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Ojo DT, Brewer PC, Imeh-Nathaniel A, Imeh-Nathaniel S, Broughton PX, Nathaniel TI. Sex differences in clinical risk factors in obese ischemic stroke patients with a history of smoking. BMC Cardiovasc Disord 2024; 24:288. [PMID: 38816791 PMCID: PMC11138086 DOI: 10.1186/s12872-024-03952-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 05/21/2024] [Indexed: 06/01/2024] Open
Abstract
Clinical risk factors associated obesity and smoking, as well as their combined effect, are not fully understood. This study aims to determine sex differences in risk factors in a population of acute ischemic stroke (AIS) patients who are obese and with a history of previous or current smoking. METHODS A retrospective analysis of risk factors in male and female AIS patients with baseline data of obesity and current or previous history of smoking, smoking, and obesity alone was determined. The primary predictor and outcome are risk factors associated with male and female AIS patients. Baseline risk factors were analyzed using a multivariate regression analysis to determine specific risk factors linked with the combined effect of obesity and current or previous history of smoking''. RESULTS Male obese AIS patients who are current or previous smokers were more likely to be older patients(OR = 1.024, 95% CI, 1.022-1.047, P = 0.033) that present with coronary artery disease (OR = 1.806, 95% CI, 1.028-3.174, P = 0.040), a history of alcohol use (OR = 2.873, 95% CI, 1.349-6.166, P = 0.006), elevated serum creatinine (OR = 4.724, 95% CI, 2.171-10.281, P < 0.001) and systolic blood pressure (OR = 1.029, 95% CI, 1.011-1.047, P < 0.002). Females were more associated with depression (OR = 0.432, 95% CI, 0.244-0.764, P = 0.004), previous TIA (OR = 0.319, 95% CI, 0.142-0.714, P < 0.005), and higher levels of HDL (OR = 0.938, 95% CI, 0.915-0.962, P < 0.001). CONCLUSION Our results reveal sex differences in risk factors in obese AIS patients with a current or past history of smoking. This finding emphasizes the need to develop management strategies to improve the care of obese AIS patients who are either current or former smokers.
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Affiliation(s)
- Dami T Ojo
- University of South Carolina School of Medicine-Greenville, Greenville, SC, 29605, USA
| | - Philip C Brewer
- University of South Carolina School of Medicine-Greenville, Greenville, SC, 29605, USA
| | | | | | - Philip X Broughton
- University of South Carolina School of Medicine-Greenville, Greenville, SC, 29605, USA
| | - Thomas I Nathaniel
- University of South Carolina School of Medicine-Greenville, Greenville, SC, 29605, USA.
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Zhang S, Cao C, Han Y, Hu H, Zheng X. A nonlinear relationship between the triglycerides to high-density lipoprotein cholesterol ratio and stroke risk: an analysis based on data from the China Health and Retirement Longitudinal Study. Diabetol Metab Syndr 2024; 16:96. [PMID: 38678294 PMCID: PMC11055270 DOI: 10.1186/s13098-024-01339-3] [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] [Received: 12/26/2023] [Accepted: 04/20/2024] [Indexed: 04/29/2024] Open
Abstract
OBJECTIVE The connection between triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) ratio and stroke risk is controversial. Our goal was to explore this relationship in individuals aged 45 and older enrolled in the China Health and Retirement Longitudinal Study (CHARLS). METHODS Our analysis encompassed 10,164 participants from the CHARLS cohorts. We applied the Cox proportional-hazards regression model to evaluate the potential correlation between the TG/HDL-C ratio and stroke incidence. Using a cubic spline function and smooth curve fitting within the Cox model allowed us to unearth a possible non-linear pattern in this relationship. We also conducted thorough sensitivity and subgroup analyses to deepen our understanding of the TG/HDL-C ratio's impact on stroke risk. RESULTS Adjusting for various risk factors, we observed a significant link between the TG/HDL-C ratio and increased stroke risk in individuals aged 45 and above (HR: 1.03, 95% CI 1.00-1.05, P = 0.0426). The relationship appeared non-linear, with an inflection at a TG/HDL-C ratio of 1.85. Ratios below this threshold indicated a heightened stroke risk (HR: 1.28, 95% CI 1.06-1.54, P = 0.0089), while ratios above it did not show a significant risk increase (HR: 1.01, 95% CI 0.98-1.04, P = 0.6738). Sensitivity analysis confirmed the robustness of these findings. Notably, non-smokers exhibited a stronger correlation between the TG/HDL-C ratio and stroke risk compared to past and current smokers. CONCLUSION Our investigation revealed a significant, yet non-linear, association between the TG/HDL-C ratio and the incidence of stroke among individuals aged 45 and above. Specifically, we found that stroke risk increased in correlation with TG/HDL-C ratio below the threshold of 1.85. These insights may guide healthcare providers in advising and developing more effective strategies for stroke prevention in this demographic.
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Affiliation(s)
- Shike Zhang
- Department of Rehabilitation, Shenzhen Yantian District People's Hospital, Shenzhen, 518000, Guangdong, China
- Department of Rehabilitation, Southern University of Science and Technology Yantian Hospital, Shenzhen, 518000, Guangdong, China
| | - Changchun Cao
- Department of Rehabilitation, Shenzhen Second People's Hospital, Shenzhen Dapeng New District Nan'ao People's Hospital, Shenzhen, 518000, Guangdong, China
| | - Yong Han
- Department of Emergency, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, 518035, Guangdong, China
| | - Haofei Hu
- Department of Nephrology, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, No. 3002, Sungang West Road, Futian District, Shenzhen, 518000, Guangdong, China.
| | - Xiaodan Zheng
- Department of Neurology, Shenzhen Samii Medical Center (The Fourth People's Hospital of Shenzhen), No. 1, Jinniu West Road, Shijing Street, Pingshan District, Shenzhen, 518000, Guangdong, China.
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Xu N, He Y, Zhang C, Zhang Y, Cheng S, Deng L, Zhong Y, Liao B, Wei Y, Feng J. TGR5 signalling in heart and brain injuries: focus on metabolic and ischaemic mechanisms. Neurobiol Dis 2024; 192:106428. [PMID: 38307367 DOI: 10.1016/j.nbd.2024.106428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 01/28/2024] [Accepted: 01/31/2024] [Indexed: 02/04/2024] Open
Abstract
The heart and brain are the core organs of the circulation and central nervous system, respectively, and play an important role in maintaining normal physiological functions. Early neuronal and cardiac damage affects organ function. The relationship between the heart and brain is being continuously investigated. Evidence-based medicine has revealed the concept of the "heart- brain axis," which may provide new therapeutic strategies for certain diseases. Takeda protein-coupled receptor 5 (TGR5) is a metabolic regulator involved in energy homeostasis, bile acid homeostasis, and glucose and lipid metabolism. Inflammation is critical for the development and regeneration of the heart and brain during metabolic diseases. Herein, we discuss the role of TGR5 as a metabolic regulator of heart and brain development and injury to facilitate new therapeutic strategies for metabolic and ischemic diseases of the heart and brain.
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Affiliation(s)
- Nan Xu
- Department of Cardiology, The First People's Hospital of Neijiang, Neijiang, China
| | - Yufeng He
- Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Key Laboratory of Medical Electrophysiology, Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, China
| | - Chunyu Zhang
- Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Key Laboratory of Medical Electrophysiology, Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, China
| | - Yongqiang Zhang
- Department of Cardiology, Hejiang County People's Hospital, Luzhou, China
| | - Shengjie Cheng
- Department of Cardiology, The First People's Hospital of Neijiang, Neijiang, China
| | - Li Deng
- Department of Rheumatology, The Afliated Hospital of Southwest Medical University, Luzhou, China
| | - Yi Zhong
- Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Key Laboratory of Medical Electrophysiology, Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, China
| | - Bin Liao
- Department of Cardiovascular Surgery, The Affiliated Hospital of Southwest Medical University, Metabolic Vascular Diseases Key Laboratory of Sichuan Province, Luzhou, China
| | - Yan Wei
- Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Key Laboratory of Medical Electrophysiology, Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, China.
| | - Jian Feng
- Department of Cardiology, The Affiliated Hospital of Southwest Medical University, Key Laboratory of Medical Electrophysiology, Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province, Institute of Cardiovascular Research, Southwest Medical University, Luzhou, China.
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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [Citation(s) in RCA: 182] [Impact Index Per Article: 182.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Mi J, Han X, Cao M, Pan Z, Guo J, Huang D, Sun W, Liu Y, Xue T, Guan T. The Association Between Urbanization and Electrocardiogram Abnormalities in China: a Nationwide Longitudinal Study. J Urban Health 2024; 101:109-119. [PMID: 38216823 PMCID: PMC10897075 DOI: 10.1007/s11524-023-00816-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/29/2023] [Indexed: 01/14/2024]
Abstract
The health effects of urbanization are controversial. The association between urbanization and reversible subclinical risks of cardiovascular diseases (e.g., electrocardiogram (ECG) abnormalities) has rarely been studied. This study aimed to assess the association between urbanization and ECG abnormalities in China based on the China National Stroke Screening Survey (CNSSS). We used changes in the satellite-measured impervious surfaces rate and nighttime light data to assess the level of urbanization. Every interquartile increment in the impervious surfaces rate or nighttime light was related to a decreased risk of ECG abnormalities, with odds ratios of 0.894 (95% CI, 0.869-0.920) or 0.809 (95% CI, 0.772-0.847), respectively. And we observed a U-shaped nonlinear exposure-response relationship curve between the impervious surfaces rate and ECG abnormalities. In conclusion, the current average level of urbanization among the studied Chinese adults remains a beneficial factor for reducing cardiovascular risks.
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Affiliation(s)
- Jiarun Mi
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Xueyan Han
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Man Cao
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Zhaoyang Pan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Jian Guo
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
- Medical Research Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Dengmin Huang
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Wei Sun
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Tao Xue
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing, 100191, China.
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing, 100871, China.
- Advanced Institute of Information Technology, Peking University, Hangzhou, 311215, China.
| | - Tianjia Guan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
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Liu F, Sun P, Cheng Y, Wang J, Ma W, Chen C, Shang S, Yu J. Age-Period-Cohort Analysis of Long-Term Trends in Ischemic Stroke Mortality in China Caused by Specific Risk Factors from 1990 to 2019. Neuroepidemiology 2024; 58:182-198. [PMID: 38295785 DOI: 10.1159/000536014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 12/12/2023] [Indexed: 06/06/2024] Open
Abstract
OBJECTIVE The objective of this study was to study the primary risk factors for the long-term trends of mortality rates in ischemic stroke (IS) in China. METHODS Using the Global Burden of Disease Study 2019 (GBD 2019) database, research was conducted on the 11 primary risk factors for the mortality rates of IS in China from 1990 to 2019. This study employed joinpoint regression software and the age-period-cohort method to evaluate the trends of mortality rates divided by age, period, and cohort over time. RESULTS From 1990 to 2019, the age-standardized mortality rate (ASMR) caused by a diet high in red meat and high body mass index in China showed an upward trend. ASMR increased first and then decreased due to smoking, diet high in sodium, particulate matter pollution, high fasting plasma glucose, and high systolic blood pressure. Low-density lipoprotein cholesterol (LDL-C), kidney dysfunction, low temperature, and lead exposure remained relatively stable during this period. In the 35-45 age group, the mortality rate of IS due to high LDL-C was up to about 60%, and smoking affected men more than women. Overall, high LDL-C, high systolic blood pressure, and particulate matter pollution were the most common risk factors in patients with IS. The risk of death rose with age. The period and cohort relative risks showed that metabolic risk factors had the greatest impact on the mortality of IS. CONCLUSION Metabolic risk factors have become the primary risk factors for the ASMR of IS in China. Relevant authorities should pay attention to their long-term effects on IS. Effective public health policies and interventions should be implemented to reduce the burden of IS.
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Affiliation(s)
- Fude Liu
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Peng Sun
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yawen Cheng
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jianyi Wang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Wenlong Ma
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Chen Chen
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Suhang Shang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jia Yu
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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7
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Becerril-Gaitan A, Ding D, Ironside N, Southerland AM, Worrall BB, Testai FD, Flaherty ML, Elkind MS, Koch S, Sung G, Kittner SJ, Mayson DJ, Gonzales N, McCauley JL, Malkoff M, Hall CE, Frankel MR, James ML, Anderson CD, Aronowski J, Savitz SI, Woo D, Chen CJ. Association Between Body Mass Index and Functional Outcomes in Patients With Intracerebral Hemorrhage. Neurology 2024; 102:e208014. [PMID: 38165334 PMCID: PMC10870743 DOI: 10.1212/wnl.0000000000208014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 10/13/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Evidence of the so-called "obesity paradox," which refers to the protective effect and survival benefit of obesity in patients with spontaneous intracerebral hemorrhage (ICH), remains controversial. This study aims to determine the association between body mass index (BMI) and functional outcomes in patients with ICH and whether it is modified by race/ethnicity. METHODS Included individuals were derived from the Ethnic/Racial Variations of Intracerebral Hemorrhage study, which prospectively recruited 1,000 non-Hispanic White, 1,000 non-Hispanic Black, and 1,000 Hispanic patients with spontaneous ICH. Only patients with available BMI were included. The primary outcome was 90-day mortality. Secondary outcomes were mortality at discharge, modified Rankin Scale (mRS), Barthel Index, and self-reported health status measures at 90 days. Associations between BMI and ICH outcomes were assessed using univariable and multivariable logistic, ordinal, and linear regression models, as appropriate. Sensitivity analyses after excluding frail patients and by patient race/ethnicity were performed. RESULTS A total of 2,841 patients with ICH were included. The median age was 60 years (interquartile range 51-73). Most patients were overweight (n = 943; 33.2%) or obese (n = 1,032; 36.3%). After adjusting for covariates, 90-day mortality was significantly lower among overweight and obese patients than their normal weight counterparts (adjusted odds ratio [aOR] = 0.71 [0.52-0.98] and aOR = 0.70 [0.50-0.97], respectively). Compared with patients with BMI <25 kg/m2, those with BMI ≥25 kg/m2 had better 90-day mRS (aOR = 0.80 [CI 0.67-0.95]), EuroQoL Group 5-Dimension (EQ-5D) (aβ = 0.05 [0.01-0.08]), and EQ-5D VAS (aβ = 3.80 [0.80-6.98]) scores. These differences persisted after excluding withdrawal of care patients. There was an inverse relationship between BMI and 90-day mortality (aOR = 0.97 [0.96-0.99]). Although non-Hispanic White patients had significantly higher 90-day mortality than non-Hispanic Black and Hispanic (26.6% vs 19.5% vs 18.0%, respectively; p < 0.001), no significant interactions were found between BMI and race/ethnicity. No significant interactions between BMI and age or sex for 90-day mortality were found, whereas for 90-day mRS, there was a significant interaction with age (pinteraction = 0.004). CONCLUSION We demonstrated that a higher BMI is associated with decreased mortality, improved functional outcomes, and better self-reported health status at 90 days, thus supporting the paradoxical role of obesity in patients with ICH. The beneficial effect of high BMI does not seem to be modified by race/ethnicity or sex, whereas age may play a significant role in patient functional outcomes.
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Affiliation(s)
- Andrea Becerril-Gaitan
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Dale Ding
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Natasha Ironside
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Andrew M Southerland
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Bradford B Worrall
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Fernando D Testai
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Matthew L Flaherty
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Mitchell S Elkind
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Sebastian Koch
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Gene Sung
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Steven J Kittner
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Douglas J Mayson
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Nicole Gonzales
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Jacob L McCauley
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Marc Malkoff
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Christiana E Hall
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Michael R Frankel
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Michael L James
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Christopher D Anderson
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Jaroslaw Aronowski
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Sean I Savitz
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Daniel Woo
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
| | - Ching-Jen Chen
- From the Departments of Neurosurgery (A.B.-G., C.-J.C.) and Neurology (J.A., S.I.S.), The University of Texas Health Science Center at Houston; Department of Neurosurgery (D.D.), University of Louisville, KY; Department of Neurosurgery (N.I.); Departments of Neurology and Public Health Sciences (A.M.S., B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; Department of Neurology (M.L.F., D.W.), University of Cincinnati, OH; Department of Neurology (M.S.E.), Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York; Department of Neurology (S.K.) and John P. Hussman Institute for Human Genomics (J.L.M.), University of Miami Miller School of Medicine, FL; Department of Neurology and Neurocritical Care and Stroke (G.S.), Keck School of Medicine, University of Southern California, Los Angeles; Department of Neurology (S.J.K.), University of Maryland School of Medicine, Baltimore; Department of Neurology (D.J.M.), MedStar Georgetown University Hospital, Washington, DC; Department of Neurology (N.G.), University of Colorado School of Medicine, Aurora; Departments of Neurology and Neurosurgery (M.M.), University of Tennessee Health Sciences, Memphis; Department of Neurology (C.E.H.), University of Texas Southwestern, Dallas; Department of Neurology (M.R.F.), Emory University, Grady Memorial Hospital, Atlanta, GA; Departments of Anesthesiology and Neurology (M.L.J.), Duke Clinical Research Institute, Duke University, Durham, NC; and Henry and Allison McCane Center for Brain Health and Center for Genomic Medicine (C.D.A.), Massachusetts General Hospital, Massachusetts, Boston
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Wang L, Han Y, Cao C, Hu H, Li H. The non-linear link between non-high-density lipoprotein to high-density lipoprotein ratio and the risk of stroke in middle-aged and older adults in Chinese: a prospective cohort study from the China health and retirement longitudinal study. Front Endocrinol (Lausanne) 2024; 14:1303336. [PMID: 38288470 PMCID: PMC10823364 DOI: 10.3389/fendo.2023.1303336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 12/20/2023] [Indexed: 02/01/2024] Open
Abstract
Objective This study aims to assess the association between the non-HDL-c/HDL-c ratio and stroke risk among middle-aged and older adults participating in the China Health and Retirement Longitudinal Study (CHARLS). Methods This study conducted a prospective cohort analysis, enrolling a total of 10,183 participants who met the designated criteria from CHARLS between 2011 and 2012. We then used the Cox proportional-hazards regression model to explore the relationship between baseline non-HDL-c/HDL-c ratio and stroke risk. Using a Cox proportional hazards regression with cubic spline function, we were able to identify the non-linear relationship between the non-HDL-c/HDL-c ratio and stroke occurrence. A series of sensitivity analyses were also carried out. Results The average age of the participants included in this study was 59.16 ± 9.35 years, and 4,735 individuals (46.68%) were male. Over a median follow-up period of 7.0 years, a total of 1,191 people (11.70%) experienced a stroke. Using a Cox proportional hazards regression model that was fully adjusted, we found no statistically significant correlation between the non-HDL-c/HDL-c ratio and the risk of stroke (HR=1.022; 95% CI 0.964, 1.083). Nevertheless, we did observe a non-linear relationship and saturation effect between the non-HDL-c/HDL-c ratio and stroke. Employing a two-piece Cox proportional hazards regression model and a recursive algorithm, we determined an inflection point of 2.685 for the non-HDL-c/HDL-c ratio. In instances where the non-HDL-c/HDL-c ratio fell below 2.685, for every 1-unit decrease in the non-HDL-c/HDL-c ratio, the likelihood of stroke decreased by 21.4% (HR=1.214, 95% CI: 1.039-1.418). In contrast, when the non-HDL-c/HDL-c ratio exceeded 2.685, there was no statistically significant change in the risk of stroke for each unit decrease in the non-HDL-c/HDL-c ratio (HR: 0.967, 95% CI: 0.897-1.042). The consistency of these findings across multiple sensitivity analyses suggests their robustness. Conclusion This study unveils a non-linear relationship between the non-HDL-c/HDL-c ratio and stroke risk in middle-aged and older adults in China. Specifically, when the non-HDL-c/HDL-c ratio was below 2.685, a significant and clearly positive association with stroke risk was observed. Additionally, maintaining the non-HDL-c/HDL-c ratio below 2.685 could potentially lead to a substantial reduction in the risk of stroke.
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Affiliation(s)
- Lanbo Wang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Yong Han
- Department of Emergency, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, China
- Department of Emergency, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Changchun Cao
- Department of Rehabilitation, Shenzhen Dapeng New District Nan’ao People’s Hospital, Shenzhen, Guangdong, China
| | - Haofei Hu
- Department of Nephrology, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, China
- Department of Nephrology, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Han Li
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
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9
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Huang H, Kuang Z, Mo R, Meng M, Cai Y, Ni X. The preliminary evidence on the association of the gut microbiota with stroke risk stratification in South Chinese population. Front Cell Infect Microbiol 2023; 13:1227450. [PMID: 38222855 PMCID: PMC10785002 DOI: 10.3389/fcimb.2023.1227450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 11/24/2023] [Indexed: 01/16/2024] Open
Abstract
Aims This study aimed to investigate the association between the gut microbiota and the risk of stroke. Methods Faecal samples from 60 participants in South China, including 45 individuals with risk factors for stroke and 15 healthy controls, were collected and subjected to 16S rRNA sequencing. A bioinformatics analysis was performed to characterise the gut microbial diversity and taxonomic compositions at different risk levels (low, moderate, and high) of stroke. Functional prediction and correlation analyses between the microbiota and laboratory markers were performed to explore the potential mechanisms. Results A significant difference in beta diversity was observed between the participants from the stroke risk and healthy control groups. Linear discriminant effect size analysis revealed a large number of vascular beneficial bacteria enriched in the participants from the healthy control and low-risk groups, but a few vascular harmful bacteria were more abundant in the participants from the high-risk group than in those from the other groups. In addition, Anaerostipes, Clostridium_XlVb, and Flavonifractor, all of which belonged to the Firmicutes phylum, were enriched in the participants from the low-risk group, and their relative abundances gradually decreased as the stroke risk increased. Spearman's analysis revealed that these outstanding microbiota correlated with the levels of triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, white blood cells, neutrophils, and carotid intima-media thickness. Conclusion The preliminary evidence suggests that gut microbiota is associated with stroke risk. It potentially ameliorates atherosclerosis by targeting lipid metabolism and inflammation. This provides novel insights into the early screening of stroke risk and primary prevention.
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Affiliation(s)
- Haiyan Huang
- The Department of Neurology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
- The Second Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zhuoran Kuang
- The Department of Neurology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
- The Second Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ruibi Mo
- The Second Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Miaomiao Meng
- The Second Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yefeng Cai
- The Department of Neurology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
- The Second Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China
- Guangdong Provincial Academy of Chinese Medical Sciences, Guangzhou, China
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xiaojia Ni
- The Department of Neurology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China
- The Second Clinical School of Guangzhou University of Chinese Medicine, Guangzhou, China
- Guangdong Provincial Academy of Chinese Medical Sciences, Guangzhou, China
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
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Weng S, Chen J, Ding C, Hu D, Liu W, Yang Y, Peng D. Utilizing machine learning algorithms for the prediction of carotid artery plaques in a Chinese population. Front Physiol 2023; 14:1295371. [PMID: 38028761 PMCID: PMC10657816 DOI: 10.3389/fphys.2023.1295371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 10/19/2023] [Indexed: 12/01/2023] Open
Abstract
Background: Ischemic stroke is a significant global health issue, imposing substantial social and economic burdens. Carotid artery plaques (CAP) serve as an important risk factor for stroke, and early screening can effectively reduce stroke incidence. However, China lacks nationwide data on carotid artery plaques. Machine learning (ML) can offer an economically efficient screening method. This study aimed to develop ML models using routine health examinations and blood markers to predict the occurrence of carotid artery plaques. Methods: This study included data from 5,211 participants aged 18-70, encompassing health check-ups and biochemical indicators. Among them, 1,164 participants were diagnosed with carotid artery plaques through carotid ultrasound. We constructed six ML models by employing feature selection with elastic net regression, selecting 13 indicators. Model performance was evaluated using accuracy, sensitivity, specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), F1 score, kappa value, and Area Under the Curve (AUC) value. Feature importance was assessed by calculating the root mean square error (RMSE) loss after permutations for each variable in every model. Results: Among all six ML models, LightGBM achieved the highest accuracy at 91.8%. Feature importance analysis revealed that age, Low-Density Lipoprotein Cholesterol (LDL-c), and systolic blood pressure were important predictive factors in the models. Conclusion: LightGBM can effectively predict the occurrence of carotid artery plaques using demographic information, physical examination data and biochemistry data.
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Affiliation(s)
- Shuwei Weng
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Research Institute of Blood Lipid and Atherosclerosis, Changsha, Hunan, China
| | - Jin Chen
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Research Institute of Blood Lipid and Atherosclerosis, Changsha, Hunan, China
| | - Chen Ding
- Department of Cardiology, Suzhou Dushu Lake Hospital, Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University, Suzhou, Jiangsu, China
| | - Die Hu
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Research Institute of Blood Lipid and Atherosclerosis, Changsha, Hunan, China
| | - Wenwu Liu
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Research Institute of Blood Lipid and Atherosclerosis, Changsha, Hunan, China
| | - Yanyi Yang
- Health Management Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Daoquan Peng
- Department of Cardiovascular Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Research Institute of Blood Lipid and Atherosclerosis, Changsha, Hunan, China
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11
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Sun W, Han X, Cao M, Pan Z, Guo J, Huang D, Mi J, Liu Y, Guan T, Li P, Huang C, Wang M, Xue T. Middle-term nitrogen dioxide exposure and electrocardiogram abnormalities: A nationwide longitudinal study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 266:115562. [PMID: 37866032 DOI: 10.1016/j.ecoenv.2023.115562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 10/03/2023] [Accepted: 10/07/2023] [Indexed: 10/24/2023]
Abstract
BACKGROUND Recently, professionals, such as those from the World Health Organization, have recommended a rigorous standard for nitrogen dioxide (NO2), a typical urban air pollutant affected by regular traffic emissions, based on its short-term and long-term cardiorespiratory effects. However, the association between middle-term NO2 exposure and cardiovascular disorders remains unknown. OBJECTIVES This study was conducted to examine the relationship between NO2 exposure and its middle-term cardiovascular risks indicated by electrocardiogram (ECG) abnormalities. METHOD We included 61,094 subjects (132,249 visits) with repeated ECG observations based on longitudinal data from the China National Stroke Screening Survey (CNSSS). The NO2 exposure concentration was derived from a predictive model, measured as the monthly average concentration in the 6 months of preceding the ECG measurement. We used the generalized estimation equation to assess the association between NO2 exposure and ECG abnormalities. RESULT For each 10 µg/m3 increase in monthly average NO2 concentration, the odds ratio of ECG abnormalities was 1.10 (95% confidence interval [CI] 1.09-1.12) after multiple adjustments. Stratified regression analyses of urban and rural residents showed associations between middle-term NO2 exposure and ECG abnormalities in urban (OR 1.09 [95% CI 1.08-1.11]) and rural residents (OR 1.14 [95% CI 1.10-1.19]). The association was robust within different subpopulations. Associations generally remained statistically significant (OR 1.03 [95% CI 1.02-1.05]) after extra adjustment for PM2.5. Exposure-response relationship analysis revealed a nearly linear relationship between NO2 exposure and the risk for ECG abnormalities. CONCLUSION Using the variation in ECG signals as a potentially reversible indicator for subclinical risk in cardiovascular systems, our study provides additional evidence on the increased risk posed by middle-term NO2 exposure. Our study showed that policies controlling for NO2 concentrations are beneficial to prevent cardiovascular diseases among Chinese adults.
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Affiliation(s)
- Wei Sun
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Xueyan Han
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Man Cao
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Zhaoyang Pan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Jian Guo
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China; Medical Research Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Dengmin Huang
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Jiarun Mi
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Tianjia Guan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China.
| | - Pengfei Li
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China
| | - Conghong Huang
- College of Land Management, Nanjing Agricultural University, Nanjing 210095, China
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY 14214, United States
| | - Tao Xue
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China; Advanced Institute of Information Technology, Peking University, Hangzhou, Zhejiang, China; State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management and Center for Environment and Health, Peking University, Beijing, China.
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12
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Guo L, Zhang M, Namassevayam G, Wei M, Zhang G, He Y, Guo Y, Liu Y. Effectiveness of health management among individuals at high risk of stroke: An intervention study based on the health ecology model and self-determination theory (HEM-SDT). Heliyon 2023; 9:e21301. [PMID: 37964830 PMCID: PMC10641168 DOI: 10.1016/j.heliyon.2023.e21301] [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: 05/30/2023] [Revised: 10/11/2023] [Accepted: 10/19/2023] [Indexed: 11/16/2023] Open
Abstract
Background Stroke is the second leading cause of death in adults worldwide. However, up to 80% of strokes can be prevented by modifying risk factors. Objective The study aims to assess the effectiveness of the Health Ecology Model and Self-Determination Theory (HEM-SDT) based health management intervention among individuals at high risk of stroke. Methods A randomized controlled trial was conducted in Zhengzhou from May 1st, 2020, to December 31st, 2020. A total of 229 participants were recruited for the study, with 116 individuals at high risk of stroke being randomly assigned to the HEM-SDT health management group, while 113 participants were enrolled in the control group, following their current routine practices. The Generalized Estimating Equation model (GEE) was used to analyze the differences in health knowledge, belief and, behavior between the two groups at the beginning of the intervention, and at 6-month intervals after the intervention. The chi-square test was utilized to assess the control rate of risk factors. Results After 6 months of intervention, there were significant improvements in health knowledge, behavior, and belief among the participants. The study found significant differences in the interaction effects between time and group for health knowledge (Mean, SD = 25.62 ± 3.88, 95%CI: 7.944-9.604, P<0.001), health belief (Mean, SD = 87.18 ± 14.21, 95%CI: 23.999-29.887, P<0.001), and health behavior (Mean, SD = 173.28 ± 24.22, 95%CI: 22.332-36.904, P<0.001). Additionally, the rates of hypertension, hyperglycemia, dyslipidemia, high or medium risk condition of stroke, obesity, hyperhomocysteinemia, smoking, alcohol consumption, and lack of exercise also showed statistical significance (P<0.05) after the intervention. Conclusion The HEM-SDT health management model improves the health knowledge, behavior, and beliefs in people at high risk of stroke and remarkably it shows improvement in modifiable risk factors. It can be recommended for systematic health management in people at high-risk of stroke.
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Affiliation(s)
- Lina Guo
- Department of Neurology, National Advanced Stroke Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Mengyv Zhang
- Department of Neurology, National Advanced Stroke Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Genoosha Namassevayam
- Department of Neurology, National Advanced Stroke Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Department of Supplementary Health Sciences, Faculty of Health-Care Sciences, Eastern University, Sri Lanka
| | - Miao Wei
- Department of Neurology, National Advanced Stroke Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Gege Zhang
- Department of Neurology, National Advanced Stroke Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yv He
- Department of Neurology, National Advanced Stroke Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Reproductive Medicine Center, Sir Run Run Shaw Hospital, Hangzhou, Zhejiang, China
| | - Yuanli Guo
- Department of Neurology, National Advanced Stroke Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yanjin Liu
- Department of Nursing, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
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13
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Lu H, Wang R, Li J, Tong M, Cao M, Liu H, Xiao Q, Zheng Y, Liu Y, Guan T, Xue T. Long-term exposure to the components of fine particulate matters and disability after stroke: Findings from the China National Stroke Screening Surveys. JOURNAL OF HAZARDOUS MATERIALS 2023; 460:132244. [PMID: 37611391 DOI: 10.1016/j.jhazmat.2023.132244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Revised: 07/04/2023] [Accepted: 08/05/2023] [Indexed: 08/25/2023]
Abstract
BACKGROUND Long-term exposure to ambient fine particulate matter (PM2.5) has been linked to an increased risk of stroke. However, the effect of long-term exposure to PM2.5 and its major components on the functional disability of stroke patients remains unclear. METHODS Based on China National Stroke Screening Survey data obtained from 2013 to 2019, we conducted a national multicenter longitudinal study of the associations of long-term exposure to PM2.5 and its components with the risk of disability after stroke in China. Post-stroke disability was assessed using the modified Rankin scale (mRS), which ranges from 0 to 5, with higher scores indicating greater disability. Long-term exposure to PM2.5 and its five components [sulfate (SO42-), nitrate (NO3-), ammonium salt (NH4+), organic matter (OM), and black carbon (BC)] was determined based on average concentrations during the 3 years preceding mRS administration according to the geographic coordinates of residential communities, using state-of-the-art estimates from multiple sources. We used a fixed-effect model to evaluate the associations between mRS scores and PM2.5 exposure, with adjustment for multiple covariates. RESULTS Every 10 µg/m3 increase in PM2.5 was associated with a 0.019 (95% confidence interval, 0.003, 0.036) increase in mRS score, but the effect was not significant after adjusting for all covariates [0.016 (95% CI, -0.003, 0.032)]. For PM2.5 components, each IQR (7.92 µg/m3) increment in OM exposure was associated significantly with 0.062 (95% CI, 0.013, 0.111) increment in the mRS score. A significant association was observed between SO42- exposure and the mRS score [0.057 (95% CI, 0.003, 0.112), per IQR: 6.28 µg/m3]. However, no significant association was found with BC, NO3-, or NH4+ exposure. Furthermore, the nonlinear curves were observed for the exposure-response relationship between PM2.5 exposure and the mRS score. CONCLUSION Greater PM2.5 exposure increased the mRS score and was associated with post-stroke functional disability among stroke patients. However, different chemical components showed unequal neurotoxic effects, and long-term exposure to OM and SO42- may play a more important role. SYNOPSIS This study reports fine particulate matter at higher concentrations damages the functional ability among specific stroke patients, and PM2.5 components have different neurotoxicities.
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Affiliation(s)
- Hong Lu
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Ruohan Wang
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jiajianghui Li
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Mingkun Tong
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Man Cao
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hengyi Liu
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Qingyang Xiao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Yixuan Zheng
- Center for Regional Air Quality Simulation and Control, Chinese Academy for Environmental Planning, Beijing 100012, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Tianjia Guan
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Tao Xue
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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Pan Z, Han X, Cao M, Guo J, Huang D, Sun W, Mi J, Liu Y, Xue T, Guan T. Short-term exposure to ozone and ECG abnormalities in China: A nationwide longitudinal study. JOURNAL OF HAZARDOUS MATERIALS 2023; 459:132290. [PMID: 37595468 DOI: 10.1016/j.jhazmat.2023.132290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 07/25/2023] [Accepted: 08/12/2023] [Indexed: 08/20/2023]
Abstract
Ambient ozone (O3) pollution has been associated with an increased risk of cardiovascular diseases. However, few studies have addressed the effect of O3 exposure on electrocardiogram (ECG) abnormalities, a subclinical indicator of early damage to the cardiovascular system. This study aimed to examine the association between short-term exposure to O3 and ECG abnormalities. We included 102,027 visits of 47,290 participants over 40 years old who had a normal ECG at baseline and then visited again at least once from the China National Stroke Screening Survey (CNSSS). Short-term ozone exposure concentrations were measured as averages of maximum daily 8-h O3 concentrations over the two weeks prior to ECG measurements. The generalized estimation equations models were used to evaluate the association between O3 exposure and ECG abnormalities. For every 10 µg/m3 increment in short-term O3 concentration, the odds ratio of any ECG abnormality was 1.055 (95% confidence interval [CI] 1.045-1.064). For ECG-diagnosed cardiac arrhythmia, the odds ratio was 1.062 (95% CI 1.052-1.072). A nonlinear analysis showed a sublinear relationship between O3 exposure and risk for ECG abnormalities. The association between O3 exposure and ECG abnormalities varied by subpopulation. Our study provided new epidemiological evidence on the association between short-term O3 exposure and ECG abnormalities. There is an urgent need to control ambient O3 pollution to prevent cardiovascular events.
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Affiliation(s)
- Zhaoyang Pan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Xueyan Han
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Man Cao
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Jian Guo
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China; Medical Research Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Dengmin Huang
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Wei Sun
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Jiarun Mi
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Tao Xue
- Institute of Reproductive and Child Health/ National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Advanced Institute of Information Technology, Peking university, Hangzhou, Zhejiang, China.
| | - Tianjia Guan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China.
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Han X, Cao M, Pan Z, Guo J, Huang D, Sun W, Mi J, Li P, Liu Y, Xue T, Guan T. Association between long-term exposure to PM 2.5 constituents and electrocardiographic abnormality: A nationwide longitudinal study in China. ENVIRONMENT INTERNATIONAL 2023; 178:108130. [PMID: 37572496 DOI: 10.1016/j.envint.2023.108130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 07/17/2023] [Accepted: 08/01/2023] [Indexed: 08/14/2023]
Abstract
BACKGROUND Electrocardiogram (ECG) abnormalities are known to have prognostic value for heart conditions, while evidence on the relationship between long-term exposure to PM2.5 constituents and electrocardiographic (ECG) abnormalities is limited. This study aimed to quantify the association between long-term exposure to PM2.5 constituents and changes in ECG diagnoses. METHODS We designed a longitudinal study among participants with repeated records of ECG examination based on the China National Stroke Screening Survey 2013-2018. Logistic regressions with multiple adjustment, estimated by the generalized estimating equation to incorporate repeated measurements, were used to assess the associations between the occurrence of any physician-diagnosed ECG abnormalities and long-term exposure to PM2.5 constituents. RESULTS We included 61,094 participants with 132,249 visits. All five constituents (sulfate, nitrate, ammonium, organic matter, and black carbon) were significantly associated with an increased risk of ECG abnormalities. The excess risk of ECG abnormalities per interquartile-range increase in exposure was the highest for sulfate (26%, 95% confidence interval [CI] 23-29%), followed by ammonium (22%, 19-26%), nitrate (21%, 17-24%), black carbon (16%, 13-10%) and organic matter (9%,6%-11%). We also found that atrial fibrillation patients might be susceptible to the adverse effects of PM2.5 constituents on ECG. CONCLUSION Differential associations between various constituents of PM2.5 and ECG abnormalities were found. The unequal toxicities for different chemical constituents of ambient particles on cardiovascular electrophysiological endpoints should be taken into consideration when considering the biological pathways linking PM2.5 and cardiovascular conditions.
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Affiliation(s)
- Xueyan Han
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Man Cao
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Zhaoyang Pan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Jian Guo
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China; State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Dengmin Huang
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Wei Sun
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Jiarun Mi
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Pengfei Li
- Institute of Reproductive and Child Health/ National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Tao Xue
- Institute of Reproductive and Child Health/ National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
| | - Tianjia Guan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China.
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Zhang Z, Zhao L, Lu Y, Meng X, Zhou X. Association between Chinese visceral adiposity index and risk of stroke incidence in middle-aged and elderly Chinese population: evidence from a large national cohort study. J Transl Med 2023; 21:518. [PMID: 37525182 PMCID: PMC10391837 DOI: 10.1186/s12967-023-04309-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 06/24/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND Abdominal obesity has long been considered as a crucial risk factor of stroke. Chinese visceral adiposity index (CVAI), a novel surrogate indicator of abdominal obesity, has been confirmed as a better predictor for coronary heart disease than other indicators in Asian population. However, the data on the relationship of CVAI with stroke is limited. The objective of our study is evaluating the relationship between CVAI and stroke incidence. METHODS In the present study, we enrolled 7242 middle-aged and elderly residents from the China Health and Retirement Longitudinal Study (CHARLS) and placed them into groups according to quartile of CVAI. The outcome of interest was stroke. Kaplan-Meier curves were used to estimate the cumulative incidences of stroke. Cox regression analyses and multivariable-adjusted restricted cubic spline (RCS) curves were performed to evaluate the relationship between CVAI and incident stroke. Multiple sensitivity analyses and subgroups analyses were performed to test the robustness of the findings. RESULTS During a median 84 months of follow-up, 612 (8.45%) participants experienced incident stroke, and the incidences of stroke for participants in quartiles (Q) 1-4 of CVAI were 4.42%, 7.29%, 9.06% and 13.04%, respectively. In the fully adjusted model, per 1.0-SD increment in CVAI has a significant increased risk of incident stroke: hazard ratio (HR) [95% confidence interval (CI)] was 1.17 (1.07-1.28); compared with participants in Q1 of CVAI, the HRs (95% CI) of incident stroke among those in Q2-4 were 1.47 (1.10-1.95), 1.62 (1.22-2.15), and 1.70 (1.28-2.27), respectively. Subgroups analyses suggested the positive association was significant in male participants, without diabetes, hypertension and heart disease. The findings were robust in all the sensitivity analyses. Additional, RCS curves showed a significant dose-response relationship of CVAI with risk of incident stroke (P for non-linear trend = 0.319). CONCLUSION Increased CVAI is significantly associated with higher risk of stroke incidence, especially in male individuals, without hypertension, diabetes and heart disease. The findings suggest that baseline CVAI is a reliable and effective biomarker for risk stratification of stroke, which has far-reaching significance for primary prevention of stroke and public health.
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Affiliation(s)
- Zenglei Zhang
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167, Beilishi Road, Xicheng District, Beijing, 100037, China
| | - Lin Zhao
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167, Beilishi Road, Xicheng District, Beijing, 100037, China
| | - Yiting Lu
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167, Beilishi Road, Xicheng District, Beijing, 100037, China
| | - Xu Meng
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167, Beilishi Road, Xicheng District, Beijing, 100037, China.
| | - Xianliang Zhou
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167, Beilishi Road, Xicheng District, Beijing, 100037, China.
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Abstract
Since 2015, stroke has become the leading cause of death and disability in China, posing a significant threat to the health of its citizens as a major chronic non-communicable disease. According to the China Stroke High-risk Population Screening and Intervention Program, an estimated 17.8 million [95% confidence interval (CI) 17.6-18.0 million] adults in China had experienced a stroke in 2020, with 3.4 million (95% CI 3.3-3.5 million) experiencing their first-ever stroke and another 2.3 million (95% CI 2.2-2.4 million) dying as a result. Additionally, approximately 12.5% (95% CI 12.4-12.5%) of stroke survivors were left disabled, as defined by a modified Rankin Scale score greater than 1, equating to 2.2 million (95% CI 2.1-2.2 million) stroke-related disabilities in 2020. As the population ages and the prevalence of risk factors like diabetes, hypertension, and hyperlipidemia continues to rise and remains poorly controlled, the burden of stroke in China is also increasing. A large national epidemiological survey initiated by the China Hypertension League in 2017 showed that the prevalence of hypertension was 24.7%; the awareness, treatment, and control rates in hypertensive patients were: 60.1%, 42.5%, and 25.4%, respectively. A nationally representative sample of the Chinese mainland population showed that the weighted prevalence of total diabetes diagnosed by the American Diabetes Association criteria was 12.8%, suggesting there are 120 million adults with diabetes in China, and the awareness, treatment, and control rates in diabetic patients were: 43.3%, 49.0%, and 49.4%, respectively. The "Sixth National Health Service Statistical Survey Report in 2018" showed that the proportion of the obese population in China was 37.4%, an increase of 7.2 points from 2013. Data from 1599 hospitals in the Hospital Quality Monitoring System and Bigdata Observatory Platform for Stroke of China (BOSC) showed that a total of 3,418,432 stroke cases [mean age ± standard error (SE) was (65.700 ± 0.006) years, and 59.1% were male] were admitted during 2020. Of those, over 80% (81.9%) were ischemic stroke (IS), 14.9% were intracerebral hemorrhage (ICH) strokes, and 3.1% were subarachnoid hemorrhage (SAH) strokes. The mean ± SE of hospitalization expenditures was Chinese Yuan (CNY) (16,975.6 ± 16.3), ranging from (13,310.1 ± 12.8) in IS to (81,369.8 ± 260.7) in SAH, and out-of-pocket expenses were (5788.9 ± 8.6), ranging from (4449.0 ± 6.6) in IS to (30,778.2 ± 156.8) in SAH. It was estimated that the medical cost of hospitalization for stroke in 2020 was CNY 58.0 billion, of which the patient pays approximately CNY 19.8 billion. In-hospital death/discharge against medical advice rate was 9.2% (95% CI 9.2-9.2%), ranging from 6.4% (95% CI 6.4-6.5%) for IS to 21.8% for ICH (95% CI 21.8-21.9%). From 2019 to 2020, the information about 188,648 patients with acute IS receiving intravenous thrombolytic therapy (IVT), 49,845 patients receiving mechanical thrombectomy (MT), and 14,087 patients receiving bridging (IVT + MT) were collected through BOSC. The incidence of intracranial hemorrhage during treatment was 3.2% (95% CI 3.2-3.3%), 7.7% (95% CI 7.5-8.0%), and 12.9% (95% CI 12.3-13.4%), respectively. And in-hospital death/discharge against medical advice rate was 8.9% (95% CI 8.8-9.0%), 16.5% (95% CI 16.2-16.9%), and 16.8% (95% CI 16.2-17.4%), respectively. A prospective nationwide hospital-based study was conducted at 231 stroke base hospitals (Level III) from 31 provinces in China through BOSC from January 2019 to December 2020 and 136,282 stroke patients were included and finished 12-month follow-up. Of those, over 86.9% were IS, 10.8% were ICH strokes, and 2.3% were SAH strokes. The disability rate [% (95% CI)] in survivors of stroke at 3-month and 12-month was 14.8% (95% CI 14.6-15.0%) and 14.0% (95% CI 13.8-14.2%), respectively. The mortality rate [% (95% CI)] of stroke at 3-month and 12-month was 4.2% (95% CI 4.1-4.3%) and 8.5% (95% CI 8.4-8.6%), respectively. The recurrence rate [% (95% CI)] of stroke at 3-month and 12-month was 3.6% (95% CI 3.5-3.7%) and 5.6% (95% CI 5.4-5.7%), respectively. The Healthy China 2030 Stroke Action Plan was launched as part of this review, and the above data provide valuable guidelines for future stroke prevention and treatment efforts in China.
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Affiliation(s)
- Wen-Jun Tu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Long-De Wang
- School of Public Health, Peking University, Beijing, 100191, China.
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Wallace ML, Mentch L, Wheeler BJ, Tapia AL, Richards M, Zhou S, Yi L, Redline S, Buysse DJ. Use and misuse of random forest variable importance metrics in medicine: demonstrations through incident stroke prediction. BMC Med Res Methodol 2023; 23:144. [PMID: 37337173 PMCID: PMC10280951 DOI: 10.1186/s12874-023-01965-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 06/06/2023] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND Machine learning tools such as random forests provide important opportunities for modeling large, complex modern data generated in medicine. Unfortunately, when it comes to understanding why machine learning models are predictive, applied research continues to rely on 'out of bag' (OOB) variable importance metrics (VIMPs) that are known to have considerable shortcomings within the statistics community. After explaining the limitations of OOB VIMPs - including bias towards correlated features and limited interpretability - we describe a modern approach called 'knockoff VIMPs' and explain its advantages. METHODS We first evaluate current VIMP practices through an in-depth literature review of 50 recent random forest manuscripts. Next, we recommend organized and interpretable strategies for analysis with knockoff VIMPs, including computing them for groups of features and considering multiple model performance metrics. To demonstrate methods, we develop a random forest to predict 5-year incident stroke in the Sleep Heart Health Study and compare results based on OOB and knockoff VIMPs. RESULTS Nearly all papers in the literature review contained substantial limitations in their use of VIMPs. In our demonstration, using OOB VIMPs for individual variables suggested two highly correlated lung function variables (forced expiratory volume, forced vital capacity) as the best predictors of incident stroke, followed by age and height. Using an organized analytic approach that considered knockoff VIMPs of both groups of features and individual features, the largest contributions to model sensitivity were medications (especially cardiovascular) and measured medical risk factors, while the largest contributions to model specificity were age, diastolic blood pressure, self-reported medical risk factors, polysomnography features, and pack-years of smoking. Thus, we reach very different conclusions about stroke risk factors using OOB VIMPs versus knockoff VIMPs. CONCLUSIONS The near-ubiquitous reliance on OOB VIMPs may provide misleading results for researchers who use such methods to guide their research. Given the rapid pace of scientific inquiry using machine learning, it is essential to bring modern knockoff VIMPs that are interpretable and unbiased into widespread applied practice to steer researchers using random forest machine learning toward more meaningful results.
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Affiliation(s)
- Meredith L Wallace
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15231, USA.
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Lucas Mentch
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bradley J Wheeler
- School of Computing and Information, University of Pittsburgh, Pittsburgh, PA, USA
| | - Amanda L Tapia
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15231, USA
| | - Marc Richards
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Siyu Zhou
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lixia Yi
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Susan Redline
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15231, USA
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Yang K, Chen M, Wang Y, Jiang G, Hou N, Wang L, Wen K, Li W. Development of a predictive risk stratification tool to identify the population over age 45 at risk for new-onset stroke within 7 years. Front Aging Neurosci 2023; 15:1101867. [PMID: 37388187 PMCID: PMC10301757 DOI: 10.3389/fnagi.2023.1101867] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 05/09/2023] [Indexed: 07/01/2023] Open
Abstract
Background and purpose With the acceleration of the aging process of society, stroke has become a major health problem in the middle-aged and elderly population. A number of new stroke risk factors have been recently found. It is necessary to develop a predictive risk stratification tool using multidimensional risk factors to identify people at high risk for stroke. Methods The study included 5,844 people (age ≥ 45 years) who participated in the China Health and Retirement Longitudinal Study in 2011 and its follow-up up to 2018. The population samples were divided into training set and validation set according to 1:1. A LASSO Cox screening was performed to identify the predictors of new-onset stroke. A nomogram was developed, and the population was stratified according to the score calculated through the X-tile program. Internal and external verifications of the nomogram were performed by ROC and calibration curves, and the Kaplan-Meier method was applied to identify the performance of the risk stratification system. Results The LASSO Cox regression screened out 13 candidate predictors from 50 risk factors. Finally, nine predictors, including low physical performance and the triglyceride-glucose index, were included in the nomogram. The nomogram's overall performance was good in both internal and external validations (AUCs at 3-, 5-, and 7-year periods were 0.71, 0.71, and 0.71 in the training set and 0.67, 0.65, and 0.66 in the validation set, respectively). The nomogram was proven to excellently discriminate between the low-, moderate-, and high-risk groups, with a prevalence of 7-year new-onset stroke of 3.36, 8.32, and 20.13%, respectively (P < 0.001). Conclusion This research developed a clinical predictive risk stratification tool that can effectively identify the different risks of new-onset stroke in 7 years in the middle-aged and elderly Chinese population.
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Affiliation(s)
- Kang Yang
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Minfang Chen
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yaoling Wang
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Gege Jiang
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Niuniu Hou
- Department of Thyroid, Breast, and Vascular Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Liping Wang
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kai Wen
- School of Software and Microelectronics, Peking University, Beijing, China
| | - Wei Li
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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20
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Tian W, Zhu G, Xiao W, Gao B, Lu W, Wang Y. Stroke burden and attributable risk factors in China, 1990-2019. Front Neurol 2023; 14:1193056. [PMID: 37292127 PMCID: PMC10245554 DOI: 10.3389/fneur.2023.1193056] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/03/2023] [Indexed: 06/10/2023] Open
Abstract
Background and purpose Understanding the temporal trends of stroke burden and its attributable risk factors are essential for targeted prevention strategies. We aimed to describe the temporal trends and attributable risk factors of stroke in China. Methods Data on the stroke burden [incidence, prevalence, mortality, and disability-adjusted life years (DALYs)] and the population-attributable fraction for stroke risk factors from 1990 to 2019 were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We analyzed trends in the burden of stroke and its attributable risk factors from 1990 to 2019, and the characteristics of stroke-attributable risk factors by sex, age group, and stroke subtype. Results From 1990 to 2019, the age-standardized incidence, mortality, and DALY rates for total stroke decreased by 9.3% (3.3, 15.5), 39.8% (28.6, 50.7), and 41.6% (30.7, 50.9) respectively. The corresponding indicators all decreased for intracerebral hemorrhage and subarachnoid hemorrhage. The age-standardized incidence rate of ischemic stroke increased by 39.5% (33.5 to 46.2) for male patients and by 31.4% (24.7 to 37.7) for female patients, and the age-standardized mortality and DALY rates remained almost unchanged. The three leading stroke risk factors were high systolic blood pressure, ambient particulate matter pollution, and smoking. High systolic blood pressure has remained the leading risk factor since 1990. The attributable risk of ambient particulate matter pollution shows a clear upward trend. Smoking and alcohol consumption were important risk factors for men. Conclusion This study reinforced the findings of an increased stroke burden in China. Precise stroke prevention strategies are needed to reduce the disease burden of stroke.
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Affiliation(s)
- Wenxin Tian
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
| | - Guanghan Zhu
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
| | - Wenbo Xiao
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
| | - Bei Gao
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
| | - Wenli Lu
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
| | - Yuan Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
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Wan B, Ma N, Zhou Z, Lu W. Modifiable risk factors that mediate the effect of educational attainment on the risk of stroke: a network Mendelian randomization study. Mol Brain 2023; 16:39. [PMID: 37170327 PMCID: PMC10173578 DOI: 10.1186/s13041-023-01030-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 04/27/2023] [Indexed: 05/13/2023] Open
Abstract
BACKGROUND Stroke is a common cerebrovascular disease with great danger to public health. Educational inequality is a universal issue that influences populations' stroke risk. This study aimed to investigate the causal relationship between education and stroke risk and the contributions of effects mediated by four modifiable factors. MATERIALS AND METHODS Public large-scale genome-wide association study (GWAS) summary data associated with educational attainment, hypertensive diseases, body mass index (BMI), smoking behavior, time spent on watching the television (TV), and stroke were obtained from European ancestry. The data were used to investigate the causal relationship among educational attainment, hypertensive disease, BMI, smoking, watching TV, and stroke risk. Inverse variance weighted (IVW) method was used as a primary algorithm for estimating causal direction and effect size in univariable and multivariable Mendelian randomization (MR) analyses. RESULTS Higher educational attainment was a causal protective factor, while hypertensive diseases, higher BMI, smoking, and longer time spent on watching the TV were all causal risk factors for the risk of stroke. Hypertensive disease, BMI, smoking, and watching TV were all mediators for linking the causal relationship between educational attainment and stroke risk. Hypertensive disease, BMI, smoking, and watching TV explained 47.35%, 24.74%, 15.72%, and 2.29% of the variance in educational attainment's effect on stroke risk, respectively. The explained proportion reached 69.32% after integrating the four factors. CONCLUSIONS These findings support the causal effect of educational attainment on the risk of stroke, with a substantial proportion mediated by modifiable risk factors. Interventions on these modifiable factors would lead to substantial reductions in stroke cases attributable to educational inequality.
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Affiliation(s)
- Bangbei Wan
- Reproductive Medical Center, Hainan Women and Children's Medical Center, Haikou, China.
- Central South University Xiangya School of Medicine Affiliated Haikou Hospital, Haikou, China.
| | - Ning Ma
- Reproductive Medical Center, Hainan Women and Children's Medical Center, Haikou, China
| | - Zhi Zhou
- Reproductive Medical Center, Hainan Women and Children's Medical Center, Haikou, China
| | - Weiying Lu
- Reproductive Medical Center, Hainan Women and Children's Medical Center, Haikou, China.
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22
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Păun O, Serbănescu MS, Badea O, Mogoantă L. Assessment of Stroke Patients Admitted to a Tertiary Emergency County Hospital of Mehedinți - Romania. CURRENT HEALTH SCIENCES JOURNAL 2023; 49:179-185. [PMID: 37779835 PMCID: PMC10541070 DOI: 10.12865/chsj.49.02.179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 05/05/2023] [Indexed: 10/03/2023]
Abstract
Cerebrovascular accidents (CVA)-strokes represent a major public health problem worldwide, due to the large number of people affected. Also, there is a large number of people who die from stroke, especially in developing countries. Our study included a group of 119 patients, diagnosed with stroke and admitted to the Emergency Hospital of Drobeta Turnul-Severin, Mehedinți county, between 2016-2020. The analysis of risk factors and associated comorbidities showed that stroke can affect both the elderly and young people, under 20 years old. However, approximately 4/5 of CVA patients (79.83%) were aged over 50 years old. If non-ischemic strokes predominated in patients under the age of 50, after this age there is a tendency to balance the incidence between the eight main forms of stroke. No significant differences were observed regarding the social environment of the patients, which shows that the risk factors are almost identical in both social environments. Among the modifiable risk factors, we highlighted: high blood pressure in 55.46% of cases, obesity in 19.33% of cases, atherosclerosis in 10.92% of cases, diabetes mellitus in 10.92%, kidney failure in 6.72% of cases. The data we obtained show that there are possibilities to reduce the incidence of stroke by controlling and reducing the modifiable risk factors.
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Affiliation(s)
- Octavian Păun
- PhD Student Doctoral School, University of Medicine and Pharmacy of Craiova, Romania
| | - Mircea-Sebastian Serbănescu
- Department of Medical Informatics and Biostatistics, University of Medicine and Pharmacy of Craiova, Romania
| | - Oana Badea
- Department of Modern Languages, University of Medicine and Pharmacy of Craiova, Romania
| | - Laurențiu Mogoantă
- Department of Histology, University of Medicine and Pharmacy of Craiova, Romania
- Romanian Academy of Medical Sciences, Craiova Subsidiary, Romania
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23
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Zhao Y, Hua X, Ren X, Ouyang M, Chen C, Li Y, Yin X, Song P, Chen X, Wu S, Song L, Anderson CS. Increasing burden of stroke in China: A systematic review and meta-analysis of prevalence, incidence, mortality, and case fatality. Int J Stroke 2023; 18:259-267. [PMID: 36274585 DOI: 10.1177/17474930221135983] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND The epidemiology of stroke is evolving in China as the population undergoes demographic, lifestyle, and economic transitions. An updated review is pertinent to providing feedback on current, and in planning future, prevention and management strategies. AIMS To identify high-quality epidemiological studies for quantifying the prevalence, incidence, mortality, and case fatality for stroke in China. METHODS A search was undertaken across a range of bibliographic databases on 30 November 2021 without time limitation. Assessments were made of the risk of bias of the included studies. The outcomes were synthesized using a random-effects model. Subgroup analysis and meta-regression models were used to define the source of heterogeneity. RESULTS Of 9407 identified records, 26 population-based studies were included. Due to significant heterogeneity across the studies, the original range for crude rates of indices was wide. The pooled annual prevalence was 1329.5/100,000 (95% confidence interval (CI) 713.6-2131.9, p < 0.001), incidence 442.1/100,000 (327.6-573.8, p < 0.001), mortality 154.1/100,000 (52.6-308.8, I2 = 100%, p < 0.001), and case fatality 35.8% (26.1% to 46.1%, I2 = 97%, p < 0.001). The prevalence and incidence of stroke have increased, but stroke-related case fatality has declined in China over recent decades. There are significant regional and rural-urban differences in incidence rates. CONCLUSION Despite improved public health policies and healthcare delivery, the burden of stroke remains high in China. Further coordinated efforts are required in prevention and community care to offset the likelihood of further expansion in the absolute number of stroke cases in this large population.
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Affiliation(s)
- Yang Zhao
- The George Institute for Global Health China, Beijing, China.,The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
| | - Xing Hua
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Xinwen Ren
- The George Institute for Global Health China, Beijing, China
| | - Menglu Ouyang
- The George Institute for Global Health China, Beijing, China.,The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
| | - Chen Chen
- The George Institute for Global Health China, Beijing, China.,The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia.,Neurology Department, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yunke Li
- The George Institute for Global Health China, Beijing, China
| | - Xiaoya Yin
- The George Institute for Global Health China, Beijing, China.,Shanghai Municipal Center for Disease Control & Prevention, Shanghai, China
| | - Peige Song
- School of Public Health and Women's Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Xiaoying Chen
- The George Institute for Global Health China, Beijing, China.,The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
| | - Simiao Wu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Lili Song
- The George Institute for Global Health China, Beijing, China.,The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia
| | - Craig S Anderson
- The George Institute for Global Health China, Beijing, China.,The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia.,Department of Neurology, Royal Prince Alfred Hospital, Sydney, NSW, Australia
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24
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 1399] [Impact Index Per Article: 1399.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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25
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Liu L, Yang Y, Zhao Y, Zhang T. Burden of stroke and its risk factors in Yunnan Province of China, 1990-2017. Int J Qual Health Care 2023; 35:6927155. [PMID: 36527417 DOI: 10.1093/intqhc/mzac101] [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: 07/12/2022] [Revised: 11/18/2022] [Accepted: 12/17/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND There is an overall decreasing trend in stroke incidence and an increasing trend in its prevalence. Disease burden of stroke continues to increase with an increase in the absolute number. In-depth analysis of stroke burden trends in remote areas is extremely important. Our aim was to describe the disease burden of and risk factors for stroke in Yunnan, from 1990 to 2017. METHODS The methodological framework and analytical strategies adopted in the 2017 Global Burden of Disease study were used. RESULTS Age-standardized mortality associated with stroke decreased from 1.53 per 100 000 in 1990 to 1.14 per 100 000 in 2017. The prevalence of stroke in Yunnan Province increased from 344 per 100 000 in 1990 to 870 per 100 000 in 2017. The age-standardized rates of years of life lost (YLLs), years lived with disability (YLDs) and disability-adjusted life years (DALYs) decreased more significantly for women than for men. The age-standardized rates of DALYs and YLLs of stroke decreased by 24.3 and 28.4%, respectively, from 1990 to 2017, and the rate of YLDs increased by 32.5%. The top three risk factors for stroke were dietary risks, high systolic blood pressure and tobacco consumption, and their percentage contributions to the DALYs of stroke were 67.5, 51.5 and 29.1%, respectively. CONCLUSIONS The burden of stroke has increased in Yunnan since 1990. The health department should emphasize on the changes of stroke risk factors and advocate healthy diet and living habits for residents.
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Affiliation(s)
- Lu Liu
- School of Public Health, Dali University, 22 Wanhua Road, Dali City, Dali Bai Autonomous Prefecture, Yunnan Province 671000, P. R. China
| | - Yixing Yang
- School of Public Health, Dali University, 22 Wanhua Road, Dali City, Dali Bai Autonomous Prefecture, Yunnan Province 671000, P. R. China
| | - Yuan Zhao
- School of Public Health, Dali University, 22 Wanhua Road, Dali City, Dali Bai Autonomous Prefecture, Yunnan Province 671000, P. R. China
| | - Tai Zhang
- School of Public Health, Dali University, 22 Wanhua Road, Dali City, Dali Bai Autonomous Prefecture, Yunnan Province 671000, P. R. China
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26
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Wang Q, Zhang L, Li Y, Tang X, Yao Y, Fang Q. Development of stroke predictive model in community-dwelling population: A longitudinal cohort study in Southeast China. Front Aging Neurosci 2022; 14:1036215. [PMID: 36620776 PMCID: PMC9813513 DOI: 10.3389/fnagi.2022.1036215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 12/06/2022] [Indexed: 12/24/2022] Open
Abstract
Background Stroke has been the leading cause of death and disability in the world. Early recognition and treatment of stroke could effectively limit brain damage and vastly improve outcomes. This study aims to develop a highly accurate prediction model of stroke with a list of lifestyle behaviors and clinical characteristics to distinguish high-risk groups in the community-dwelling population. Methods Participants in this longitudinal cohort study came from the community-dwelling population in Suzhou between November 2018 and June 2019. A total of 4,503 residents participated in the study, while stroke happened to 22 participants in the 2-year follow-up period. Baseline information of each participant was acquired and enrolled in this study. T-test, Chi-square test, and Fisher's exact test were used to examine the relationship of these indexes with stroke, and a prediction scale was constructed by multivariate logistic regression afterward. Receiver operating characteristic analysis was applied to testify to the prediction accuracy. Results A highly accurate prediction model of stroke was constructed by age, gender, exercise, meat and vegetarian diet, BMI, waist circumference, systolic blood pressure, Chinese visceral adiposity index, and waist-height ratio. Two additional prediction models for overweight and non-overweight individuals were formulated based on crucial risk factors, respectively. The stroke risk prediction models for community-dwelling and overweight populations had accuracies of 0.79 and 0.82, severally. Gender and exercise were significant predictors (χ2 > 4.57, p < 0.05) in the community-dwelling population model, while homocysteine (χ2 = 4.95, p < 0.05) was significant in the overweight population model. Conclusion The predictive models could predict 2-year stroke with high accuracy. The models provided an effective tool for identifying high-risk groups and supplied guidance for improving prevention and treatment strategies in community-dwelling population.
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Affiliation(s)
- Qi Wang
- Department of Biostatistics, School of Public Health, Fudan University, Shanghai, China
| | - Lulu Zhang
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yidan Li
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiang Tang
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, China,*Correspondence: Xiang Tang,
| | - Ye Yao
- Department of Biostatistics, School of Public Health, Fudan University, Shanghai, China,National Clinical Research Centre for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China,Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China,Ye Yao,
| | - Qi Fang
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, China
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27
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Huang M, Xu S, Zhou M, Luo J, Zha F, Shan L, Yang Q, Zhou B, Wang Y. Lysophosphatidylcholines and phosphatidylcholines as biomarkers for stroke recovery. Front Neurol 2022; 13:1047101. [PMID: 36588912 PMCID: PMC9797831 DOI: 10.3389/fneur.2022.1047101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 11/29/2022] [Indexed: 12/16/2022] Open
Abstract
Stroke is a serious global public health issue, associated with severe disability and high mortality rates. Its early detection is challenging, and no effective biomarkers are available. To obtain a better understanding of stroke prevention, management, and recovery, we conducted lipidomic analyses to characterize plasma metabolic features. Lipid species were measured using an untargeted lipidomic analysis with liquid chromatography-tandem mass spectrometry. Sixty participants were recruited in this cohort study, including 20 healthy individuals and 40 patients with stroke. To investigate the association between lipids related to long-term functional recovery in stroke patients. The primary independent variable was activities of daily living (ADL) dependency upon admission to the stroke unit and at the 3-month follow-up appointment. ADL dependency was assessed using the Barthel Index. Eleven significantly altered lipid species between the stroke and healthy groups were detected and displayed in a hierarchically clustered heatmap. Acyl carnitine, triacylglycerol, and ceramides were detected as potential lipid markers. Regarding the association between lipid profiles and functional status of patients with stroke the results indicated, lysophosphatidylcholines (LPC) and phosphatidylcholines were closely associated with stroke recovery. LPC may contribute positively role in patient's rehabilitation process via an anti-inflammatory mechanism. Appropriate management or intervention for lipid levels is expected to lead to better clinical outcomes.
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Affiliation(s)
- Meiling Huang
- Department of Rehabilitation, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Shaohang Xu
- Deepxomics., Ltd., Shenzhen, Guangdong, China
| | - Mingchao Zhou
- Department of Rehabilitation, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Jiao Luo
- Department of Rehabilitation, Shenzhen Dapeng New District Nan'ao People's Hospital, Shenzhen, Guangdong, China
| | - Fubing Zha
- Department of Rehabilitation, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Linlin Shan
- Department of Rehabilitation, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Qingqing Yang
- Department of Rehabilitation, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Baojin Zhou
- Deepxomics., Ltd., Shenzhen, Guangdong, China,Baojin Zhou
| | - Yulong Wang
- Department of Rehabilitation, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China,*Correspondence: Yulong Wang
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28
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Li AL, Ji Y, Zhu S, Hu ZH, Xu XJ, Wang YW, Jian XZ. Risk probability and influencing factors of stroke in followed-up hypertension patients. BMC Cardiovasc Disord 2022; 22:328. [PMID: 35871681 PMCID: PMC9308930 DOI: 10.1186/s12872-022-02780-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 07/04/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Objective
To explore the risk probability and main influencing factors of stroke in followed-up hypertension patients through the analysis of long-term followed-up cohort data.
Methods
The method of followed-up observation cohort was used to collect the information of 168,417 followed-up hypertension patients from 2002 to 2020 in Jiading District in Shanghai. Kaplan–Meier method was used to analyze the risk probability of stroke complications in long-term followed-up HTN patients, and the influencing factors were analyzed by Cox proportional risk model.
Results
Among 168,417 followed-up hypertension patients, 11,143 cases had suffered stroke, and the cumulative incidence rate of stroke was 6.62% (male was 6.87%, female was 6.37%). With the extension of the hypertension years, the cumulative risk probability of stroke in HTN patients would continue to increase and the interval was not equidistant. The total cumulative risk probability of stroke in HTN patients was 78.9% (male was 91.0%, female was 70.7%). During the period of hypertension, the risk occurring probability of stroke was not fixed, but fluctuating. There were 4 onset peaks, which were in 8 years (probability was 4.2%), 15 years (probability was 14.0%), 22 years (probability was 6.0%) and 26 years (probability was 13.9%). The highest risk probability of male patients was in 26 years (probability was 23.1%), and the second peak was in 15 years (probability was 15.6%). The highest risk probability of female patients was in 15 years (probability was 12.9%), and the second peak was in 26 years (probability was 8.7%). The risk probability of different gender, BP grade and BMI was different, the male were at higher risk than the female, stage 3 HTN was higher than stage 2 and stage 1 HTN, obese people and underweight people were at higher risk than those who have normal weight. The main factors closely related to the occurrence of stroke complications were age (RR = 2.917, p < 0.001), body mass index (RR = 1.654, p < 0.001), family history of stroke (RR = 1.386, p < 0.001) and blood pressure grade (RR = 1.148, p < 0.001).
Conclusion
The risk probability of stroke among hypertension patients was high in followed-up hypertension patients (total 78.9%, male 91.0%, female 70.7%), and would continue to increase disproportionately during period of hypertension (4 different onset peaks). With the persistence of hypertension, the risk probability of stroke would increase continuously. Multivariate Cox regression analysis showed that male patients, patients with HBP, abnormal BMI and positive family history were main factors closely related to the occurrence of stroke complications.
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29
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Wang H, Yang M, Cheng S, Ren Y, Deng Y, Liang J, Lin X, Li J, Yin J, Wu Q. The Spouses of Stroke Patients Have a Similar Oral Microbiome to Their Partners with an Elevated Risk of Stroke. Microorganisms 2022; 10:2288. [PMID: 36422358 PMCID: PMC9697374 DOI: 10.3390/microorganisms10112288] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 11/09/2022] [Accepted: 11/16/2022] [Indexed: 01/19/2024] Open
Abstract
Spousal members who share no genetic relatedness show similar oral microbiomes. Whether a shared microbiome increases the risk of cerebrovascular disease is challenging to investigate. The aim of this study was to compare the oral microbiota composition of poststroke patients, their partners, and controls and to compare the risk of stroke between partners of poststroke patients and controls. Forty-seven pairs of spouses and 34 control subjects were recruited for the study. Alcohol use, smoking, metabolic disease history, clinical test results, and oral health were documented. Oral microbiome samples were measured by 16S rRNA gene sequencing. The risk of stroke was measured by risk factor assessment (RFA) and the Framingham Stroke Profile (FSP). Poststroke patients and their partners exhibited higher alpha diversity than controls. Principal-coordinate analysis (PCoA) showed that poststroke patients share a more similar microbiota composition with their partners than controls. The differentially abundant microbial taxa among the 3 groups were identified by linear discriminant analysis effect size (LEfSe) analysis. The risk factor assessment indicated that partners of poststroke patients had a higher risk of stroke than controls. Spearman correlation analysis showed that Prevotellaceae was negatively associated with RFA. Lactobacillales was negatively associated with FSP, while Campilobacterota and [Eubacterium]_nodatum_group were positively associated with FSP. These results suggest that stroke risk may be transmissible between spouses through the oral microbiome, in which several bacteria might be involved in the pathogenesis of stroke.
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Affiliation(s)
- Huidi Wang
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
- Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Mengjia Yang
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Sanping Cheng
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Yueran Ren
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Yiting Deng
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Jingru Liang
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Xiaofei Lin
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Jie Li
- Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Jia Yin
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Qiheng Wu
- Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
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Wang Y, Huang Y, Li S, Lin J, Liu Y, Gao Y, Zhao J. The value of circulating lymphocytic subpopulations in the diagnosis and repair of ischemic stroke patients with dizziness. Front Aging Neurosci 2022; 14:1042123. [PMID: 36408111 PMCID: PMC9670111 DOI: 10.3389/fnagi.2022.1042123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 10/13/2022] [Indexed: 11/06/2022] Open
Abstract
Background To determine whether dizziness can contribute to stroke as a main cause still remains challenging. This study aims to explore clinical biomarkers in the identification of ischemic stroke patients from people with dizziness and the prediction of their long-term recovery. Methods From January 2018 to June 2019, 21 ischemic stroke patients with a main complaint of dizziness, 84 non-stroke dizziness patients and 87 healthy volunteers were recruited in this study. Then, their peripheral blood samples were collected, and the percentages of circulating lymphocytes T cells, CD4+ T cells, CD8+ T cells, T−/− cells (DNTs), CD4+ regulatory T cells (Tregs), CD8+ Tregs, B cells and regulatory B cells (Bregs) were examined to identify biomarkers with clinical value. Results According to our data, a significant difference in the DNTs proportion was detected between non-stroke dizziness and ischemic stroke patients with dizziness (p = 0.0009). The Bregs proportion in ischemic stroke patients with dizziness was lower than that in non-stroke dizziness patients (p = 0.035). In addition, the percentage of Bregs and DNTs within lymphocytes in patients’ peripheral blood exhibited a significant negative correlation with stroke occurrence (Bregs, p = 0.039; DNTs, p = 0.046). Moreover, the Bregs and DNTs within lymphocytes were negatively related to participants’ age, while presented a weak relationship with clinical risks like smoking, hypertension, and diabetes. Then, area under the receiver operating characteristic curve (AUC) of Bregs and DNTs together was 0.768, the risk factors and Bregs or DNTs ranged from 0.795 and 0.792, respectively, and the AUC value of risk factors, Bregs and DNTs combination was further increased to 0.815. Furthermore, the Bregs percentage within lymphocytes at admission was also a potential predictor of repair at discharge and the following 3 months. Conclusion Bregs and DNTs could be the clinical biomarkers together in the identification of ischemic stroke patients from people with dizziness.
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Affiliation(s)
- Yong Wang
- Department of Neurology, Minhang Hospital, Fudan University, Shanghai, China
| | - Yichen Huang
- State Key Laboratory of Medical Neurobiology, MOE Frontier Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Sicheng Li
- State Key Laboratory of Medical Neurobiology, MOE Frontier Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Jixian Lin
- Department of Neurology, Minhang Hospital, Fudan University, Shanghai, China
| | - Yang Liu
- Department of Neurology, Minhang Hospital, Fudan University, Shanghai, China
| | - Yanqin Gao
- State Key Laboratory of Medical Neurobiology, MOE Frontier Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
- *Correspondence: Yanqin Gao,
| | - Jing Zhao
- Department of Neurology, Minhang Hospital, Fudan University, Shanghai, China
- Jing Zhao,
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31
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Cao M, Guan T, Tong M, Li J, Lu H, Yang X, Wang R, Liu H, Chao B, Liu Y, Xue T. Greenspace exposure and poststroke disability: A nationwide longitudinal study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 246:114195. [PMID: 36265403 DOI: 10.1016/j.ecoenv.2022.114195] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 10/12/2022] [Accepted: 10/13/2022] [Indexed: 06/16/2023]
Abstract
INTRODUCTION Exposure to greenspace has been reported to reduce stroke mortality, but there is a lack of evidence regarding poststroke disability. This study aimed to investigate the association between long-term greenspace exposure and the risk of poststroke disability. METHODS Based on the China National Stroke Screening Survey from 2013 to 2019, a total of 65,892 visits from 28,085 stroke survivors with ≥ 2 visits were included in this longitudinal study. Long-term greenspace exposure was assessed by a 3-year average of the Normalized Difference Vegetation Index (NDVI) and the proportion of green land cover according to participants' residential communities. Poststroke functional status was assessed with the modified Ranking Score (mRS) at each visit; a cutoff score > 2 indicated disability. Fixed effects regressions were used to examine the association of greenspace exposure with continuous mRS scores or binary indicators for disability. RESULTS The annual mean NDVI value was 0.369 (standard deviation = 0.120) for all visits among stroke survivors. With full adjustments, each 0.05 increase in NDVI was associated with a 0.056-unit (95 % confidence interval (CI): 0.034, 0.079) decrease in the mRS score and a 46.6 % (95 % CI: 10.0 %, 68.3 %) lower risk of poststroke disability. An L-shaped curve was observed for the nonlinear associations between NDVI and mRS score or disability. Additionally, each 1 % increase in grasslands, savannas, forest, and croplands was associated with 0.008- (95 % CI: 0.002, 0.014), 0.003- (95 % CI: 0.001, 0.005), 0.001- (95 % CI: -0.015, 0.018), and 0.002-unit (95 % CI: -0.003, 0.007) decreases in the mRS score, respectively. CONCLUSIONS Increasing greenspace was inversely associated with mRS score. Greenspace planning can be a potential intervention to prevent poststroke disability.
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Affiliation(s)
- Man Cao
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Tianjia Guan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Mingkun Tong
- Institute of Reproductive and Child Health / National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jiajianghui Li
- Institute of Reproductive and Child Health / National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Hong Lu
- Institute of Reproductive and Child Health / National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Xinyue Yang
- College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Ruohan Wang
- Institute of Reproductive and Child Health / National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Hengyi Liu
- Institute of Reproductive and Child Health / National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Baohua Chao
- The General Office of Stroke Prevention Project Committee, National Health Commission of the People's Republic of China, Beijing, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
| | - Tao Xue
- Institute of Reproductive and Child Health / National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
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Tu WJ, Hua Y, Yan F, Bian H, Yang Y, Lou M, Kang D, He L, Chu L, Zeng J, Wu J, Chen H, Han J, Ma L, Cao L, Wang L. Prevalence of stroke in China, 2013-2019: A population-based study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 28:100550. [PMID: 36507089 PMCID: PMC9727498 DOI: 10.1016/j.lanwpc.2022.100550] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background The stroke burden in China has increased during the past 40 years. The present study aimed to determine the recent trends in the prevalence of stroke from 2013 to 2019 stratified by sociodemographic characteristics, including sex, age, residence, ethnicity, and province within a population-based screening project in China. Methods We made use of data generated from 2013 to 2019 in the China Stroke High-risk Population Screening Program. All living subjects with confirmed stroke at interview were considered to have prevalent stroke. All analyses of prevalence of stroke were weighted and results were presented as percentage and 95% confidence interval (CI). Findings A total of 4229,616 Chinese adults aged ≥40 years from 227 cities in the 31 provinces were finally included. The enrollment rate ranged from 58.8% (2017) to 67.8% (2013). The weighted prevalence of stroke increased annually from 2013 to 2019, being 2.28% (95% CI: 2.28-2.28%) in 2013, 2.34% (2.34-2.35%) in 2014, 2.43% (2.43-2.43%) in 2015, 2.48% (2.48-2.48%) in 2016, 2.52% (2.52-2.52%) in 2017, 2.55% (2.55-2.55%) in 2018, and 2.58% (2.58-2.58%) in 2019 (p for trend <0.001). The weighted prevalence of stroke was higher for male sex, older age, and residence in rural and northeast areas. Interpretation The prevalence of stroke in China and most provinces has continued to increase in the past 7 years (2013-2019). These findings, especially in provinces with high stroke prevalence, can help public health officials to increase province capacity for stroke and related risk factors prevention. Fundings This study was supported by grants from the National Major Public Health Service Projects.
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Affiliation(s)
- Wen-Jun Tu
- The General Office of Stroke Prevention Project Committee, National Health Commission of the People's Republic of China, Beijing, China
- Institute of Radiation Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Yang Hua
- Department of Ultrasound Vascular, Xuanwu Hospital Capital Medical University, Beijing, China
| | - Feng Yan
- Department of Neurosurgery, Capital Medical University Xuanwu Hospital, Beijing, China
| | - Hetao Bian
- The General Office of Stroke Prevention Project Committee, National Health Commission of the People's Republic of China, Beijing, China
| | - Yi Yang
- Department of Neurology, the First Bethune Hospital of Jilin University, Changchun, China
| | - Min Lou
- Department of Neurology, the Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Dezhi Kang
- Department of Neurosurgery, the First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Li He
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, China
| | - Lan Chu
- Department of Neurology, the Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Jingsheng Zeng
- Department of Neurology, the First Affiliated Hospital of Sun Yat–sen University, Guangzhou, China
| | - Jian Wu
- Department of Neurology, Beijing Tsinghua Changgung Memoria Hospital, Beijing, China
| | - Huisheng Chen
- Department of Neurology, The General Hospital of Northern Theater Command of the Chinese People's Liberation Army, Shenyang, China
| | - Jianfeng Han
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Lin Ma
- Department of Interventional Radiology, Shanghai Tongji Hospital, Tongji University School of Medicine, Shanghai, China
| | - Lei Cao
- The General Office of Stroke Prevention Project Committee, National Health Commission of the People's Republic of China, Beijing, China
| | - Longde Wang
- The General Office of Stroke Prevention Project Committee, National Health Commission of the People's Republic of China, Beijing, China
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Song W, Qiu L, Qing J, Zhi W, Zha Z, Hu X, Qin Z, Gong H, Li Y. Using Bayesian network model with MMHC algorithm to detect risk factors for stroke. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:13660-13674. [PMID: 36654062 DOI: 10.3934/mbe.2022637] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Stroke is a major chronic non-communicable disease with high incidence, high mortality, and high recurrence. To comprehensively digest its risk factors and take some relevant measures to lower its prevalence is of great significance. This study aimed to employ Bayesian Network (BN) model with Max-Min Hill-Climbing (MMHC) algorithm to explore the risk factors for stroke. From April 2019 to November 2019, Shanxi Provincial People's Hospital conducted opportunistic screening for stroke in ten rural areas in Shanxi Province. First, we employed propensity score matching (PSM) for class balancing for stroke. Afterwards, we used Chi-square testing and Logistic regression model to conduct a preliminary analysis of risk factors for stroke. Statistically significant variables were incorporated into BN model construction. BN structure learning was achieved using MMHC algorithm, and its parameter learning was achieved with Maximum Likelihood Estimation. After PSM, 748 non-stroke cases and 748 stroke cases were included in this study. BN was built with 10 nodes and 12 directed edges. The results suggested that age, fasting plasma glucose, systolic blood pressure, and family history of stroke constitute direct risk factors for stroke, whereas sex, educational levels, high density lipoprotein cholesterol, diastolic blood pressure, and urinary albumin-to-creatinine ratio represent indirect risk factors for stroke. BN model with MMHC algorithm not only allows for a complicated network relationship between risk factors and stroke, but also could achieve stroke risk prediction through Bayesian reasoning, outshining traditional Logistic regression model. This study suggests that BN model boasts great prospects in risk factor detection for stroke.
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Affiliation(s)
- Wenzhu Song
- School of Public Health, Shanxi Medical University, Taiyuan, China
| | - Lixia Qiu
- School of Public Health, Shanxi Medical University, Taiyuan, China
| | - Jianbo Qing
- Department of Nephrology, Shanxi Provincial People's Hospital (Fifth Hospital) of Shanxi Medical University, Taiyuan, China
| | - Wenqiang Zhi
- Department of Nephrology, Shanxi Provincial People's Hospital (Fifth Hospital) of Shanxi Medical University, Taiyuan, China
| | - Zhijian Zha
- Chinese Internal Medicine, Shanxi University of Chinese Medicine, Taiyuan, China
| | - Xueli Hu
- School of Public Health, Shanxi Medical University, Taiyuan, China
| | - Zhiqi Qin
- Department of Biochemistry & Molecular Biology, Shanxi Medical University, Taiyuan, China
| | - Hao Gong
- Department of Biochemistry & Molecular Biology, Shanxi Medical University, Taiyuan, China
| | - Yafeng Li
- Department of Nephrology, Shanxi Provincial People's Hospital (Fifth Hospital) of Shanxi Medical University, Taiyuan, China
- Core Laboratory, Shanxi Provincial People's Hospital (Fifth Hospital) of Shanxi Medical University, Taiyuan, China
- Shanxi Provincial Key Laboratory of Kidney Disease, Taiyuan, China
- Academy of Microbial Ecology, Shanxi Medical University, Taiyuan, China
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Sun X, Yan AF, Shi Z, Zhao B, Yan N, Li K, Gao L, Xue H, Peng W, Cheskin LJ, Wang Y. Health consequences of obesity and projected future obesity health burden in China. Obesity (Silver Spring) 2022; 30:1724-1751. [PMID: 36000246 DOI: 10.1002/oby.23472] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 03/20/2022] [Accepted: 03/22/2022] [Indexed: 11/07/2022]
Abstract
OBJECTIVE This study examined the effects of overweight/obesity on mortality and morbidity outcomes and the disparities, time trends, and projected future obesity health burden in China. METHODS Cohort studies that were conducted in China and published in English or Chinese between January 1, 1995, and July 31, 2021, were systematically searched. This study focused on overweight/obesity, type 2 diabetes mellitus (T2DM), hypertension, cardiovascular diseases, metabolic syndrome, cancers, and chronic kidney disease. RESULTS A total of 31 cohorts and 50 cohort studies reporting on mortality (n = 20) and morbidities (n = 30) associated with obesity met study inclusion criteria. Overall, BMI was nonlinearly (U-shaped) associated with all-cause mortality and linearly associated with risks of T2DM, cardiovascular diseases, hypertension, cancer, metabolic syndrome, and chronic kidney disease. In 2018, among adults, the prevalence of overweight/obesity, hypertension, and T2DM was 51.2%, 27.5%, and 12.4%, respectively. Their future projected prevalence would be 70.5%, 35.4%, and 18.5% in 2030, respectively. The projected number of adults having these conditions would be 810.65 million, 416.47 million, and 217.64 million, respectively. The urban-rural disparity in overweight/obesity prevalence was projected to shrink and then reverse over time. CONCLUSIONS The current health burden of obesity in China is high and it will sharply increase in coming years and affect population groups differently. China needs to implement vigorous interventions for obesity prevention and treatment.
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Affiliation(s)
- Xiaomin Sun
- Global Health Institute, School of Public Health, Xi'an Jiaotong University, Xi'an, China
| | - Alice Fang Yan
- Center for Advancing Population Science, Division of Internal Medicine, Department of Medicine, Medical College of Wisconsin, Wauwatosa, Wisconsin, USA
| | - Zumin Shi
- Human Nutrition Department, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Bingtong Zhao
- Global Health Institute, School of Public Health, Xi'an Jiaotong University, Xi'an, China
| | - Na Yan
- Global Health Institute, School of Public Health, Xi'an Jiaotong University, Xi'an, China
| | - Ke Li
- Global Health Institute, School of Public Health, Xi'an Jiaotong University, Xi'an, China
| | - Liwang Gao
- Center for Non-communicable Disease Management, Beijing Children's Hospital, National Center for Children's Health, Capital Medical University, Beijing, China
| | - Hong Xue
- Department of Health Administration and Policy, College of Health and Human Services, George Mason University, Fairfax, Virginia, USA
| | - Wen Peng
- Nutrition and Health Promotion Center, Department of Public Health, Medical College, Qinghai University and Global Health Institute, Xi'an Jiaotong University, Xi'an, China
| | - Lawrence J Cheskin
- Department of Nutrition and Food Studies, College of Health and Human Services, George Mason University, Fairfax, Virginia, USA
- Department of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Youfa Wang
- Global Health Institute, School of Public Health, Xi'an Jiaotong University, Xi'an, China
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Long-Term Exposure to Ozone Increases Neurological Disability after Stroke: Findings from a Nationwide Longitudinal Study in China. BIOLOGY 2022; 11:biology11081216. [PMID: 36009843 PMCID: PMC9404899 DOI: 10.3390/biology11081216] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 08/05/2022] [Accepted: 08/10/2022] [Indexed: 11/17/2022]
Abstract
Simple Summary In China, ozone is a major air pollutant that has been linked to stroke incidence and mortality. However, how long-term exposure to ozone affects the life quality among stroke survivors is unknown. This study presents a longitudinal analysis of nationwide data of Chinese adults, and shows that exposure to ozone can increase the risk of post-stroke disability. Taking ambient O3 under control can delay the progression of neurological disability among stroke survivors. Abstract Exposure to ozone (O3) is associated with stroke incidence and mortality. However, whether long-term exposure to O3 is associated with post-stroke neurological disability remains unknown. This study investigated the relationship based on the longitudinal analysis of China National Stroke Screening Survey (CNSSS), which included 65,778 records of stroke patients. All of the analyzed patients were followed-up at least twice. Stroke disability was assessed using the modified Rankin scale (mRS). Long-term exposure was assessed by the peak-season or annual mean of maximum 8-h O3 concentrations for 365 days before the mRS measurement. We used fixed-effect models to evaluate the associations between O3 and mRS score, with adjustment for multiple confounders, and found a 10 µg/m3 increase in peak-season O3 concentration was associated with a 0.0186 (95% confidence interval [CI] 0.0115–0.0256) increment in the mRS score. The association was robust in various subpopulations. For secondary outcomes, for each 10 µg/m3 increment in peak-season O3, the odds ratio of an increased mRS score (vs. unchanged or decreased mRS score) increased by 23% (95% CI 9–37%). A nonlinear analysis showed a sublinear association between O3 exposure and risk for post-stroke disability. A saturation effect was observed at an O3 concentration of more than ~120 μg/m3. Our study adds to evidence that long-term exposure to O3 increases the risk of neurological disability after stroke.
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Hu J, Zheng X, Shi G, Guo L. Associations of multiple chronic disease and depressive symptoms with incident stroke among Chinese middle-aged and elderly adults: a nationwide population-based cohort study. BMC Geriatr 2022; 22:660. [PMID: 35953770 PMCID: PMC9373457 DOI: 10.1186/s12877-022-03329-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 07/18/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND With the population aging, multiple chronic diseases, depressive symptoms, and stroke are increasingly common among middle-aged and elderly adults worldwide. This study aimed to explore the independent associations of multiple chronic diseases and depressive symptoms as well as their combination with incident stroke in a prospective cohort of Chinese middle-aged and elderly adults, and to sensitively estimate the association between each type of chronic disease and incident stroke. METHODS This study used data from the China Health and Retirement Longitudinal Study (CHARLS). A total of 8389 participants meeting the inclusion criteria at baseline (between 2011 and 2012) survey were included, and 7108 eligible participants completed the follow-up survey over 8 years (Wave 4, in 2018). Questionnaire information, physical examination, and clinical and biochemical measurements were collected. RESULTS The mean (SD) age at baseline was 58.5 (± 9.1) years. Multiple chronic disease and depressive symptoms were independently associated with incident stroke. After adjusting for control variables, patients having 1 type of chronic disease and depressive symptoms were at 1.943 (95% CI = 1.166-3.238) times higher risk of incident stroke than those without chronic disease and depressive symptoms, and patients having at least 2 types of chronic diseases and depressive symptoms were at 3.000 (95% CI = 1.846-4.877) times higher risk of incident stroke; the magnitudes of the associations increased by the numbers of having chronic diseases and depressive symptoms. Sensitivity analyses incorporating all five types of chronic disease (i.e., hypertension, dyslipidemia, heart disease, diabetes, and chronic kidney disease) showed that the magnitude of the associations between hypertension and incident stroke was most significant. CONCLUSIONS We identified significant independent and combined longitudinal associations of multiple chronic diseases and depressive symptoms with incident stroke, and the combined associations reflected a dose-response relationship. The association between hypertension and incident stroke was strongest among the five chronic diseases.
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Affiliation(s)
- Jingyang Hu
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
| | - Xinyu Zheng
- Cerebrovascular Disease Department, Zhuhai People's Hospital Medical Group, 519000, Zhuhai, People's Republic of China
| | - Guangduoji Shi
- Cerebrovascular Disease Department, Zhuhai People's Hospital Medical Group, 519000, Zhuhai, People's Republic of China
| | - Lan Guo
- Cerebrovascular Disease Department, Zhuhai People's Hospital Medical Group, 519000, Zhuhai, People's Republic of China.
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Chen J, Yang Y, Yu N, Sun W, Yang Y, Zhao M. Relationship between gut microbiome characteristics and the effect of nutritional therapy on glycemic control in pregnant women with gestational diabetes mellitus. PLoS One 2022; 17:e0267045. [PMID: 35427393 PMCID: PMC9012359 DOI: 10.1371/journal.pone.0267045] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 03/31/2022] [Indexed: 12/15/2022] Open
Abstract
The purpose of this study was to explore the relationship between the characteristics of gut microbiome and the effect of medical nutrition therapy (MNT) on glycemic control in pregnant women with gestational diabetes mellitus (GDM). Seventy-four pregnant women newly diagnosed with GDM received MNT for one-week. The effect of glycemic control was evaluated by fasting and 2-hour postprandial blood glucose; and stool samples of pregnant women were collected to detect the gut microbiome before and after MNT. We used a nested case-control study design, with pregnant women with GDM who did not meet glycemic standards after MNT as the ineffective group and those with an age difference of ≤5 years, matched for pre-pregnancy body mass index (BMI) 1:1, and meeting glycemic control criteria as the effective group. Comparison of the gut microbiome characteristics before MNT showed that the ineffective group was enriched in Desulfovibrio, Aeromonadales, Leuconostocaceae, Weissella, Prevotella, Bacillales_Incertae Sedis XI, Gemella and Bacillales, while the effective group was enriched in Roseburia, Clostridium, Bifidobacterium, Bifidobacteriales, Bifidobacteriaceae, Holdemania and Proteus. After treatment, the effective group was enriched in Bifidobacterium and Actinomycete, while the ineffective group was enriched in Holdemania, Proteus, Carnobacteriaceae and Granulicatella. In conclusion, the decrease in the abundance of characteristic gut microbiome positively correlated with blood glucose may be a factor influencing the poor hypoglycemic effect of MNT in pregnant women with GDM. Abundance of more characteristic gut microbiome negatively correlated with blood glucose could help control blood glucose in pregnant women with GDM.
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Affiliation(s)
- Jing Chen
- School of Nursing, Anhui Medical University, Hefei, Anhui Province, The people’s Republic of China
| | - Yuying Yang
- Division of Life Sciences and Medicine, Department of Nursing, Hefei Ion Medical Center, The First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui Province, The people’s Republic of China
| | - Ningning Yu
- School of Nursing, Anhui Medical University, Hefei, Anhui Province, The people’s Republic of China
| | - Wanxiao Sun
- School of Nursing, Anhui Medical University, Hefei, Anhui Province, The people’s Republic of China
| | - Yuanyuan Yang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, The people’s Republic of China
| | - Mei Zhao
- School of Nursing, Anhui Medical University, Hefei, Anhui Province, The people’s Republic of China
- * E-mail:
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Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, Boehme AK, Buxton AE, Carson AP, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Ferguson JF, Generoso G, Ho JE, Kalani R, Khan SS, Kissela BM, Knutson KL, Levine DA, Lewis TT, Liu J, Loop MS, Ma J, Mussolino ME, Navaneethan SD, Perak AM, Poudel R, Rezk-Hanna M, Roth GA, Schroeder EB, Shah SH, Thacker EL, VanWagner LB, Virani SS, Voecks JH, Wang NY, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation 2022; 145:e153-e639. [PMID: 35078371 DOI: 10.1161/cir.0000000000001052] [Citation(s) in RCA: 2577] [Impact Index Per Article: 1288.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Chang WW, Fei SZ, Pan N, Yao YS, Jin YL. Incident Stroke and Its Influencing Factors in Patients With Type 2 Diabetes Mellitus and/or Hypertension: A Prospective Cohort Study. Front Cardiovasc Med 2022; 9:770025. [PMID: 35224030 PMCID: PMC8863944 DOI: 10.3389/fcvm.2022.770025] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 01/03/2022] [Indexed: 11/13/2022] Open
Abstract
Objective To understand the incidence of stroke in patients with type 2 diabetes mellitus (T2DM) and/or hypertension (HTN), and provide a basis for the prevention of stroke in these patients. Methods A prospective cohort study was performed for adults with T2DM and/or HTN. The follow-up period was 1 year. The incidence and recurrence rate of stroke was calculated and a multivariate Cox proportional hazard was used to analyze influencing factors of stroke occurrence and recurrence in the follow-up of patients with T2DM and/or HTN. Results Of the 1,650 patients with T2DM and/or HTN, 1,213 patients had no history of stroke. After 1 year of follow-up, 147 new stroke cases occurred, and the incidence rate of stroke was 12.1%. Among the patients who had stroke history (413), there were 116 cases of stroke with a recurrence rate of 26.5%. Seven risk factors were independently associated with stroke occurrence among patients without stroke history, included smoking, abnormal total cholesterol abnormal low-density lipoprotein patients with comorbid T2DM with HTN, physical inactivity, carotid artery stenosis (CAS), and higher scores of National Institutes of Health Stroke Scale (NIHSS). Higher scores of NHISS and CAS were independent risk factors for the recurrence of stroke among patients with stroke history. Conclusions Patients with T2DM and/or HTN have a higher rate of new stroke and recurrence after 1-year follow-up. Actively identifying the controllable risk factors, such as smoking and physical inactivity, will help reduce the risk of stroke and recurrence in patients with T2DM and HTN.
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Affiliation(s)
- Wei-Wei Chang
- Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, Wuhu, China
| | - Shi-Zao Fei
- Department of Neurology, The Second People's Hospital, Wuhu, China
| | - Na Pan
- The Fifth People's Hospital of Wuhu City (Wannan Rehabilitation Hospital), Wuhu, China
| | - Ying-Shui Yao
- Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, Wuhu, China
- Anhui College of Traditional Chinese Medicine, Wuhu, China
- Ying-Shui Yao
| | - Yue-Long Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, Wuhu, China
- *Correspondence: Yue-Long Jin
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Tang X, Zhang L, Li Y, Zhou Y, Cai X, Yao Y, Fang Q. Relationship between triglyceride-glucose index and carotid plaques in a high-stroke-risk population in southeast china: A population-based cross-sectional survey. Front Endocrinol (Lausanne) 2022; 13:1023867. [PMID: 36313776 PMCID: PMC9596760 DOI: 10.3389/fendo.2022.1023867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 09/20/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Cervical arterial atherosclerosis (CAA) is an important risk factor of stroke in China. The triglyceride-glucose (TyG) index is a simple and low-cost marker for ischemic stroke. Whether the TyG index predicts cervical arterial atherosclerosis remains uncertain. This study aimed to investigate the relationship between the TyG index and cervical arterial atherosclerosis. METHODS This cross-sectional study was conducted in residents aged ≥40 years in the general population of southeast China. All participants completed a detailed questionnaire and provided blood samples. The high-stroke-risk groups further completed cervical artery ultrasonography. The TyG index was calculated using a well-established formula and analyzed in quartiles (Q1-Q4). Multivariate logistic regression was used to investigate the relationship between the TyG index and cervical arterial atherosclerosis. RESULTS A total of 4,499 participants aged ≥40 years were finally included, with 23.47% comprising the high-stroke-risk population. The prevalence rates of increased intima-media thickness (IMT), carotid plaque, and cervical artery stenosis (CAS) in the high-stroke-risk population were 21.97%, 39.3%, and 6.1%, respectively. Subjects with higher TyG were still more likely to have carotid plaque. After adjusting for several established risk factors, compared with the TyG-Q1 group, the TyG-Q2, TyG-Q3, and TyG-Q4 groups were more likely to have carotid plaque (OR = 1.85, 95%CI = 1.28-2.67; OR = 1.51, 95%CI = 1.05-2.18; and OR = 1.29, 95%CI = 0.90-1.84). TyG was an independent predictor of the presence of plaque in the carotid artery of the high-stroke-risk population. CONCLUSIONS An elevated TyG index is a potential predictor of carotid plaques in the high-stroke-risk population older than 40 years.
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Affiliation(s)
- Xiang Tang
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, China
| | - Lulu Zhang
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yidan Li
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yun Zhou
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiuying Cai
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, China
| | - Ye Yao
- Department of Biostatistics, School of Public Health, Fudan University, China and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- *Correspondence: Ye Yao, ; Qi Fang,
| | - Qi Fang
- Department of Neurology, First Affiliated Hospital of Soochow University, Suzhou, China
- *Correspondence: Ye Yao, ; Qi Fang,
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Lu Y, Sun W, Shen Z, Sun W, Liu R, Li F, Shu J, Tai L, Li G, Chen H, Zhang G, Zhang L, Sun X, Qiu J, Wei Y, Jin H, Huang Y. Regional Differences in Hospital Costs of Acute Ischemic Stroke in China: Analysis of Data From the Chinese Acute Ischemic Stroke Treatment Outcome Registry. Front Public Health 2021; 9:783242. [PMID: 34957035 PMCID: PMC8702643 DOI: 10.3389/fpubh.2021.783242] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 11/15/2021] [Indexed: 11/13/2022] Open
Abstract
Background and Purpose: Studies on the regional differences in hospital costs of acute ischemic stroke (AIS) are scarce in China. We aimed to explore the regional differences in hospital costs and identify the determinants of hospital costs in each region. Methods: Data were collected from the Chinese Acute Ischemic Stroke Treatment Outcome Registry (CASTOR), a multicenter prospective study on patients diagnosed with AIS and hospitalized from 2015 to 2017. Univariate and multivariate analyses were undertaken to identify the determinants of hospital costs of AIS. Results: A total of 8,547 patients were included in the study, of whom 3,700 were from the eastern area, 2,534 were from the northeastern area, 1,819 were from the central area, and 494 were from the western area. The median hospital costs presented a significant difference among each region, which were 2175.9, 2175.1, 2477.7, and 2282.4 dollars in each area, respectively. Each region showed a similar hospital cost proportion size order of cost components, which was Western medicine costs, other costs, diagnostic costs, and traditional medicine costs, in descending order. Male sex, diabetes mellitus, severe stroke symptoms, longer length of stay, admission to the intensive care unit, in-hospital complications of hemorrhage, and thrombectomy were independently associated with hospital costs in most regions. Conclusion: Hospital costs in different regions showed a similar proportion size order of components in China. Each region had different determinants of hospital costs, which reflected its current medical conditions and provided potential determinants for increasing medical efficiency according to each region's situation.
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Affiliation(s)
- Yuxuan Lu
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Weiping Sun
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Zhiyuan Shen
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Wei Sun
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Ran Liu
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Fan Li
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Junlong Shu
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Liwen Tai
- Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Guozhong Li
- Department of Neurology, First Affiliated Hospital of Harbin Medical University, Neurology, Harbin, China
| | - Huisheng Chen
- Department of Neurology, The General Hospital of Shenyang Military Command, Shenyang, China
| | - Guiru Zhang
- Department of Neurology, Penglai People's Hospital, Penglai, China
| | - Lei Zhang
- Department of Neurology, Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
| | - Xuwen Sun
- Department of Neurology, Qingdao University Medical College Affiliated Yantai Yuhuangding Hospital, Yantai, China
| | - Jinhua Qiu
- Department of Neurology, Huizhou First Hospital, Huizhou, China
| | - Yan Wei
- Department of Neurology, Harrison International Peace Hospital, Hengshui, China
| | - Haiqiang Jin
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Yining Huang
- Department of Neurology, Peking University First Hospital, Beijing, China
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Yao H, Zhang J, Wang Y, Wang Q, Zhao F, Zhang P. Stroke risk and its association with quality of life: a cross-sectional study among Chinese urban adults. Health Qual Life Outcomes 2021; 19:236. [PMID: 34627278 PMCID: PMC8501711 DOI: 10.1186/s12955-021-01868-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/20/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Stroke is a leading cause of mortality and disability worldwide. Most stroke risk studies focused on more established biological and pathophysiological risk factors such as hypertension and smoking, psychosocial factors such as quality of life are often under-investigated and thus less reported. The current study aims to estimate stroke risk and explore the impact of quality of life on stroke risk among a community sample of urban residents in Shanghai. METHODS This cross-sectional study was conducted in Fengxian District of Shanghai City from December 2018 to April 2019. 4030 representative participants were recruited through a multistage, stratified, probability proportional to size sampling method and completed the study. Stroke risk was assessed using the Rapid Stroke Risk Screening Chart that included 8 risk factors for stroke. Quality of life was measured using the World Health Organization Quality of Life-brief version (WHOQOL-BREF). RESULTS One-third of residents were at risk for stroke, including 14.39% at high risk, and 18.68% at middle risk. The top three most commonly reported risk factors were physical inactivity (37.30%), hypertension (25.38%), and smoking (17.32%). Quality of life and its four domains were all independently and significantly associated with stroke risk. Multinominal logistic regressions showed that a one-unit increase in the quality of life was associated with a decreased relative risk for middle-risk relative to low-risk of stroke by a factor of 0.988 (95% CI:0.979, 0.997, P = 0.007), and a decreased relative risk for high-risk relative to low-risk of stroke by a factor of 0.975 (95% CI:0.966, 0.984, P < 0.001). CONCLUSIONS Our findings showed an alarmingly high prevalence of stroke risk among the sample, which may require future intervention programs to focus on improving both biological and behavioral risk factors such as increasing physical activity, early diagnosis and treatment of hypertension, and smoking cessation, as well as improving psychosocial factors such as quality of life.
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Affiliation(s)
- Huiqing Yao
- Clinical Trial Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Science, Beijing Key Laboratory of Drug Clinical Risk and Personalized Medication Evaluation, Beijing, 100730, People's Republic of China
| | - Juhua Zhang
- Fudan University, Shanghai, 200433, People's Republic of China.,Shanghai Pudong Health Development Research Institute, Shanghai, 200129, People's Republic of China.,Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, 201318, People's Republic of China
| | - Yanmei Wang
- Department of Nursing, Shanghai Gongli Hospital, Second Military Medical University, Shanghai, 200135, People's Republic of China
| | - Qingqing Wang
- Clinical Trial Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Science, Beijing Key Laboratory of Drug Clinical Risk and Personalized Medication Evaluation, Beijing, 100730, People's Republic of China
| | - Fei Zhao
- Clinical Trial Center, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Science, Beijing Key Laboratory of Drug Clinical Risk and Personalized Medication Evaluation, Beijing, 100730, People's Republic of China.
| | - Peng Zhang
- Department of Neurology, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, 201800, People's Republic of China. .,School of Clinical Medicine, Shanghai University of Medicine & Health Sciences, Shanghai, 201318, People's Republic of China.
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Shiozawa M, Kaneko H, Itoh H, Morita K, Okada A, Matsuoka S, Kiriyama H, Kamon T, Fujiu K, Michihata N, Jo T, Takeda N, Morita H, Nakamura S, Node K, Yasunaga H, Komuro I. Association of Body Mass Index with Ischemic and Hemorrhagic Stroke. Nutrients 2021; 13:nu13072343. [PMID: 34371853 PMCID: PMC8308685 DOI: 10.3390/nu13072343] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Revised: 06/28/2021] [Accepted: 06/29/2021] [Indexed: 01/22/2023] Open
Abstract
Data on the association between body mass index (BMI) and stroke are scarce. We aimed to examine the association between BMI and incident stroke (ischemic or hemorrhagic) and to clarify the relationship between underweight, overweight, and obesity and stroke risk stratified by sex. We analyzed the JMDC Claims Database between January 2005 and April 2020 including 2,740,778 healthy individuals (Median (interquartile) age, 45 (38-53) years; 56.2% men; median (interquartile) BMI, 22.3 (20.2-24.8) kg/m2). None of the participants had a history of cardiovascular disease. Each participant was categorized as underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5-24.9 kg/m2), overweight (BMI 25.0-29.9 kg/m2), or obese (BMI ≥ 30 kg/m2). We investigated the association of BMI with incidence stroke in men and women using the Cox regression model. We used restricted cubic spline (RCS) functions to identify the association of BMI as a continuous parameter with incident stroke. The incidence (95% confidence interval) of total stroke, ischemic stroke, and hemorrhagic stroke was 32.5 (32.0-32.9), 28.1 (27.6-28.5), and 5.5 (5.3-5.7) per 10,000 person-years in men, whereas 25.7 (25.1-26.2), 22.5 (22.0-23.0), and 4.0 (3.8-4.2) per 10,000 person-years in women, respectively. Multivariable Cox regression analysis showed that overweight and obesity were associated with a higher incidence of total and ischemic stroke in both men and women. Underweight, overweight, and obesity were associated with a higher hemorrhagic stroke incidence in men, but not in women. Restricted cubic spline showed that the risk of ischemic stroke increased in a BMI dose-dependent manner in both men and women, whereas there was a U-shaped relationship between BMI and the hemorrhagic stroke risk in men. In conclusion, overweight and obesity were associated with a greater incidence of stroke and ischemic stroke in both men and women. Furthermore, underweight, overweight, and obesity were associated with a higher hemorrhagic stroke risk in men. Our results would help in the risk stratification of future stroke based on BMI.
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Affiliation(s)
- Masahiro Shiozawa
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo 113-8655, Japan; (M.S.); (H.I.); (S.M.); (H.K.); (T.K.); (K.F.); (N.T.); (H.M.); (I.K.)
| | - Hidehiro Kaneko
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo 113-8655, Japan; (M.S.); (H.I.); (S.M.); (H.K.); (T.K.); (K.F.); (N.T.); (H.M.); (I.K.)
- The Department of Advanced Cardiology, The University of Tokyo, Tokyo 113-8655, Japan
- Correspondence: or ; Tel.: +81-33815-5411; Fax: +81-35800-9171
| | - Hidetaka Itoh
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo 113-8655, Japan; (M.S.); (H.I.); (S.M.); (H.K.); (T.K.); (K.F.); (N.T.); (H.M.); (I.K.)
| | - Kojiro Morita
- Global Nursing Research Center, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan;
| | - Akira Okada
- Department of Prevention of Diabetes and Lifestyle-Related Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan;
| | - Satoshi Matsuoka
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo 113-8655, Japan; (M.S.); (H.I.); (S.M.); (H.K.); (T.K.); (K.F.); (N.T.); (H.M.); (I.K.)
- The Department of Cardiology, New Tokyo Hospital, Matsudo 270-2232, Japan;
| | - Hiroyuki Kiriyama
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo 113-8655, Japan; (M.S.); (H.I.); (S.M.); (H.K.); (T.K.); (K.F.); (N.T.); (H.M.); (I.K.)
| | - Tatsuya Kamon
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo 113-8655, Japan; (M.S.); (H.I.); (S.M.); (H.K.); (T.K.); (K.F.); (N.T.); (H.M.); (I.K.)
| | - Katsuhito Fujiu
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo 113-8655, Japan; (M.S.); (H.I.); (S.M.); (H.K.); (T.K.); (K.F.); (N.T.); (H.M.); (I.K.)
- The Department of Advanced Cardiology, The University of Tokyo, Tokyo 113-8655, Japan
| | - Nobuaki Michihata
- The Department of Health Services Research, The University of Tokyo, Tokyo 113-0033, Japan; (N.M.); (T.J.)
| | - Taisuke Jo
- The Department of Health Services Research, The University of Tokyo, Tokyo 113-0033, Japan; (N.M.); (T.J.)
| | - Norifumi Takeda
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo 113-8655, Japan; (M.S.); (H.I.); (S.M.); (H.K.); (T.K.); (K.F.); (N.T.); (H.M.); (I.K.)
| | - Hiroyuki Morita
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo 113-8655, Japan; (M.S.); (H.I.); (S.M.); (H.K.); (T.K.); (K.F.); (N.T.); (H.M.); (I.K.)
| | - Sunao Nakamura
- The Department of Cardiology, New Tokyo Hospital, Matsudo 270-2232, Japan;
| | - Koichi Node
- Department of Cardiovascular Medicine, Saga University, Saga 849-8501, Japan;
| | - Hideo Yasunaga
- The Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, Tokyo 113-0033, Japan;
| | - Issei Komuro
- The Department of Cardiovascular Medicine, The University of Tokyo, Tokyo 113-8655, Japan; (M.S.); (H.I.); (S.M.); (H.K.); (T.K.); (K.F.); (N.T.); (H.M.); (I.K.)
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Qi W, Ma J, Guan T, Zhao D, Abu‐Hanna A, Schut M, Chao B, Wang L, Liu Y. Risk Factors for Incident Stroke and Its Subtypes in China: A Prospective Study. J Am Heart Assoc 2020; 9:e016352. [PMID: 33103569 PMCID: PMC7763402 DOI: 10.1161/jaha.120.016352] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Background Managing risk factors is crucial to prevent stroke. However, few cohort studies have evaluated socioeconomic factors together with conventional factors affecting incident stroke and its subtypes in China. Methods and Results A 2014 to 2016 prospective study from the China National Stroke Screening and Intervention Program comprised 437 318 adults aged ≥40 years without stroke at baseline. There were 2429 cases of first‐ever stroke during a median follow‐up period of 2.1 years, including 2206 ischemic strokes and 237 hemorrhagic strokes. The multivariable Cox regression analysis indicated that age 50 to 59 years (versus 40–49 years), primary school or no formal education (versus middle school), having >1 child (versus 1 child), living in Northeast, Central, East, or North China (versus Southwest China), physical inactivity, hypertension, diabetes mellitus, and obesity were positively associated with the risk of total and ischemic stroke, whereas age 60 to 69 years and living with spouse or children (versus living alone) were negatively associated with the risk of total and ischemic stroke. Men, vegetable‐based diet, underweight, physical inactivity, hypertension, living in a high‐income region, having Urban Resident Basic Medical Insurance, and New Rural Cooperative Medical System were positively associated with the risk of hemorrhagic stroke, whereas age 60 to 69 years was negatively associated with the risk of hemorrhagic stroke. Conclusions We identified socioeconomic factors that complement traditional risk factors for incident stroke and its subtypes, allowing targeting these factors to reduce stroke burden.
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Affiliation(s)
- Wenwei Qi
- School of Health Policy and ManagementChinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
- Tianjin Institute of CardiologySecond Hospital of Tianjin Medical UniversityTianjinChina
- Department of Medical InformaticsAmsterdam UMCAmsterdamThe Netherlands
| | - Jing Ma
- Brigham & Women’s HospitalHarvard Medical SchoolBostonMA
| | - Tianjia Guan
- School of Health Policy and ManagementChinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
| | - Dongsheng Zhao
- Information CenterAcademy of Military Medical SciencesBeijingChina
| | - Ameen Abu‐Hanna
- Department of Medical InformaticsAmsterdam UMCAmsterdamThe Netherlands
| | - Martijn Schut
- Department of Medical InformaticsAmsterdam UMCAmsterdamThe Netherlands
| | - Baohua Chao
- National Health Commission of the People’s Republic of ChinaBeijingChina
| | - Longde Wang
- School of Public HealthPeking University Health Science CenterBeijingPeople’s Republic of China
| | - Yuanli Liu
- School of Health Policy and ManagementChinese Academy of Medical Sciences & Peking Union Medical CollegeBeijingChina
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