sheng
- Center for Epidemiological Studies and Clinical Trials and Center for Vascular Evaluation, Shanghai Institute of Hypertension, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Weihong Sun
- Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences and Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Xiaomin Song
- Department of Endocrinology and Metabolism, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
| | - Haiyan Wang
- Pingliang Community Health Service Center, Yangpu District, Shanghai, China
| | - Qifang Li
- Department of Anesthesia, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Wenyi Li
- Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrinology and Metabolism, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Weiqing Wang
- Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrinology and Metabolism, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
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