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You FF, Zhong WF, Gao YN, Shen D, Li ZH, Ren JJ, Gao J, Wang XM, Song WQ, Li C, Chen H, Xie JH, Yan HY, Mao C. Age-specific in the relationship between diastolic blood pressure and the risk of cardiovascular disease: A cohort study of the UK Biobank. Exp Gerontol 2024; 198:112635. [PMID: 39549888 DOI: 10.1016/j.exger.2024.112635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 08/30/2024] [Accepted: 11/13/2024] [Indexed: 11/18/2024]
Abstract
AIMS To investigate the effect of optimal diastolic blood pressure (DBP) level on cardiovascular disease (CVD) events, considering different age groups. And the nonlinear relationship between DBP and CVD events by age were evaluated. METHODS 358,734 participants of the UK biobank were included. Multivariable Cox regressions were performed to evaluate the relation between DBP and cardiovascular risk, and the natural cubic spline was applied to estimate the nonlinear relationship between the DBP measures and the hazard. RESULTS In the UK Biobank, a total of 358,734 participants (mean [SD] age, 55.3 [8.1] years; 205,215 [57.2 %] female) were included in this analysis. The rate of CVD cases was 6.05 per 1000 person-years. For each SD increase, DBP was associated with elevated CVD events for both <50 year (HR, 1.19; 95 % CI, 1.12 to 1.26) and 50-59 year-old group (HR, 1.04; 95 % CI, 1.01 to 1.08). However, for every SD increment, a marginal protective effect against CVD events was observed between DBP and the CVD events in elder people (≥60 years old) and lower DBP (<70 mm Hg) may confer an increased CVD risks (HR, 1.10; 95 % CI, 1.03 to 1.17). CONCLUSIONS For adults younger than 60 years old, the study seems to support the ACC/AHA blood pressure guidelines lowering the DBP threshold to 80 mm Hg. Conversely, it may be reasonable to rule out large effects of high DBP on CVD events and DBP <70 mm Hg may be cause for caution in older people aged 60-69.
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Affiliation(s)
- Fang-Fei You
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Wen-Fang Zhong
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Yi-Ning Gao
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Dong Shen
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Zhi-Hao Li
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Jiao-Jiao Ren
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Jian Gao
- Department of Laboratory Medicine, Microbiome Medicine Center, Zhujiang Hospital, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Xiao-Meng Wang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Wei-Qi Song
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Chuan Li
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Huan Chen
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Jia-Hao Xie
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Hao-Yu Yan
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Chen Mao
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China, National Institute of Health Data Science of China, Southern Medical University, Guangzhou, Guangdong, China.
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2
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Bhak Y, Tenesa A. Mendelian randomization study of whole blood viscosity and cardiovascular diseases. PLoS One 2024; 19:e0294095. [PMID: 38669241 PMCID: PMC11051600 DOI: 10.1371/journal.pone.0294095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/04/2024] [Indexed: 04/28/2024] Open
Abstract
AIMS Association between whole blood viscosity (WBV) and an increased risk of cardiovascular disease (CVD) has been reported. However, the causal relationship between WBV and CVD remains not thoroughly investigated. The aim of this study was to investigate the causal relation between WBV and CVD. METHODS Two-sample Mendelian randomization (MR) was employed, with inverse variance weighting (IVW) as the primary method, to investigate the casual relationship between WBV and CVD. The calculated WBV and medical records of 378,210 individuals participating in the UK Biobank study were divided into halves and analyzed. RESULTS The means of calculated WBVs were 16.9 (standard deviation: 0.8) and 55.1 (standard deviation: 17.2) for high shear rate (HSR) and low shear rate (LSR), respectively. 37,859 (10.0%) major cardiovascular events (MACE) consisted of 23,894 (6.3%) cases of myocardial infarction (MI), 9,245 (2.4%) cases of ischemic stroke, 10,377 (2.7%) cases of revascularization, and 5,703 (1.5%) cases of coronary heart disease-related death. In the MR analysis, no evidence was found indicating a causal effect of WBV on MACE (IVW p-value for HSR = 0.81, IVW p-value for LSR = 0.47), MI (0.92, 0.83), ischemic stroke (0.52, 0.74), revascularization (0.71, 0.54), and coronary heart disease-related death (0.83, 0.70). The lack of sufficient evidence for causality persisted in other MR methods, including weighted median and MR-egger. CONCLUSIONS The Mendelian randomization analysis conducted in this study does not support a causal relationship between calculated WBV and CVD.
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Affiliation(s)
- Youngjune Bhak
- MRC Human Genetics Unit at the MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Albert Tenesa
- MRC Human Genetics Unit at the MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, United Kingdom
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3
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Øvretveit K, Ingeström EML, Spitieris M, Tragante V, Wade KH, Thomas LF, Wolford BN, Wisløff U, Gudbjartsson DF, Holm H, Stefansson K, Brumpton BM, Hveem K. Polygenic risk scores associate with blood pressure traits across the lifespan. Eur J Prev Cardiol 2024; 31:644-654. [PMID: 38007706 PMCID: PMC11025038 DOI: 10.1093/eurjpc/zwad365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 10/18/2023] [Accepted: 11/02/2023] [Indexed: 11/28/2023]
Abstract
AIMS Hypertension is a major modifiable cause of morbidity and mortality that affects over 1 billion people worldwide. Blood pressure (BP) traits have a strong genetic component that can be quantified with polygenic risk scores (PRSs). To date, the performance of BP PRSs has mainly been assessed in adults, and less is known about polygenic hypertension risk in childhood. METHODS AND RESULTS Multiple PRSs for systolic BP (SBP), diastolic BP (DBP), and pulse pressure were developed using either genome-wide significant weights, pruning and thresholding, or Bayesian regression. Among 87 total PRSs, the top performer for each trait was applied in independent cohorts of children and adult to assess genotype-phenotype associations and disease risk across the lifespan. Differences between those with low (1st decile), average (2nd-9th decile), and high (10th decile) PRS emerge in the first years of life and are maintained throughout adulthood. These diverging BP trajectories also seem to affect cardiovascular and renal disease risk, with increased risk observed among those in the top decile and reduced risk among those in the bottom decile of the polygenic risk distribution compared with the rest of the population. CONCLUSION Genetic risk factors are associated with BP traits across the lifespan, beginning in the first years of life. Given the importance of exposure time in disease pathogenesis and the early rise in BP levels among those genetically susceptible, PRSs may help identify high-risk individuals prior to hypertension onset, facilitate primordial prevention, and reduce the burden of this public health challenge.
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Affiliation(s)
- Karsten Øvretveit
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
| | - Emma M L Ingeström
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Michail Spitieris
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
- Department of Mathematical Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | | | - Kaitlin H Wade
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 1TH, UK
- Population Health Science, Bristol Medical School, Bristol BS8 1TH, UK
- Avon Longitudinal Study of Parents and Children, Bristol BS8 1TH, UK
| | - Laurent F Thomas
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Brooke N Wolford
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
| | - Ulrik Wisløff
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Ben M Brumpton
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Kristian Hveem
- K.G. Jebsen Centre for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, N-7491 Trondheim, Norway
- Department of Innovation and Research, St. Olavs Hospital, Trondheim, Norway
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Li C, Liu X, Shen P, Sun Y, Zhou T, Chen W, Chen Q, Lin H, Tang X, Gao P. Improving cardiovascular risk prediction through machine learning modelling of irregularly repeated electronic health records. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2024; 5:30-40. [PMID: 38264696 PMCID: PMC10802828 DOI: 10.1093/ehjdh/ztad058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/03/2023] [Accepted: 09/19/2023] [Indexed: 01/25/2024]
Abstract
Aims Existing electronic health records (EHRs) often consist of abundant but irregular longitudinal measurements of risk factors. In this study, we aim to leverage such data to improve the risk prediction of atherosclerotic cardiovascular disease (ASCVD) by applying machine learning (ML) algorithms, which can allow automatic screening of the population. Methods and results A total of 215 744 Chinese adults aged between 40 and 79 without a history of cardiovascular disease were included (6081 cases) from an EHR-based longitudinal cohort study. To allow interpretability of the model, the predictors of demographic characteristics, medication treatment, and repeatedly measured records of lipids, glycaemia, obesity, blood pressure, and renal function were used. The primary outcome was ASCVD, defined as non-fatal acute myocardial infarction, coronary heart disease death, or fatal and non-fatal stroke. The eXtreme Gradient boosting (XGBoost) algorithm and Least Absolute Shrinkage and Selection Operator (LASSO) regression models were derived to predict the 5-year ASCVD risk. In the validation set, compared with the refitted Chinese guideline-recommended Cox model (i.e. the China-PAR), the XGBoost model had a significantly higher C-statistic of 0.792, (the differences in the C-statistics: 0.011, 0.006-0.017, P < 0.001), with similar results reported for LASSO regression (the differences in the C-statistics: 0.008, 0.005-0.011, P < 0.001). The XGBoost model demonstrated the best calibration performance (men: Dx = 0.598, P = 0.75; women: Dx = 1.867, P = 0.08). Moreover, the risk distribution of the ML algorithms differed from that of the conventional model. The net reclassification improvement rates of XGBoost and LASSO over the Cox model were 3.9% (1.4-6.4%) and 2.8% (0.7-4.9%), respectively. Conclusion Machine learning algorithms with irregular, repeated real-world data could improve cardiovascular risk prediction. They demonstrated significantly better performance for reclassification to identify the high-risk population correctly.
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Affiliation(s)
- Chaiquan Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
| | - Xiaofei Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
| | - Peng Shen
- Yinzhou District Center for Disease Control and Prevention, No. 1221 Xueshi Road, Yinzhou District, 315199 Ningbo, China
| | - Yexiang Sun
- Yinzhou District Center for Disease Control and Prevention, No. 1221 Xueshi Road, Yinzhou District, 315199 Ningbo, China
| | - Tianjing Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
| | - Weiye Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
| | - Qi Chen
- Yinzhou District Center for Disease Control and Prevention, No. 1221 Xueshi Road, Yinzhou District, 315199 Ningbo, China
| | - Hongbo Lin
- Yinzhou District Center for Disease Control and Prevention, No. 1221 Xueshi Road, Yinzhou District, 315199 Ningbo, China
| | - Xun Tang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
| | - Pei Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
- Center for Real-world Evidence Evaluation, Peking University Clinical Research Institute, No. 38 Xueyuan Road, Haidian District, 100191 Beijing, China
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5
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Georgiou AN, Zagkos L, Markozannes G, Chalitsios CV, Asimakopoulos AG, Xu W, Wang L, Mesa‐Eguiagaray I, Zhou X, Loizidou EM, Kretsavos N, Theodoratou E, Gill D, Burgess S, Evangelou E, Tsilidis KK, Tzoulaki I. Appraising the Causal Role of Risk Factors in Coronary Artery Disease and Stroke: A Systematic Review of Mendelian Randomization Studies. J Am Heart Assoc 2023; 12:e029040. [PMID: 37804188 PMCID: PMC7615320 DOI: 10.1161/jaha.122.029040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 06/27/2023] [Indexed: 10/09/2023]
Abstract
BACKGROUND Mendelian randomization (MR) offers a powerful approach to study potential causal associations between exposures and health outcomes by using genetic variants associated with an exposure as instrumental variables. In this systematic review, we aimed to summarize previous MR studies and to evaluate the evidence for causality for a broad range of exposures in relation to coronary artery disease and stroke. METHODS AND RESULTS MR studies investigating the association of any genetically predicted exposure with coronary artery disease or stroke were identified. Studies were classified into 4 categories built on the significance of the main MR analysis results and its concordance with sensitivity analyses, namely, robust, probable, suggestive, and insufficient. Studies reporting associations that did not perform any sensitivity analysis were classified as nonevaluable. We identified 2725 associations eligible for evaluation, examining 535 distinct exposures. Of them, 141 were classified as robust, 353 as probable, 110 as suggestive, and 926 had insufficient evidence. The most robust associations were observed for anthropometric traits, lipids, and lipoproteins and type 2 diabetes with coronary artery; disease and clinical measurements with coronary artery disease and stroke; and thrombotic factors with stroke. CONCLUSIONS Despite the large number of studies that have been conducted, only a limited number of associations were supported by robust evidence. Approximately half of the studies reporting associations presented an MR sensitivity analysis along with the main analysis that further supported the causality of associations. Future research should focus on more thorough assessments of sensitivity MR analyses and further assessments of mediation effects or nonlinearity of associations.
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Affiliation(s)
- Andrea N. Georgiou
- Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
| | - Loukas Zagkos
- Department of Epidemiology and BiostatisticsSchool of Public Health, Imperial College LondonLondonUK
| | - Georgios Markozannes
- Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
- Department of Epidemiology and BiostatisticsSchool of Public Health, Imperial College LondonLondonUK
| | - Christos V. Chalitsios
- Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
| | | | - Wei Xu
- Centre for Global Health, Usher InstituteThe University of EdinburghEdinburghUK
| | - Lijuan Wang
- Centre for Global Health, Usher InstituteThe University of EdinburghEdinburghUK
| | | | - Xuan Zhou
- Centre for Global Health, Usher InstituteThe University of EdinburghEdinburghUK
| | - Eleni M. Loizidou
- Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
- Biobank Cyprus Center of Excellence in Biobanking and Biomedical ResearchUniversity of CyprusNicosiaCyprus
| | - Nikolaos Kretsavos
- Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
| | - Evropi Theodoratou
- Centre for Global Health, Usher InstituteThe University of EdinburghEdinburghUK
- Cancer Research UK Edinburgh Centre, Institute of Genetics and CancerThe University of EdinburghEdinburghUK
| | - Dipender Gill
- Department of Epidemiology and BiostatisticsSchool of Public Health, Imperial College LondonLondonUK
- Medical Research Council Biostatistics UnitUniversity of CambridgeCambridgeUK
| | - Stephen Burgess
- Medical Research Council Biostatistics UnitUniversity of CambridgeCambridgeUK
- Cardiovascular Epidemiology UnitUniversity of CambridgeCambridgeUK
| | - Evangelos Evangelou
- Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
- Department of Epidemiology and BiostatisticsSchool of Public Health, Imperial College LondonLondonUK
- Department of Biomedical Research, Institute of Molecular Biology and BiotechnologyFoundation for Research and Technology‐HellasIoanninaGreece
| | - Konstantinos K. Tsilidis
- Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
- Department of Epidemiology and BiostatisticsSchool of Public Health, Imperial College LondonLondonUK
| | - Ioanna Tzoulaki
- Department of Epidemiology and BiostatisticsSchool of Public Health, Imperial College LondonLondonUK
- Centre for Systems Biology, Biomedical Research FoundationAcademy of AthensAthensGreece
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Schooling CM, Zhao JV. Insights into Causal Cardiovascular Risk Factors from Mendelian Randomization. Curr Cardiol Rep 2023; 25:67-76. [PMID: 36640254 DOI: 10.1007/s11886-022-01829-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/07/2022] [Indexed: 01/15/2023]
Abstract
PURPOSE OF THE REVIEW This review summarizes major insights into causal risk factors for cardiovascular disease (CVD) by using Mendelian randomization (MR) to obtain unconfounded estimates, contextualized within its strengths and weaknesses. RECENT FINDINGS MR studies have confirmed the role of major CVD risk factors, including alcohol, smoking, adiposity, blood pressure, type 2 diabetes, lipids, and possibly inflammation, but added that the relation with alcohol is likely linear, confirmed the role of diastolic blood pressure, identified apolipoprotein B as the major target lipid, and foreshadowed results of some trials concerning anti-inflammatories. Identifying a healthy diet and the role of early life influences, such as birth weight, has proved more difficult. Use of MR has winnowed empirically driven hypotheses about CVD into a set of genetically validated targets of intervention. Greater inclusion of global diversity in genetic studies and the use of an overarching framework would enable even more informative MR studies.
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Affiliation(s)
- C M Schooling
- School of Public Health and Health Policy, City University of New York, 55 West 125th St, NY, 10027, New York, USA. .,School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
| | - J V Zhao
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
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7
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Lauffenburger JC, Khatib R, Siddiqi A, Albert MA, Keller PA, Samal L, Glowacki N, Everett ME, Hanken K, Lee SG, Bhatkhande G, Haff N, Sears ES, Choudhry NK. Reducing ethnic and racial disparities by improving undertreatment, control, and engagement in blood pressure management with health information technology (REDUCE-BP) hybrid effectiveness-implementation pragmatic trial: Rationale and design. Am Heart J 2023; 255:12-21. [PMID: 36220355 PMCID: PMC9742137 DOI: 10.1016/j.ahj.2022.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 09/29/2022] [Accepted: 10/01/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND While racial/ethnic disparities in blood pressure control are documented, few interventions have successfully reduced these gaps. Under-prescribing, lack of treatment intensification, and suboptimal follow-up care are thought to be central contributors. Electronic health record (EHR) tools may help address these barriers and may be enhanced with behavioral science techniques. OBJECTIVE To evaluate the impact of a multicomponent behaviorally-informed EHR-based intervention on blood pressure control. TRIAL DESIGN Reducing Ethnic and racial Disparities by improving Undertreatment, Control, and Engagement in Blood Pressure management with health information technology (REDUCE-BP) (NCT05030467) is a two-arm cluster-randomized hybrid type 1 pragmatic trial in a large multi-ethnic health care system. Twenty-four clinics (>350 primary care providers [PCPs] and >10,000 eligible patients) are assigned to either multi-component EHR-based intervention or usual care. Intervention clinic PCPs will receive several EHR tools designed to reduce disparities delivered at different points, including a: (1) dashboard of all patients visible upon logging on to the EHR displaying blood pressure control by race/ethnicity compared to their PCP peers and (2) set of tools in an individual patient's chart containing decision support to encourage treatment intensification, ordering home blood pressure measurement, interventions to address health-related social needs, default text for note documentation, and enhanced patient education materials. The primary outcome is patient-level change in systolic blood pressure over 12 months between arms; secondary outcomes include changes in disparities and other clinical outcomes. CONCLUSION REDUCE-BP will provide important insights into whether an EHR-based intervention designed using behavioral science can improve hypertension control and reduce disparities.
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Affiliation(s)
- Julie C Lauffenburger
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
| | - Rasha Khatib
- Advocate Aurora Research Institute, Advocate Aurora Health, Downers Grove, IL
| | - Alvia Siddiqi
- Enterprise Population Health, Advocate Aurora Health, Downers Grove, IL
| | - Michelle A Albert
- Center for the Study of Adversity and Cardiovascular Disease (NURTURE Center), Division of Cardiology of Medicine (Cardiology), University of California, San Francisco, San Francisco, CA
| | | | - Lipika Samal
- Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Nicole Glowacki
- Advocate Aurora Research Institute, Advocate Aurora Health, Downers Grove, IL
| | | | - Kaitlin Hanken
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Simin G Lee
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Gauri Bhatkhande
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Nancy Haff
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Ellen S Sears
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Niteesh K Choudhry
- Center for Healthcare Delivery Sciences (C4HDS), Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
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8
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Laukkanen JA, Jae SY, Kauhanen J, Kunutsor SK. The Interplay between Systolic Blood Pressure, Sauna Bathing, and Cardiovascular Mortality in Middle-Aged and Older Finnish Men: A Cohort Study. J Nutr Health Aging 2023; 27:348-353. [PMID: 37248758 DOI: 10.1007/s12603-023-1895-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 02/25/2023] [Indexed: 05/31/2023]
Abstract
OBJECTIVES Elevated systolic blood pressure (SBP) is associated with an increased risk of cardiovascular disease (CVD) mortality, whereas frequent sauna bathing reduces the risk. Whether frequent sauna bathing mitigates CVD mortality among adults with elevated SBP has not been previously investigated. DESIGN AND SETTING We examined the interactions between SBP and frequency of sauna bathing (FSB) with the risk of CVD mortality in a cohort of Caucasian men. PARTICIPANTS The Kuopio Ischaemic Heart Disease Study cohort comprising of 2,575 men aged 42-61 years at baseline was employed for this prospective study analysis. MEASUREMENTS Resting blood pressure was measured using a standardized protocol and sauna bathing habits were assessed by a self-administered questionnaire. Systolic blood pressure was categorized as normal and high (<140 and ≥140 mmHg, respectively) and FSB as low and high (defined as ≤ 2 and 3-7 sessions/week, respectively). RESULTS A total of 744 CVD deaths were recorded during a median follow-up of 27.8 yr. Comparing high vs normal SBP, the multivariable-adjusted HR (95% CI) for CVD mortality was 1.44 (1.23-1.68). Comparing low vs high FSB, the multivariable-adjusted HR (95% CI) for CVD mortality was 1.24 (1.03-1.51). The associations persisted following mutual adjustment for each exposure. Compared with men with normal SBP-high FSB, high SBP-low FSB was associated with an increased risk of CVD mortality 1.81 (1.39-2.36), with attenuated but persisting evidence of an association for men with high SBP and high FSB 1.52 (1.06-2.16). When SBP was categorized as normal and high (<130 and ≥130 mmHg, respectively), there was no evidence of an association for men with high SBP and high FSB 1.11 (0.77-1.61). CONCLUSION There might be an interaction between SBP, sauna bathing and CVD mortality risk in middle-aged and older Caucasian males. Frequent sauna baths may offset the increased risk of CVD mortality in men with high-normal SBP but not elevated SBP.
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Affiliation(s)
- J A Laukkanen
- Prof. Jari Laukkanen, Institute of Clinical Medicine, Department of Medicine, University of Eastern Finland, P.O. Box 1627, FIN-70211 Kuopio, Finland, Fax: +358-17-162936, Tel +358-50-5053013, E-mail:
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