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Bazoukis G, Loscalzo J, Hall JL, Bollepalli SC, Singh JP, Armoundas AA. Impact of Social Determinants of Health on Cardiovascular Disease. J Am Heart Assoc 2025; 14:e039031. [PMID: 40035388 DOI: 10.1161/jaha.124.039031] [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] [Indexed: 03/05/2025]
Abstract
An increasing number of studies have shown the impact of social determinants of health (SDoHs) on different cardiovascular outcomes. SDoHs influence the regional incidence of heart failure, heart failure outcomes, and heart failure readmission rates; can prevent use of advanced heart failure therapies in minorities with an indication for their use; can influence the incidence of coronary artery disease and peripheral artery disease outcomes; and can also prevent providing equal quality of care to all patients with myocardial infarction. In the setting of arrhythmias, specific SDoHs can increase the incidence of atrial fibrillation and adversely affect major outcomes in these patients. In congenital heart diseases, SDoHs can affect major outcomes, as well. In conclusion, SDoHs significantly impact cardiovascular morbidity and death and specific outcomes of patients with cardiovascular disease. Policy measures that aim to improve those SDoHs that negatively affect health outcomes hold promise for improving cardiovascular outcomes at individual and population levels.
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Affiliation(s)
- George Bazoukis
- Department of Cardiology Larnaca General Hospital Larnaca Cyprus
- European University of Cyprus Medical School Nicosia Cyprus
| | - Joseph Loscalzo
- Department of Medicine Brigham and Women's Hospital Boston MA USA
| | | | | | - Jagmeet P Singh
- Cardiology Division, Cardiac Arrhythmia Service Massachusetts General Hospital Boston MA USA
| | - Antonis A Armoundas
- Cardiovascular Research Center Massachusetts General Hospital Boston MA USA
- Broad Institute, Massachusetts Institute of Technology Cambridge MA USA
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Venkatesh KK, Grobman WA, Huang X, Yee LM, Catov J, Simhan H, Haas DM, Mercer B, Reddy U, Silver RM, Levine LD, Chung J, Saade G, Greenland P, Bairey Merz CN, McNeil B, Khan SS. Association of neighborhood-level socioeconomic disadvantage and Life's Essential 8 in early pregnancy. Am J Prev Cardiol 2025; 21:100925. [PMID: 39838971 PMCID: PMC11750432 DOI: 10.1016/j.ajpc.2024.100925] [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: 06/17/2024] [Revised: 11/13/2024] [Accepted: 12/21/2024] [Indexed: 01/23/2025] Open
Abstract
We examined whether neighborhood-level socioeconomic disadvantage per the Area Deprivation Index (ADI) was associated with maternal cardiovascular health (CVH) in early pregnancy per the American Heart Association Life's Essential 8 (LE8). This is a cross-sectional analysis from the prospective Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-Be Heart Health Study (nuMoM2b-HHS) cohort. The exposure was the ADI in tertiles (T) from least (T1) to most (T3) socioeconomic disadvantage. The outcome was the LE8 as a continuous score ranging from worst (0) to best (100) composite CVH; and included physical activity, diet quality, tobacco use, sleep quantity, body mass index, blood pressure, glucose, and lipid levels. Among 4,508 nulliparous individuals at a mean maternal age of 27.0 years (SD: 5.6) and at a mean gestational age of 11.4 weeks (SD 1.6), the mean ADI was 48.0 (SD: 30.4) and the mean LE8 was 80.3 (SD: 12.5). Pregnant individuals living in neighborhoods with greater socioeconomic disadvantage had lower mean LE8 scores (i.e., worse CVH) compared with those living in neighborhoods with lesser disadvantage (T1 vs. T2 adjusted mean: 82.6 vs. 80.5; adj. ß:2.08; 95 % CI:3.51, -0.64; and T1 vs. T3 adjusted mean: 82.6 vs. 77.8; adj. ß:4.77; 95 % CI:8.16, -1.38). Neighborhood-level socioeconomic disadvantage was associated with worse maternal CVH in early pregnancy.
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Affiliation(s)
- Kartik K. Venkatesh
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH, USA
| | - William A. Grobman
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH, USA
| | - Xiaoning Huang
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - Lynn M. Yee
- Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL, USA
| | - Janet Catov
- Department of Obstetrics and Gynecology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Hy Simhan
- Department of Obstetrics and Gynecology, University of Pittsburgh, Pittsburgh, PA, USA
| | - David M. Haas
- Department of Obstetrics and Gynecology, Indiana University, Indianapolis, IN, USA
| | - Brian Mercer
- Department of Obstetrics and Gynecology, Case Western Reserve University, Cleveland, OH, USA
| | - Uma Reddy
- Department of Obstetrics and Gynecology, Columbia University, New York, NY, USA
| | - Robert M. Silver
- Department of Obstetrics and Gynecology, University of Utah, Salt Lake City, UT, USA
| | - Lisa D. Levine
- Department of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, PA, USA
| | - Judith Chung
- Department of Obstetrics and Gynecology, University of California, Irvine, Orange, CA, USA
- RTI International, Durham, NC, USA
| | - George Saade
- Department of Obstetrics and Gynecology, Eastern Virginia Medical College, Norfolk, VA, USA
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
| | - C. Noel Bairey Merz
- Barbra Streisand Women's Heart Center, Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA, USA
| | | | - Sadiya S Khan
- Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
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3
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Martin SS, Aday AW, Allen NB, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Bansal N, Beaton AZ, Commodore-Mensah Y, Currie ME, Elkind MSV, Fan W, Generoso G, Gibbs BB, Heard DG, Hiremath S, Johansen MC, Kazi DS, Ko D, Leppert MH, Magnani JW, Michos ED, Mussolino ME, Parikh NI, Perman SM, Rezk-Hanna M, Roth GA, Shah NS, Springer MV, St-Onge MP, Thacker EL, Urbut SM, Van Spall HGC, Voeks JH, Whelton SP, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2025; 151:e41-e660. [PMID: 39866113 DOI: 10.1161/cir.0000000000001303] [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] [Indexed: 01/28/2025]
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 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update. 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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Tsukada YT, Aoki-Kamiya C, Mizuno A, Nakayama A, Ide T, Aoyama R, Honye J, Hoshina K, Ikegame T, Inoue K, Bando YK, Kataoka M, Kondo N, Maemura K, Makaya M, Masumori N, Mito A, Miyauchi M, Miyazaki A, Nakano Y, Nakao YM, Nakatsuka M, Nakayama T, Oginosawa Y, Ohba N, Otsuka M, Okaniwa H, Saito A, Saito K, Sakata Y, Harada-Shiba M, Soejima K, Takahashi S, Takahashi T, Tanaka T, Wada Y, Watanabe Y, Yano Y, Yoshida M, Yoshikawa T, Yoshimatsu J, Abe T, Dai Z, Endo A, Fukuda-Doi M, Ito-Hagiwara K, Harima A, Hirakawa K, Hosokawa K, Iizuka G, Ikeda S, Ishii N, Izawa KP, Kagiyama N, Umeda-Kameyama Y, Kanki S, Kato K, Komuro A, Konagai N, Konishi Y, Nishizaki F, Noma S, Norimatsu T, Numao Y, Oishi S, Okubo K, Ohmori T, Otaki Y, Shibata T, Shibuya J, Shimbo M, Shiomura R, Sugiyama K, Suzuki T, Tajima E, Tsukihashi A, Yasui H, Amano K, Kohsaka S, Minamino T, Nagai R, Setoguchi S, Terada K, Yumino D, Tomoike H. JCS/JCC/JACR/JATS 2024 Guideline on Cardiovascular Practice With Consideration for Diversity, Equity, and Inclusion. Circ J 2025:CJ-23-0890. [PMID: 39971310 DOI: 10.1253/circj.cj-23-0890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Affiliation(s)
| | - Chizuko Aoki-Kamiya
- Department of Obstetrics and Gynecology, National Cerebral and Cardiovascular Center
| | - Atsushi Mizuno
- Department of Cardiology, St. Luke's International Hospital
| | | | - Tomomi Ide
- Department of Cardiovascular Medicine, Kyushu University
| | - Rie Aoyama
- Department of Cardiology, Heart and Vascular Institute, Funabashi Municipal Medical Center
| | - Junko Honye
- Cardiovascular Center, Kikuna Memorial Hospital
| | | | | | - Koki Inoue
- Department of Neuropsychiatry, Graduate School of Medicine, Osaka Metropolitan University
| | - Yasuko K Bando
- Department of Molecular Physiology and Cardiovascular Biology, Mie University Graduate School of Medicine
| | - Masaharu Kataoka
- The Second Department of Internal Medicine, University of Occupational and Environmental Health, Japan
| | - Naoki Kondo
- Department of Social Epidemiology, Graduate School of Medicine and School of Public Health, Kyoto University
| | - Koji Maemura
- Department of Cardiovascular Medicine, Nagasaki University Graduate School of Biomedical Sciences
| | | | - Naoya Masumori
- Department of Urology, Sapporo Medical University School of Medicine
| | - Asako Mito
- Division of Maternal Medicine, Center for Maternal-Fetal-Reproductive Medicine, National Center for Child Health and Development
| | - Mizuho Miyauchi
- Department of Cardiovascular Medicine, Nippon Medical School
| | - Aya Miyazaki
- Department of Pediatric Cardiology, Department of Adult Congenital Heart Disease, Seirei Hamamatsu General Hospital
| | - Yukiko Nakano
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences
| | - Yoko M Nakao
- Department of Pharmacoepidemiology, Graduate School of Medicine and Public Health, Kyoto University
| | - Mikiya Nakatsuka
- Faculty of Health Sciences, Okayama University Graduate School of Medicine
| | - Takeo Nakayama
- Department of Health Informatics, School of Public Health, Kyoto University
| | - Yasushi Oginosawa
- The Second Department of Internal Medicine, University of Occupational and Environmental Health, Japan
| | | | - Maki Otsuka
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kurume University School of Medicine
| | - Hiroki Okaniwa
- Department of Technology, Gunma Prefectural Cardiovascular Center
| | - Aya Saito
- Department of Surgery, Division of Cardiovascular Surgery, Yokohama City University, Graduate School of Medicine
| | - Kozue Saito
- Department of Neurology, Stroke Center, Nara Medical University
| | - Yasushi Sakata
- Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine
| | | | - Kyoko Soejima
- Department of Cardiovascular Medicine, Kyorin University School of Medicine
| | | | - Tetsuya Takahashi
- Department of Physical Therapy, Faculty of Health Science, Juntendo University
| | - Toshihiro Tanaka
- Department of Human Genetics and Disease Diversity, Tokyo Medical and Dental University
| | - Yuko Wada
- Division of Cardiovascular Surgery, Department of Surgery, Shinshu University School of Medicine
| | | | - Yuichiro Yano
- Department of General Medicine, Juntendo University Faculty of Medicine
| | - Masayuki Yoshida
- Department of Life Sciences and Bioethics, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU)
| | - Toru Yoshikawa
- Research Center for Overwork-Related Disorders (RECORDs), National Institute of Occuatopnal Safety and Health, Japan (JNIOSH)
| | - Jun Yoshimatsu
- Department of Obstetrics and Gynecology, National Cerebral and Cardiovascular Center
| | - Takahiro Abe
- Department of Rehabilitation Medicine, Hokkaido University Hospital
| | - Zhehao Dai
- Department of Cardiovascular Medicine, The University of Tokyo Hospital
| | - Ayaka Endo
- Department of Cardiology, Tokyo Saiseikai Central Hospital
| | - Mayumi Fukuda-Doi
- Department of Data Science, National Cerebral and Cardiovascular Center
- Department of Cerebrovascular Medicine, National Cerebral and Cardiovascular Center
| | | | | | - Kyoko Hirakawa
- Department of Cardiovascular Medicine, Kumamoto University
| | | | | | - Satoshi Ikeda
- Stroke and Cardiovascular Diseases Support Center, Nagasaki University Hospital
| | - Noriko Ishii
- Department of Nursing, Sakakibara Heart Institute
| | - Kazuhiro P Izawa
- Department of Public Health, Graduate School of Health Sciences, Kobe University
| | - Nobuyuki Kagiyama
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine
| | | | - Sachiko Kanki
- Department of Thoracic and Cardiovascular Surgery, Osaka Medical and Pharmaceutical University
| | - Katsuhito Kato
- Department of Hygiene and Public Health, Nippon Medical School
| | - Aya Komuro
- Department of Geriatric Medicine, The University of Tokyo Hospital
| | - Nao Konagai
- Department of Obstetrics and Gynecology, National Cerebral and Cardiovascular Center
| | - Yuto Konishi
- Department of Cardiovascular Medicine, The University of Tokyo Hospital
| | - Fumie Nishizaki
- Department of Cardiology and Nephrology, Hirosaki University Graduate School of Medicine
| | - Satsuki Noma
- Department of Cardiovascular Medicine, Nippon Medical School
| | | | - Yoshimi Numao
- Department of Cardiology, Itabasih Chuo Medical Center
| | | | - Kimie Okubo
- Division of Cardiology, Department of Medicine, Nihon University School of Medicine Itabashi Hospital
| | | | - Yuka Otaki
- Department of Radiology, Sakakibara Heart Institute
| | | | - Junsuke Shibuya
- Division of Cardiovascular Intensive Care, Nippon Medical School Hospital
| | - Mai Shimbo
- Department of Cardiovascular Medicine, Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo
| | - Reiko Shiomura
- Division of Cardiovascular Intensive Care, Nippon Medical School Hospital
| | | | - Takahiro Suzuki
- Department of Cardiovascular Medicine, St. Luke's International Hospital
| | - Emi Tajima
- Department of Cardiology, Tokyo General Hospital
| | - Ayako Tsukihashi
- Department of Cardiovascular Medicine, The University of Tokyo Hospital
| | - Haruyo Yasui
- Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine
| | | | - Shun Kohsaka
- Department of Cardiology, Keio University School of Medicine
| | - Tohru Minamino
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine
| | | | - Soko Setoguchi
- Division of Education, Department of Medicine, Rutgers Robert Wood Johnson Medical School
- Division of Cardiovascular Disease and Hypertension, Department of Medicine, Rutgers Robert Wood Johnson Medical School
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Venkatesh KK, Khan SS, Catov J, Wu J, McNeil R, Greenland P, Wu J, Levine LD, Yee LM, Simhan HN, Haas DM, Reddy UM, Saade G, Silver RM, Merz CNB, Grobman WA. Socioeconomic disadvantage in pregnancy and postpartum risk of cardiovascular disease. Am J Obstet Gynecol 2025; 232:226.e1-226.e14. [PMID: 38759711 DOI: 10.1016/j.ajog.2024.05.007] [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: 11/28/2023] [Revised: 05/03/2024] [Accepted: 05/09/2024] [Indexed: 05/19/2024]
Abstract
BACKGROUND Pregnancy is an educable and actionable life stage to address social determinants of health (SDOH) and lifelong cardiovascular disease (CVD) prevention. However, the link between a risk score that combines multiple neighborhood-level social determinants in pregnancy and the risk of long-term CVD remains to be evaluated. OBJECTIVE To examine whether neighborhood-level socioeconomic disadvantage measured by the Area Deprivation Index (ADI) in early pregnancy is associated with a higher 30-year predicted risk of CVD postpartum, as measured by the Framingham Risk Score. STUDY DESIGN An analysis of data from the prospective Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-Be Heart Health Study longitudinal cohort. Participant home addresses during early pregnancy were geocoded at the Census-block level. The exposure was neighborhood-level socioeconomic disadvantage using the 2015 ADI by tertile (least deprived [T1], reference; most deprived [T3]) measured in the first trimester. Outcomes were the predicted 30-year risks of atherosclerotic cardiovascular disease (ASCVD, composite of fatal and nonfatal coronary heart disease and stroke) and total CVD (composite of ASCVD plus coronary insufficiency, angina pectoris, transient ischemic attack, intermittent claudication, and heart failure) using the Framingham Risk Score measured 2 to 7 years after delivery. These outcomes were assessed as continuous measures of absolute estimated risk in increments of 1%, and, secondarily, as categorical measures with high-risk defined as an estimated probability of CVD ≥10%. Multivariable linear regression and modified Poisson regression models adjusted for baseline age and individual-level social determinants, including health insurance, educational attainment, and household poverty. RESULTS Among 4309 nulliparous individuals at baseline, the median age was 27 years (interquartile range [IQR]: 23-31) and the median ADI was 43 (IQR: 22-74). At 2 to 7 years postpartum (median: 3.1 years, IQR: 2.5, 3.7), the median 30-year risk of ASCVD was 2.3% (IQR: 1.5, 3.5) and of total CVD was 5.5% (IQR: 3.7, 7.9); 2.2% and 14.3% of individuals had predicted 30-year risk ≥10%, respectively. Individuals living in the highest ADI tertile had a higher predicted risk of 30-year ASCVD % (adjusted ß: 0.41; 95% confidence interval [CI]: 0.19, 0.63) compared with those in the lowest tertile; and those living in the top 2 ADI tertiles had higher absolute risks of 30-year total CVD % (T2: adj. ß: 0.37; 95% CI: 0.03, 0.72; T3: adj. ß: 0.74; 95% CI: 0.36, 1.13). Similarly, individuals living in neighborhoods in the highest ADI tertile were more likely to have a high 30-year predicted risk of ASCVD (adjusted risk ratio [aRR]: 2.21; 95% CI: 1.21, 4.02) and total CVD ≥10% (aRR: 1.35; 95% CI: 1.08, 1.69). CONCLUSION Neighborhood-level socioeconomic disadvantage in early pregnancy was associated with a higher estimated long-term risk of CVD postpartum. Incorporating aggregated SDOH into existing clinical workflows and future research in pregnancy could reduce disparities in maternal cardiovascular health across the lifespan, and requires further study.
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Affiliation(s)
- Kartik K Venkatesh
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH.
| | - Sadiya S Khan
- Departments of Preventive Medicine and Medicine, Northwestern University, Chicago, IL
| | - Janet Catov
- Department of Obstetrics and Gynecology, University of Pittsburgh, Pittsburgh, PA
| | - Jiqiang Wu
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH
| | | | - Philip Greenland
- Departments of Preventive Medicine and Medicine, Northwestern University, Chicago, IL
| | - Jun Wu
- Department of Environmental and Occupational Health, Susan and Henry Samueli College of Health Sciences, University of California, Irvine, Orange, CA
| | - Lisa D Levine
- Department of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, PA
| | - Lynn M Yee
- Department of Obstetrics and Gynecology, Northwestern University, Chicago, IL
| | - Hyagriv N Simhan
- Department of Obstetrics and Gynecology, University of Pittsburgh, Pittsburgh, PA
| | - David M Haas
- Department of Obstetrics and Gynecology, Indiana University, Indianapolis, IN
| | - Uma M Reddy
- Department of Obstetrics and Gynecology, Columbia University, New York, NY
| | - George Saade
- Department of Obstetrics and Gynecology, Eastern Virginia Medical College, Norfolk, VA
| | - Robert M Silver
- Department of Obstetrics and Gynecology, University of Utah, Salt Lake City, UT
| | - C Noel Bairey Merz
- Barbra Streisand Women's Heart Center, Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA
| | - William A Grobman
- Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH
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Wang A, French D, Black B, Kho AN. Cohort study examining social determinants of health and their association with mortality among hospitalised adults in New York and California. BMJ PUBLIC HEALTH 2025; 3:e001266. [PMID: 40134538 PMCID: PMC11934384 DOI: 10.1136/bmjph-2024-001266] [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: 04/04/2024] [Accepted: 02/24/2025] [Indexed: 03/27/2025]
Abstract
Background Adults in the US face significant disparities in health as a result of the social determinants of health (SDOH). While the link between SDOH and mortality is well-established, their impact on outcomes after hospitalisation is less understood. Methods Among adults aged 18-84 years hospitalised in New York (NY) during the period of 2000-2009 and in California (CA) from during the period of 2000-2006, we examined the association between 1-year post-hospitalisation mortality and a community-level SDOH combined index (comprising six component domains) using Kaplan-Meier survival analysis and multivariable Cox proportional-hazard models to estimate the mortality HR (adjusted HR (aHR)) adjusted for age, gender, race, ethnicity and Charlson Comorbidity Index. We also studied subcohorts in NY and CA grouped by hospitalisation conditions (subgroups with chronic or acute disease). Results In NY, the overall 1-year mortality rate was 8.9% (9.7% for chronic diseases and 13.2% for acute diseases). In CA, the overall 1-year mortality rate was 8.3% (12.6% for chronic diseases and 15.8% for acute diseases). In both states, the 1-year risk of death was significantly lower for those in the best (Q4) SDOH (combined index) compared with the worst (Q1 is the reference category). In NY, the aHR was 0.964 (p<0.001 and 95% CI 0.950 to 0.978), while in CA, the aHR: 0.83 (p<0.001 and 95% CI 0.825 to 0.842). Similar patterns were observed for the disease cohorts in both states. The Economic and Education domains of SDOH showed stronger and more consistent associations with mortality risk compared with the domains of Neighbourhood, Food Access, Community and Social Context, and Healthcare. Conclusions This study demonstrates a significant association between worse SDOH and higher post-hospitalisation mortality. The findings emphasise the importance of community-level SDOH in patient care planning and discharge strategies to reduce health disparities.
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Affiliation(s)
- Andrew Wang
- Center for Health Services and Outcomes Research, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Center for Health Information Partnerships, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Dustin French
- Center for Health Services and Outcomes Research, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Department of Ophthalmology, Northwestern Medicine, Chicago, Illinois, USA
- Health Services Research and Development, US Department of Veterans Affairs, Hines, Illinois, USA
| | - Bernard Black
- Northwestern University Pritzker School of Law, Chicago, Illinois, USA
- Northwestern University Kellogg School of Management, Evanston, Illinois, USA
| | - Abel N Kho
- Center for Health Information Partnerships, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Institute for Augmented Intelligence in Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern Medicine, Chicago, Illinois, USA
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Rangachari P, Thapa A, Sherpa DL, Katukuri K, Ramadyani K, Jaidi HM, Goodrum L. Characteristics of hospital and health system initiatives to address social determinants of health in the United States: a scoping review of the peer-reviewed literature. Front Public Health 2024; 12:1413205. [PMID: 38873294 PMCID: PMC11173975 DOI: 10.3389/fpubh.2024.1413205] [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: 04/06/2024] [Accepted: 05/17/2024] [Indexed: 06/15/2024] Open
Abstract
Background Despite the incentives and provisions created for hospitals by the US Affordable Care Act related to value-based payment and community health needs assessments, concerns remain regarding the adequacy and distribution of hospital efforts to address SDOH. This scoping review of the peer-reviewed literature identifies the key characteristics of hospital/health system initiatives to address SDOH in the US, to gain insight into the progress and gaps. Methods PRISMA-ScR criteria were used to inform a scoping review of the literature. The article search was guided by an integrated framework of Healthy People SDOH domains and industry recommended SDOH types for hospitals. Three academic databases were searched for eligible articles from 1 January 2018 to 30 June 2023. Database searches yielded 3,027 articles, of which 70 peer-reviewed articles met the eligibility criteria for the review. Results Most articles (73%) were published during or after 2020 and 37% were based in Northeast US. More initiatives were undertaken by academic health centers (34%) compared to safety-net facilities (16%). Most (79%) were research initiatives, including clinical trials (40%). Only 34% of all initiatives used the EHR to collect SDOH data. Most initiatives (73%) addressed two or more types of SDOH, e.g., food and housing. A majority (74%) were downstream initiatives to address individual health-related social needs (HRSNs). Only 9% were upstream efforts to address community-level structural SDOH, e.g., housing investments. Most initiatives (74%) involved hot spotting to target HRSNs of high-risk patients, while 26% relied on screening and referral. Most initiatives (60%) relied on internal capacity vs. community partnerships (4%). Health disparities received limited attention (11%). Challenges included implementation issues and limited evidence on the systemic impact and cost savings from interventions. Conclusion Hospital/health system initiatives have predominantly taken the form of downstream initiatives to address HRSNs through hot-spotting or screening-and-referral. The emphasis on clinical trials coupled with lower use of EHR to collect SDOH data, limits transferability to safety-net facilities. Policymakers must create incentives for hospitals to invest in integrating SDOH data into EHR systems and harnessing community partnerships to address SDOH. Future research is needed on the systemic impact of hospital initiatives to address SDOH.
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Affiliation(s)
- Pavani Rangachari
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Alisha Thapa
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Dawa Lhomu Sherpa
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Keerthi Katukuri
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Kashyap Ramadyani
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Hiba Mohammed Jaidi
- Department of Population Health and Leadership, School of Health Sciences, University of New Haven, West Haven, CT, United States
| | - Lewis Goodrum
- Northeast Medical Group, Yale New Haven Health System, Stratford, CT, United States
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Savitz ST, Falk K, Stearns SC, Grove LR, Pathman DE, Rossi JS. Race-ethnicity and sex differences in 1-year survival following percutaneous coronary intervention among Medicare fee-for-service beneficiaries. J Eval Clin Pract 2024; 30:406-417. [PMID: 38091249 DOI: 10.1111/jep.13954] [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: 05/02/2023] [Revised: 11/25/2023] [Accepted: 11/27/2023] [Indexed: 04/18/2024]
Abstract
RATIONALE Existing literature describing differences in survival following percutaneous coronary intervention (PCI) by patient sex, race-ethnicity and the role of socioeconomic characteristics (SEC) is limited. AIMS AND OBJECTIVES Evaluate differences in 1-year survival after PCI by sex and race-ethnicity, and explore the contribution of SEC to observed differences. METHODS Using a 20% sample of Medicare claims data for beneficiaries aged 65+, we identified fee-for-service patients who received PCI from 2007 to 2015. We performed logistic regression to assess how sex and race-ethnicity relate to procedural indication, inpatient versus outpatient setting, and 1-year mortality. We evaluated whether these relationships are moderated by sequentially controlling for factors including age, comorbidities, presence of acute myocardial infarction (AMI), county SEC, medical resource availability and inpatient versus outpatient procedural status. RESULTS We identified 300,491 PCI procedures, of which 94,863 (31.6%) were outpatient. There was a significant transition to outpatient PCI during the study period, especially for men compared with women and White patients compared with Black patients. Black patients were 3.50 percentage points (p < 0.001) and women were 3.41 percentage points (p < 0.001) more likely than White and male patients to undergo PCI at the time of AMI, which typically occurs in the inpatient setting. Controlling for age and calendar year, Black patients were 2.87 percentage points more likely than non-Hispanic White patients to die within 1 year after PCI. After controlling for Black-White differences in comorbidities, the differences in 1-year mortality decreased to 0.95 percentage points, which then became nonsignificant when further controlling for county resources and state of residence. CONCLUSION Women were more likely to experience PCI in the setting of AMI and had less transition to outpatient care during the period. Black patients experienced higher 1-year mortality following PCI, which is explained by differences in baseline comorbidities, county medical resources, and state of residence.
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Affiliation(s)
- Samuel T Savitz
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Division of Health Care Delivery Research, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA
| | - Kristine Falk
- Division of Cardiology, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Sally C Stearns
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Lexie R Grove
- Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Donald E Pathman
- Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Family Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Joseph S Rossi
- Division of Cardiology, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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9
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Suzuki T, Mizuno A, Yasui H, Noma S, Ohmori T, Rewley J, Kawai F, Nakayama T, Kondo N, Tsukada YT. Scoping Review of Screening and Assessment Tools for Social Determinants of Health in the Field of Cardiovascular Disease. Circ J 2024; 88:390-407. [PMID: 38072415 DOI: 10.1253/circj.cj-23-0443] [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] [Indexed: 02/23/2024]
Abstract
BACKGROUND Despite the importance of implementing the concept of social determinants of health (SDOH) in the clinical practice of cardiovascular disease (CVD), the tools available to assess SDOH have not been systematically investigated. We conducted a scoping review for tools to assess SDOH and comprehensively evaluated how these tools could be applied in the field of CVD. METHODS AND RESULTS We conducted a systematic literature search of PubMed and Embase databases on July 25, 2023. Studies that evaluated an SDOH screening tool with CVD as an outcome or those that explicitly sampled or included participants based on their having CVD were eligible for inclusion. In addition, studies had to have focused on at least one SDOH domain defined by Healthy People 2030. After screening 1984 articles, 58 articles that evaluated 41 distinct screening tools were selected. Of the 58 articles, 39 (67.2%) targeted populations with CVD, whereas 16 (27.6%) evaluated CVD outcome in non-CVD populations. Three (5.2%) compared SDOH differences between CVD and non-CVD populations. Of 41 screening tools, 24 evaluated multiple SDOH domains and 17 evaluated only 1 domain. CONCLUSIONS Our review revealed recent interest in SDOH in the field of CVD, with many useful screening tools that can evaluate SDOH. Future studies are needed to clarify the importance of the intervention in SDOH regarding CVD.
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Affiliation(s)
- Takahiro Suzuki
- Department of Cardiovascular Medicine, St. Luke's International Hospital
| | - Atsushi Mizuno
- Department of Cardiovascular Medicine, St. Luke's International Hospital
- Leonard Davis Institute for Health Economics, University of Pennsylvania
| | - Haruyo Yasui
- Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine
| | - Satsuki Noma
- Department of Cardiovascular Medicine, Nippon Medical School
| | | | - Jeffrey Rewley
- Leonard Davis Institute for Health Economics, University of Pennsylvania
- The MITRE Corporation
| | - Fujimi Kawai
- Department of Academic Resources, St. Luke's International University
| | - Takeo Nakayama
- Department of Health Informatics, Kyoto University School of Public Health
| | - Naoki Kondo
- Department of Social Epidemiology, Graduate School of Medicine and School of Public Health, Kyoto University
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10
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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: 659] [Impact Index Per Article: 659.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [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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11
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Akioyamen LE, Abdel-Qadir H, Han L, Sud M, Mistry N, Alter DA, Atzema CL, Austin PC, Bhatia RS, Booth GL, Dhalla I, Ha ACT, Jackevicius CA, Kapral MK, Krumholz HM, Lee DS, McNaughton CD, Roifman I, Schull MJ, Sivaswamy A, Tu K, Udell JA, Wijeysundera HC, Ko DT. Association of Neighborhood-Level Marginalization With Health Care Use and Clinical Outcomes Following Hospital Discharge in Patients Who Underwent Coronary Catheterization for Acute Myocardial Infarction in a Single-Payer Health Care System. Circ Cardiovasc Qual Outcomes 2023; 16:e010063. [PMID: 38050754 DOI: 10.1161/circoutcomes.123.010063] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 10/06/2023] [Indexed: 12/06/2023]
Abstract
BACKGROUND Canadian data suggest that patients of lower socioeconomic status with acute myocardial infarction receive less beneficial therapy and have worse clinical outcomes, raising questions regarding care disparities even in universal health care systems. We assessed the contemporary association of marginalization with clinical outcomes and health services use. METHODS Using clinical and administrative databases in Ontario, Canada, we conducted a population-based study of patients aged ≥65 years hospitalized for their first acute myocardial infarction between April 1, 2010 and March 1, 2019. Patients receiving cardiac catheterization and surviving 7 days postdischarge were included. Our primary exposure was neighborhood-level marginalization, a multidimensional socioeconomic status metric. Neighborhoods were categorized by quintile from Q1 (least marginalized) to Q5 (most marginalized). Our primary outcome was all-cause mortality. A proportional hazards regression model with a robust variance estimator was used to quantify the association of marginalization with outcomes, adjusting for risk factors, comorbidities, disease severity, and regional cardiologist supply. RESULTS Among 53 841 patients (median age, 75 years; 39.1% female) from 20 640 neighborhoods, crude 1- and 3-year mortality rates were 7.7% and 17.2%, respectively. Patients in Q5 had no significant difference in 1-year mortality (hazard ratio [HR], 1.08 [95% CI, 0.95-1.22]), but greater mortality over 3 years (HR, 1.13 [95% CI, 1.03-1.22]) compared with Q1. Over 1 year, we observed differences between Q1 and Q5 in visits to primary care physicians (Q1, 96.7%; Q5, 93.7%) and cardiologists (Q1, 82.6%; Q5, 72.6%), as well as diagnostic testing. There were no differences in secondary prevention medications dispensed or medication adherence at 1 year. CONCLUSIONS In older patients with acute myocardial infarction who survived to hospital discharge, those residing in the most marginalized neighborhoods had a greater long-term risk of mortality, less specialist care, and fewer diagnostic tests. Yet, there were no differences across socioeconomic status in prescription medication use and adherence.
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Affiliation(s)
- Leo E Akioyamen
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
| | - Husam Abdel-Qadir
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- University Health Network, Toronto, ON, Canada (H.A.-Q., D.A.A., R.S.B., A.C.T.H., M.K.K., D.S.L., J.A.U.)
- Women's College Hospital, Toronto, ON, Canada (H.A.-Q., J.A.U.)
| | - Lu Han
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
| | - Maneesh Sud
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada (M.S., C.L.A., C.D.M., I.R., M.J.S., H.C.W., D.T.K.)
| | - Nikhil Mistry
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
| | - David A Alter
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- University Health Network, Toronto, ON, Canada (H.A.-Q., D.A.A., R.S.B., A.C.T.H., M.K.K., D.S.L., J.A.U.)
| | - Clare L Atzema
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada (M.S., C.L.A., C.D.M., I.R., M.J.S., H.C.W., D.T.K.)
| | - Peter C Austin
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
| | - R Sacha Bhatia
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- University Health Network, Toronto, ON, Canada (H.A.-Q., D.A.A., R.S.B., A.C.T.H., M.K.K., D.S.L., J.A.U.)
| | - Gillian L Booth
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Li Ka Shing Knowledge Institute of St Michael's Hospital, Toronto, Ontario, Canada (G.L.B., I.R.,)
| | - Irfan Dhalla
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
| | - Andrew C T Ha
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- University Health Network, Toronto, ON, Canada (H.A.-Q., D.A.A., R.S.B., A.C.T.H., M.K.K., D.S.L., J.A.U.)
| | - Cynthia A Jackevicius
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Western University of Health Sciences, Pomona, CA (C.A.J.)
| | - Moira K Kapral
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- University Health Network, Toronto, ON, Canada (H.A.-Q., D.A.A., R.S.B., A.C.T.H., M.K.K., D.S.L., J.A.U.)
| | - Harlan M Krumholz
- Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT (H.M.K.)
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT (H.M.K.)
- Department of Health Policy and Management, Yale School of Public Health, New Haven, CT (H.M.K.)
| | - Douglas S Lee
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- University Health Network, Toronto, ON, Canada (H.A.-Q., D.A.A., R.S.B., A.C.T.H., M.K.K., D.S.L., J.A.U.)
| | - Candace D McNaughton
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada (M.S., C.L.A., C.D.M., I.R., M.J.S., H.C.W., D.T.K.)
| | - Idan Roifman
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada (M.S., C.L.A., C.D.M., I.R., M.J.S., H.C.W., D.T.K.)
- Li Ka Shing Knowledge Institute of St Michael's Hospital, Toronto, Ontario, Canada (G.L.B., I.R.,)
| | - Michael J Schull
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada (M.S., C.L.A., C.D.M., I.R., M.J.S., H.C.W., D.T.K.)
| | - Atul Sivaswamy
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
| | - Karen Tu
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Department of Family and Community Medicine, (K.T.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- North York General Hospital, Toronto, ON, Canada (K.T.)
| | - Jacob A Udell
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- University Health Network, Toronto, ON, Canada (H.A.-Q., D.A.A., R.S.B., A.C.T.H., M.K.K., D.S.L., J.A.U.)
- Women's College Hospital, Toronto, ON, Canada (H.A.-Q., J.A.U.)
| | - Harindra C Wijeysundera
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada (M.S., C.L.A., C.D.M., I.R., M.J.S., H.C.W., D.T.K.)
| | - Dennis T Ko
- Department of Medicine (L.E.A., H.A.-Q., D.A.A., C.L.A., R.S.B., I.D., A.C.T.H., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation (H.A.-Q., M.S., D.A.A., C.L.A., P.C.A., G.L.B., I.D., C.A.J., M.K.K., D.S.L., I.R., M.J.S., K.T., J.A.U., H.C.W., D.T.K.), University of Toronto, ON, Canada
- ICES (formerly known as the Institute for Clinical Evaluative Sciences), Toronto, ON, Canada (H.A.-Q., L.H., M.S., N.M., D.A.A., C.L.A., P.C.A., G.L.B., C.A.J., M.K.K., D.S.L., C.D.M., I.R., M.J.S., A.S., K.T., J.A.U., H.C.W., D.T.K.)
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada (M.S., C.L.A., C.D.M., I.R., M.J.S., H.C.W., D.T.K.)
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Kontos MC, Gandhi S, Garrett KN, Davis LL, Anderson C, Wang TY, Bhatt DL. The NCDR's Chest Pain Myocardial Infarction Registry: 15 Years of Myocardial Infarction Quality Improvement. JACC. ADVANCES 2023; 2:100712. [PMID: 38938480 PMCID: PMC11198411 DOI: 10.1016/j.jacadv.2023.100712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/29/2024]
Affiliation(s)
- Michael C. Kontos
- Division of Cardiology, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Sanjay Gandhi
- Division of Cardiology, Case Western Reserve University- MetroHealth Hospital, Cleveland, Ohio, USA
| | - Kirk N. Garrett
- Division of Cardiology, ChristianaCare, Newark, Delaware, USA
| | - Leslie L. Davis
- School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Tracy Y. Wang
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, USA
- Division of Cardiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Deepak L. Bhatt
- Division of Cardiology, Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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13
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Virani SS, Newby LK, Arnold SV, Bittner V, Brewer LC, Demeter SH, Dixon DL, Fearon WF, Hess B, Johnson HM, Kazi DS, Kolte D, Kumbhani DJ, LoFaso J, Mahtta D, Mark DB, Minissian M, Navar AM, Patel AR, Piano MR, Rodriguez F, Talbot AW, Taqueti VR, Thomas RJ, van Diepen S, Wiggins B, Williams MS. 2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines. Circulation 2023; 148:e9-e119. [PMID: 37471501 DOI: 10.1161/cir.0000000000001168] [Citation(s) in RCA: 421] [Impact Index Per Article: 210.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
AIM The "2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease" provides an update to and consolidates new evidence since the "2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease" and the corresponding "2014 ACC/AHA/AATS/PCNA/SCAI/STS Focused Update of the Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease." METHODS A comprehensive literature search was conducted from September 2021 to May 2022. Clinical studies, systematic reviews and meta-analyses, and other evidence conducted on human participants were identified that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. STRUCTURE This guideline provides an evidenced-based and patient-centered approach to management of patients with chronic coronary disease, considering social determinants of health and incorporating the principles of shared decision-making and team-based care. Relevant topics include general approaches to treatment decisions, guideline-directed management and therapy to reduce symptoms and future cardiovascular events, decision-making pertaining to revascularization in patients with chronic coronary disease, recommendations for management in special populations, patient follow-up and monitoring, evidence gaps, and areas in need of future research. Where applicable, and based on availability of cost-effectiveness data, cost-value recommendations are also provided for clinicians. Many recommendations from previously published guidelines have been updated with new evidence, and new recommendations have been created when supported by published data.
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Affiliation(s)
| | | | | | | | | | | | - Dave L Dixon
- Former Joint Committee on Clinical Practice Guideline member; current member during the writing effort
| | - William F Fearon
- Society for Cardiovascular Angiography and Interventions representative
| | | | | | | | - Dhaval Kolte
- AHA/ACC Joint Committee on Clinical Data Standards
| | | | | | | | - Daniel B Mark
- Former Joint Committee on Clinical Practice Guideline member; current member during the writing effort
| | | | | | | | - Mariann R Piano
- Former Joint Committee on Clinical Practice Guideline member; current member during the writing effort
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14
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Virani SS, Newby LK, Arnold SV, Bittner V, Brewer LC, Demeter SH, Dixon DL, Fearon WF, Hess B, Johnson HM, Kazi DS, Kolte D, Kumbhani DJ, LoFaso J, Mahtta D, Mark DB, Minissian M, Navar AM, Patel AR, Piano MR, Rodriguez F, Talbot AW, Taqueti VR, Thomas RJ, van Diepen S, Wiggins B, Williams MS. 2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines. J Am Coll Cardiol 2023; 82:833-955. [PMID: 37480922 DOI: 10.1016/j.jacc.2023.04.003] [Citation(s) in RCA: 160] [Impact Index Per Article: 80.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/24/2023]
Abstract
AIM The "2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease" provides an update to and consolidates new evidence since the "2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease" and the corresponding "2014 ACC/AHA/AATS/PCNA/SCAI/STS Focused Update of the Guideline for the Diagnosis and Management of Patients With Stable Ischemic Heart Disease." METHODS A comprehensive literature search was conducted from September 2021 to May 2022. Clinical studies, systematic reviews and meta-analyses, and other evidence conducted on human participants were identified that were published in English from MEDLINE (through PubMed), EMBASE, the Cochrane Library, Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. STRUCTURE This guideline provides an evidenced-based and patient-centered approach to management of patients with chronic coronary disease, considering social determinants of health and incorporating the principles of shared decision-making and team-based care. Relevant topics include general approaches to treatment decisions, guideline-directed management and therapy to reduce symptoms and future cardiovascular events, decision-making pertaining to revascularization in patients with chronic coronary disease, recommendations for management in special populations, patient follow-up and monitoring, evidence gaps, and areas in need of future research. Where applicable, and based on availability of cost-effectiveness data, cost-value recommendations are also provided for clinicians. Many recommendations from previously published guidelines have been updated with new evidence, and new recommendations have been created when supported by published data.
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15
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Dugani SB, Zubaid M, Rashed W, Girardo ME, Balayah Z, Mora S, Alsheikh-Ali AA. Social Determinants of Health and Mortality After Premature and Non-premature Acute Coronary Syndrome. Mayo Clin Proc Innov Qual Outcomes 2023; 7:153-164. [PMID: 37152409 PMCID: PMC10160579 DOI: 10.1016/j.mayocpiqo.2023.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2023] Open
Abstract
Objective To describe and compare the determinants of 1-year mortality after premature vs non-premature acute coronary syndrome (ACS). Patients and Methods Participants presenting with ACS were enrolled in a prospective registry of 29 hospitals in 4 countries, from January 22, 2012 to January 22, 2013, with 1-year of follow-up data. The primary outcome was all-cause 1-year mortality after premature ACS (men aged <55 years and women aged <65 years) and non-premature ACS (men aged ≥55 years and women aged ≥65 years). The associations between the baseline patient characteristics and 1-year mortality were analyzed in models adjusting for the Global Registry of Acute Coronary Events (GRACE) score and reported as adjusted odds ratio (aOR) (95% CI). Results Of the 3868 patients, 43.3% presented with premature ACS that was associated with lower 1-year mortality (5.7%) than those with non-premature ACS. In adjusted models, women experienced higher mortality than men after premature (aOR, 2.14 [1.37-3.41]) vs non-premature ACS (aOR, 1.28 [0.99-1.65]) (P interaction=.047). Patients lacking formal education vs any education had higher mortality after both premature (aOR, 2.92 [1.87-4.61]) and non-premature ACS (aOR, 1.78 [1.36-2.34]) (P interaction=.06). Lack of employment vs any employment was associated with approximately 3-fold higher mortality after premature and non-premature ACS (P interaction=.72). Using stepwise logistic regression to predict 1-year mortality, a model with GRACE risk score and 4 characteristics (education, employment, body mass index [kg/m2], and statin use within 24 hours after admission) had higher discrimination than the GRACE risk score alone (area under the curve, 0.800 vs 0.773; P comparison=.003). Conclusion In this study, women, compared with men, had higher 1-year mortality after premature ACS. The social determinants of health (no formal education or employment) were strongly associated with higher 1-year mortality after premature and non-premature ACS, improved mortality prediction, and should be routinely considered in risk assessment after ACS.
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Affiliation(s)
- Sagar B. Dugani
- Division of Hospital Internal Medicine and Division of Health Care Delivery Research, Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Mohammad Zubaid
- Department of Medicine, Faculty of Medicine, Kuwait University, Kuwait
| | - Wafa Rashed
- Division of Cardiology, Mubarak Al Kabeer Hospital, Kuwait University, Kuwait
| | | | - Zuhur Balayah
- Bayes Business School, Centre for Health Care Innovation Research, University of London, UK
| | - Samia Mora
- Center for Lipid Metabolomics, Divisions of Preventive and Cardiovascular Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Alawi A. Alsheikh-Ali
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
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16
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Anand VV, Zhe ELC, Chin YH, Goh RSJ, Lin C, Kueh MTW, Chong B, Kong G, Tay PWL, Dalakoti M, Muthiah M, Dimitriadis GK, Wang JW, Mehta A, Foo R, Tse G, Figtree GA, Loh PH, Chan MY, Mamas MA, Chew NWS. Socioeconomic deprivation and prognostic outcomes in acute coronary syndrome: A meta-analysis using multidimensional socioeconomic status indices. Int J Cardiol 2023:S0167-5273(23)00597-1. [PMID: 37116760 DOI: 10.1016/j.ijcard.2023.04.042] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 02/26/2023] [Accepted: 04/23/2023] [Indexed: 04/30/2023]
Abstract
BACKGROUND Low socioeconomic status (SES) is an important prognosticator amongst patients with acute coronary syndrome (ACS). This paper analysed the effects of SES on ACS outcomes. METHODS Medline and Embase were searched for articles reporting outcomes of ACS patients stratified by SES using a multidimensional index, comprising at least 2 of the following components: Income, Education and Employment. A comparative meta-analysis was conducted using random-effects models to estimate the risk ratio of all-cause mortality in low SES vs high SES populations, stratified according to geographical region, study year, follow-up duration and SES index. RESULTS A total of 29 studies comprising of 301,340 individuals were included, of whom 43.7% were classified as low SES. While patients of both SES groups had similar cardiovascular risk profiles, ACS patients of low SES had significantly higher risk of all-cause mortality (adjusted HR:1.19, 95%CI: 1.10-1.1.29, p < 0.001) compared to patients of high SES, with higher 1-year mortality (RR:1.08, 95%CI:1.03-1.13, p = 0.0057) but not 30-day mortality (RR:1.07, 95%CI:0.98-1.16, p = 0.1003). Despite having similar rates of ST-elevation myocardial infarction and non-ST-elevation ACS, individuals with low SES had lower rates of coronary revascularisation (RR:0.95, 95%CI:0.91-0.99, p = 0.0115) and had higher cerebrovascular accident risk (RR:1.25, 95%CI:1.01-1.55, p = 0.0469). Excess mortality risk was independent of region (p = 0.2636), study year (p = 0.7271) and duration of follow-up (p = 0.0604) but was dependent on the SES index used (p < 0.0001). CONCLUSION Low SES is associated with increased mortality post-ACS, with suboptimal coronary revascularisation rates compared to those of high SES. Concerted efforts are needed to address the global ACS-related socioeconomic inequity. REGISTRATION AND PROTOCOL The current study was registered with PROSPERO, ID: CRD42022334482.
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Affiliation(s)
- Vickram Vijay Anand
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Ethan Lee Cheng Zhe
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Yip Han Chin
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Yong Loo Lin School of Medicine, National University Singapore, Singapore
| | - Rachel Sze Jen Goh
- Yong Loo Lin School of Medicine, National University Singapore, Singapore
| | - Chaoxing Lin
- Yong Loo Lin School of Medicine, National University Singapore, Singapore
| | - Martin Tze Wah Kueh
- Royal College of Surgeons in Ireland and University College Dublin Malaysia Campus, Malaysia
| | - Bryan Chong
- Yong Loo Lin School of Medicine, National University Singapore, Singapore
| | - Gwyneth Kong
- Yong Loo Lin School of Medicine, National University Singapore, Singapore
| | - Phoebe Wen Lin Tay
- Yong Loo Lin School of Medicine, National University Singapore, Singapore
| | - Mayank Dalakoti
- Yong Loo Lin School of Medicine, National University Singapore, Singapore; Department of Cardiology, National University Heart Centre, National University Health System, Singapore
| | - Mark Muthiah
- Yong Loo Lin School of Medicine, National University Singapore, Singapore; Division of Gastroenterology and Hepatology, Department of Medicine, National University Hospital, Singapore; National University Centre for Organ Transplantation, National University Health System, Singapore
| | - Georgios K Dimitriadis
- Faculty of Life Sciences and Medicine, School of Life Course Sciences, King's College London, London, UK; Department of Endocrinology ASO/EASO COM, King's College Hospital NHS Foundation Trust, Denmark Hill, London, UK
| | - Jiong-Wei Wang
- Yong Loo Lin School of Medicine, National University Singapore, Singapore; Department of Surgery, Cardiovascular Research Institute (CVRI), National University of Singapore, Singapore; Nanomedicine Translational Research Programme, Centre for NanoMedicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Anurag Mehta
- Division of Cardiology, Department of Internal Medicine, Virginia Commonwealth University Pauley Heart Centre, Richmond, VA, USA
| | - Roger Foo
- Yong Loo Lin School of Medicine, National University Singapore, Singapore; Department of Cardiology, National University Heart Centre, National University Health System, Singapore
| | - Gary Tse
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin 300211, China; Kent and Medway Medical School, Kent, Canterbury CT2 7NT, UK
| | - Gemma A Figtree
- Northern Clinical School, Kolling Institute of Medical Research, University of Sydney, Sydney, NSW, Australia; Department of Cardiology, Royal North Shore Hospital, Sydney, NSW, Australia
| | - Poay Huan Loh
- Yong Loo Lin School of Medicine, National University Singapore, Singapore; Department of Cardiology, National University Heart Centre, National University Health System, Singapore
| | - Mark Y Chan
- Yong Loo Lin School of Medicine, National University Singapore, Singapore; Department of Cardiology, National University Heart Centre, National University Health System, Singapore
| | - Mamas A Mamas
- Keele Cardiovascular Research Group, School of Medicine, Keele University, Stoke-on-Trent, UK; Institute of Population Health, University of Manchester, UK
| | - Nicholas W S Chew
- Department of Cardiology, National University Heart Centre, National University Health System, Singapore.
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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: 2115] [Impact Index Per Article: 1057.5] [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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18
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Rao VN, Mentz RJ, Coniglio AC, Kelsey MD, Fudim M, Fonarow GC, Matsouaka RA, DeVore AD, Caughey MC. Neighborhood Socioeconomic Disadvantage and Hospitalized Heart Failure Outcomes in the American Heart Association Get With The Guidelines-Heart Failure Registry. Circ Heart Fail 2022; 15:e009353. [PMID: 36378758 PMCID: PMC9673180 DOI: 10.1161/circheartfailure.121.009353] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 06/13/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Neighborhood socioeconomic status (SES) is associated with worse health outcomes, yet its relationship with in-hospital heart failure (HF) outcomes and quality metrics are underexplored. We examined the association between socioeconomic neighborhood disadvantage and in-hospital HF outcomes for patients from diverse neighborhoods in the Get With The Guidelines-Heart Failure registry. METHODS SES-disadvantage scores were derived from geocoded US census data using a validated algorithm, which incorporated household income, home value, rent, education, and employment. We examined the association between SES-disadvantage quintiles with all-cause in-hospital mortality, adjusting for demographics and comorbidities. RESULTS Of 593 053 patients hospitalized for HF between 2017 and 2020, 321 314 (54%) had residential ZIP Codes recorded. Patients from the most compared with least disadvantaged neighborhoods were younger (mean age 67 versus 76 years), more often Black (42% versus 9%) or Hispanic (14% versus 5%), and had higher comorbidity burden. Demographic-adjusted length of stay increased by ≈1.5 hours with each increment in worsening SES-disadvantage quintiles. Adjusted-mortality odds ratios increased with worsening SES-disadvantage quintiles (Ptrend=0.003), and was 28% higher (adjusted OR=1.28 [1.12-1.48]) for the most compared with least disadvantaged neighborhood groups. CONCLUSIONS Patients hospitalized for HF from disadvantaged neighborhoods were younger and more often Black or Hispanic. SES disadvantage was independently associated with higher in-hospital mortality. Further research is needed to characterize care delivery patterns in disadvantaged neighborhoods and to address social determinants of health among patients hospitalized for HF. REGISTRATION: URL: https://www. CLINICALTRIALS gov; Unique identifier: NCT02693509.
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Affiliation(s)
- Vishal N. Rao
- Division of Cardiology, Duke University Medical Center, Durham, North Carolina
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina
| | - Robert J. Mentz
- Division of Cardiology, Duke University Medical Center, Durham, North Carolina
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina
| | - Amanda C. Coniglio
- Division of Cardiology, Duke University Medical Center, Durham, North Carolina
| | - Michelle D. Kelsey
- Division of Cardiology, Duke University Medical Center, Durham, North Carolina
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina
| | - Marat Fudim
- Division of Cardiology, Duke University Medical Center, Durham, North Carolina
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina
| | - Gregg C. Fonarow
- Division of Cardiology, Department of Medicine, University of California at Los Angeles, Los Angeles, California
| | - Roland A. Matsouaka
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina
| | - Adam D. DeVore
- Division of Cardiology, Duke University Medical Center, Durham, North Carolina
- Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina
| | - Melissa C. Caughey
- Joint Department of Biomedical Engineering, University of North Carolina and North Carolina State University, Chapel Hill, North Carolina
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19
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Heindl B, Clarkson S, Parcha V, Dillon C, Narayan R, Usifo E, Hillegass W, Irvin MR, Arora P, Zhai G, Beasley M, Limdi N. Risk of Postdischarge Bleeding From Dual Antiplatelet Therapy After Percutaneous Coronary Intervention Among US Black and White Adults. J Am Heart Assoc 2022; 11:e024412. [PMID: 36073636 PMCID: PMC9683679 DOI: 10.1161/jaha.121.024412] [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: 11/25/2021] [Accepted: 07/07/2022] [Indexed: 11/16/2022]
Abstract
Background Dual antiplatelet therapy after percutaneous coronary intervention reduces myocardial infarctions but increases bleeding. The risk of bleeding may be higher among Black patients for unknown reasons. Bleeding risk scores have not been validated among Black patients. We assessed the difference in bleeding risk between Black and White patients along with the performance of the Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Anti Platelet Therapy, Patterns of Nonadherence to Antiplatelet Regimens in Stented Patients, and Academic Research Consortium for High Bleeding Risk scores among both groups. Methods and Results This was a single-center prospective study of patients who underwent percutaneous coronary intervention (2014-2019) and were followed for 1 year. The outcome was postdischarge Bleeding Academic Research Consortium 2 to 5 bleeding. Incidence rates were reported. Cox proportional hazards models measured the effect of self-reported Black race on bleeding and determined the predictors of bleeding among 19 a priori variables. The 3 risk scores were assessed among Black and White patients separately using the Harrell concordance index. Of 1529 included patients, 342 (22.4%) self-reported as being Black race. Unadjusted bleeding rates were 22.7 per 100 person-years among Black patients versus 16.3 among White patients (hazard ratio, 1.41 [95% CI, 1.00-2.00], P=0.052). Predictors of bleeding were age, glomerular filtration rate <30 mL/min per 1.73 m2, prior bleeding, ticagrelor or prasugrel use, and anticoagulant use. Among Black and White patients, respectively, the C-indexes were the following: 0.644 versus 0.600 for Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Anti Platelet Therapy (P<0.001 for both), 0.620 versus 0.612 for Patterns of Nonadherence to Antiplatelet Regimens in Stented Patients (P=0.003 and P<0.001, respectively), and 0.600 versus 0.598 for Academic Research Consortium for High Bleeding Risk (P=0.006 and P<0.001, respectively). Conclusions The risk of dual antiplatelet therapy-associated postdischarge Bleeding Academic Research Consortium 2 to 5 bleeding was not significantly different between self-reported Black and White patients. Bleeding risk scores performed similarly among both groups.
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Affiliation(s)
- Brittain Heindl
- Division of Cardiovascular Diseases, Department of MedicineUniversity of Alabama at BirminghamBirminghamAL
| | - Stephen Clarkson
- Division of Cardiovascular Diseases, Department of MedicineUniversity of Alabama at BirminghamBirminghamAL
| | - Vibhu Parcha
- Division of Cardiovascular Diseases, Department of MedicineUniversity of Alabama at BirminghamBirminghamAL
| | - Chrisly Dillon
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAL
| | - Renuka Narayan
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAL
| | - Ebikere Usifo
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAL
| | - William Hillegass
- Department of Data Science, School of Public HealthUniversity of Mississippi Medical CenterJacksonMS
| | | | - Pankaj Arora
- Division of Cardiovascular Diseases, Department of MedicineUniversity of Alabama at BirminghamBirminghamAL
| | - Guihua Zhai
- Department of BiostatisticsUniversity of Alabama at BirminghamBirminghamAL
| | - Mark Beasley
- School of Public HealthUniversity of Alabama at BirminghamBirminghamAL
| | - Nita Limdi
- Department of NeurologyUniversity of Alabama at BirminghamBirminghamAL
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20
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Socioeconomic inequity in incidence, outcomes and care for acute coronary syndrome: A systematic review. Int J Cardiol 2022; 356:19-29. [DOI: 10.1016/j.ijcard.2022.03.053] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 02/17/2022] [Accepted: 03/24/2022] [Indexed: 12/17/2022]
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21
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Dawson LP, Andrew E, Nehme Z, Bloom J, Biswas S, Cox S, Anderson D, Stephenson M, Lefkovits J, Taylor AJ, Kaye D, Smith K, Stub D. Association of Socioeconomic Status With Outcomes and Care Quality in Patients Presenting With Undifferentiated Chest Pain in the Setting of Universal Health Care Coverage. J Am Heart Assoc 2022; 11:e024923. [PMID: 35322681 PMCID: PMC9075482 DOI: 10.1161/jaha.121.024923] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
BACKGROUND This study aimed to assess whether there are disparities in incidence rates, care, and outcomes for patients with chest pain attended by emergency medical services according to socioeconomic status (SES) in a universal health coverage setting. METHODS AND RESULTS This was a population‐based cohort study of individually linked ambulance, emergency, hospital admission, and mortality data in the state of Victoria, Australia, from January 2015 to June 2019 that included 183 232 consecutive emergency medical services attendances for adults with nontraumatic chest pain (mean age 62 [SD 18] years; 51% women) and excluded out‐of‐hospital cardiac arrest and ST‐segment–elevation myocardial infarction. Age‐standardized incidence of chest pain was higher for patients residing in lower SES areas (lowest SES quintile 1595 versus highest SES quintile 760 per 100 000 person‐years; P<0.001). Patients of lower SES were less likely to attend metropolitan, private, or revascularization‐capable hospitals and had greater comorbidities. In multivariable models adjusted for clinical characteristics and final diagnosis, lower SES quintiles were associated with increased risks of 30‐day and long‐term mortality, readmission for chest pain and acute coronary syndrome, lower acuity emergency department triage categorization, emergency department length of stay >4 hours, and emergency department or emergency medical services discharge without hospital admission and were inversely associated with use of prehospital ECGs and transfer to a revascularization‐capable hospital for patients presenting to non‐percutaneous coronary intervention centers. CONCLUSIONS In this study, lower SES was associated with a higher incidence of chest pain presentations to emergency medical services and differences in care and outcomes. These findings suggest that substantial disparities for socioeconomically disadvantaged chest pain cohorts exist, even in the setting of universal health care access.
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Affiliation(s)
- Luke P Dawson
- Department of Cardiology The Alfred Hospital Melbourne Victoria Australia.,Department of Epidemiology and Preventive Medicine Monash University Melbourne Victoria Australia.,Department of Cardiology The Royal Melbourne Hospital Melbourne Victoria Australia
| | - Emily Andrew
- Department of Epidemiology and Preventive Medicine Monash University Melbourne Victoria Australia.,Ambulance Victoria Melbourne Victoria Australia
| | - Ziad Nehme
- Department of Epidemiology and Preventive Medicine Monash University Melbourne Victoria Australia.,Ambulance Victoria Melbourne Victoria Australia.,Department of Paramedicine Monash University Melbourne Victoria Australia
| | - Jason Bloom
- Department of Cardiology The Alfred Hospital Melbourne Victoria Australia.,The Baker Institute Melbourne Victoria Australia
| | - Sinjini Biswas
- Department of Epidemiology and Preventive Medicine Monash University Melbourne Victoria Australia
| | - Shelley Cox
- Department of Epidemiology and Preventive Medicine Monash University Melbourne Victoria Australia.,Ambulance Victoria Melbourne Victoria Australia
| | - David Anderson
- Ambulance Victoria Melbourne Victoria Australia.,Department of Intensive Care Medicine The Alfred Hospital Melbourne Victoria Australia
| | - Michael Stephenson
- Department of Epidemiology and Preventive Medicine Monash University Melbourne Victoria Australia.,Ambulance Victoria Melbourne Victoria Australia.,Department of Paramedicine Monash University Melbourne Victoria Australia
| | - Jeffrey Lefkovits
- Department of Epidemiology and Preventive Medicine Monash University Melbourne Victoria Australia.,Department of Cardiology The Royal Melbourne Hospital Melbourne Victoria Australia
| | - Andrew J Taylor
- Department of Cardiology The Alfred Hospital Melbourne Victoria Australia.,Department of Epidemiology and Preventive Medicine Monash University Melbourne Victoria Australia.,Department of Medicine Monash University Melbourne Victoria Australia
| | - David Kaye
- Department of Cardiology The Alfred Hospital Melbourne Victoria Australia.,The Baker Institute Melbourne Victoria Australia
| | - Karen Smith
- Department of Epidemiology and Preventive Medicine Monash University Melbourne Victoria Australia.,Ambulance Victoria Melbourne Victoria Australia.,Department of Paramedicine Monash University Melbourne Victoria Australia
| | - Dion Stub
- Department of Cardiology The Alfred Hospital Melbourne Victoria Australia.,Department of Epidemiology and Preventive Medicine Monash University Melbourne Victoria Australia.,The Baker Institute Melbourne Victoria Australia
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22
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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: 3043] [Impact Index Per Article: 1014.3] [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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23
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Buckman M, Grant A, Henson S, Ribeiro J, Roth K, Stranton D, Korvink M, Gunn LH. A review of socioeconomic factors associated with acute myocardial infarction-related mortality and hospital readmissions. Hosp Pract (1995) 2022; 50:1-8. [PMID: 34933647 DOI: 10.1080/21548331.2021.2022357] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
BACKGROUND Risk-adjustment models are widely used methodological approaches within the healthcare industry to measure hospital performance and quality of care. However, the Centers for Medicare and Medicaid Services (CMS) do not fully adjust for socioeconomic status (SES) in acute myocardial infarction (AMI) models. A review and evidence synthesis was conducted to identify associations of SES factors with hospital readmission and mortality in AMI patients. METHODS Multiple electronic databases were queried to identify studies assessing risk for AMI-related mortality or hospital readmissions and SES factors. Identified studies were screened by title and abstract. Full-text reviews followed for articles meeting the inclusion criteria, including quality assessments. Data were extracted from all included studies, and evidence synthesis was performed to identify associations between SES factors and outcome variables. RESULTS Ten studies were included in the review. One study showed that Black patients had higher AMI-related readmission rates compared to White patients (mean difference 4.3% [SD 1.4%], p < 0.001). Another study showed that income inequality was associated with increased risk of AMI-related readmissions (RR 1.18 [95% CI], 1.13-1.23). One study found that unemployed individuals experienced significantly greater rates of AMI-related mortality than those working full-time (HR 2.08, 1.51-2.87). According to another study, lack of health insurance was associated with worse rates for in-hospital AMI-related mortality (OR 1.77, 1.72-1.82). Based on one study, AMI-related mortality was higher in those with <8 years of education compared to those with >16 years (17.5% vs. 3.5%, p < 0.0001). Five of six studies found a significant association between ZIP code/neighborhood/location and AMI-related readmission or mortality. CONCLUSION Race, ZIP code/neighborhood/location, insurance status, income/poverty, and education comprise SES factors found to be associated with AMI-related mortality and/or readmission outcomes. Including these SES factors in future updates of CMS's risk-adjusted models has the potential to provide more appropriate compensation mechanisms to hospitals.
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Affiliation(s)
- Mercy Buckman
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA.,School of Data Science, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Amanda Grant
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA.,School of Data Science, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Sally Henson
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA.,School of Data Science, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Julia Ribeiro
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA.,School of Data Science, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Katie Roth
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA.,School of Data Science, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Derek Stranton
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA.,School of Data Science, University of North Carolina at Charlotte, Charlotte, NC, USA
| | | | - Laura H Gunn
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA.,School of Data Science, University of North Carolina at Charlotte, Charlotte, NC, USA.,Department of Primary Care and Public Health, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
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24
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Shahian DM, Badhwar V, O'Brien SM, Habib RH, Han J, McDonald DE, Antman MS, Higgins RSD, Preventza O, Estrera AL, Calhoon JH, Grondin SC, Cooke DT. Social Risk Factors in Society of Thoracic Surgeons Risk Models Part 1: Concepts, Indicator Variables, and Controversies. Ann Thorac Surg 2022; 113:1703-1717. [PMID: 34998732 DOI: 10.1016/j.athoracsur.2021.11.067] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 10/29/2021] [Accepted: 11/02/2021] [Indexed: 11/01/2022]
Affiliation(s)
- David M Shahian
- Division of Cardiac Surgery, Department of Surgery, and Center for Quality and Safety, Massachusetts General Hospital and Harvard Medical School, Boston, MA.
| | - Vinay Badhwar
- Department of Cardiovascular and Thoracic Surgery, West Virginia University, Morgantown WV
| | | | | | - Jane Han
- Society of Thoracic Surgeons, Chicago, IL
| | | | | | - Robert S D Higgins
- Johns Hopkins University School of Medicine and Johns Hopkins Hospital, Baltimore, MD
| | - Ourania Preventza
- Baylor College of Medicine, Texas Heart Institute, Baylor St. Luke's Medical Center, Houston, TX
| | - Anthony L Estrera
- McGovern Medical School at UTHealth; Memorial Hermann Heart and Vascular Institute; Houston, TX
| | - John H Calhoon
- Department of Cardiothoracic Surgery, University of Texas Health Science Center at San Antonio
| | - Sean C Grondin
- Cumming School of Medicine, University of Calgary, and Foothills Medical Centre, Calgary, Alberta, Canada
| | - David T Cooke
- Division of General Thoracic Surgery, UC Davis Health, Sacramento, CA
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25
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Huded CP, Dalton JE, Kumar A, Krieger NI, Kassis N, Phelan M, Kravitz K, Reed GW, Krishnaswamy A, Kapadia SR, Khot U. Relationship of Neighborhood Deprivation and Outcomes of a Comprehensive ST Elevation Myocardial Infarction Protocol. J Am Heart Assoc 2021; 10:e024540. [PMID: 34779652 PMCID: PMC9075260 DOI: 10.1161/jaha.121.024540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Background We evaluated whether a comprehensive ST‐segment–elevation myocardial infarction protocol (CSP) focusing on guideline‐directed medical therapy, transradial percutaneous coronary intervention, and rapid door‐to‐balloon time improves process and outcome metrics in patients with moderate or high socioeconomic deprivation. Methods and Results A total of 1761 patients with ST‐segment–elevation myocardial infarction treated with percutaneous coronary intervention at a single hospital before (January 1, 2011–July 14, 2014) and after (July 15, 2014– July 15, 2019) CSP implementation were included in an observational cohort study. Neighborhood deprivation was assessed by the Area Deprivation Index and was categorized as low (≤50th percentile; 29.0%), moderate (51st –90th percentile; 40.8%), and high (>90th percentile; 30.2%). The primary process outcome was door‐to‐balloon time. Achievement of guideline‐recommend door‐to‐balloon time goals improved in all deprivation groups after CSP implementation (low, 67.8% before CSP versus 88.5% after CSP; moderate, 50.7% before CSP versus 77.6% after CSP; high, 65.5% before CSP versus 85.6% after CSP; all P<0.001). Median door‐to‐balloon time among emergency department/in‐hospital patients was significantly noninferior in higher versus lower deprivation groups after CSP (noninferiority limit=5 minutes; Pnoninferiority high versus moderate = 0.002, high versus low <0.001, moderate versus low = 0.02). In‐hospital mortality, the primary clinical outcome, was significantly lower after CSP in patients with moderate/high deprivation in unadjusted (before CSP 7.0% versus after CSP 3.1%; odds ratio [OR], 0.42 [95% CI, 0.25–0.72]; P=0.002) and risk‐adjusted (OR, 0.42 [95% CI, 0.23–0.77]; P=0.005) models. Conclusions A CSP was associated with improved ST‐segment–elevation myocardial infarction care across all deprivation groups and reduced mortality in those from moderate or high deprivation neighborhoods. Standardized initiatives to reduce care variability may mitigate social determinants of health in time‐sensitive conditions such as ST‐segment–elevation myocardial infarction.
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Affiliation(s)
- Chetan P Huded
- Department of Cardiology Saint Luke's Mid-America Heart Institute Kansas City MO
| | - Jarrod E Dalton
- Department of Quantitative Health Sciences Lerner Research Institute Cleveland Clinic Cleveland OH
| | - Anirudh Kumar
- Department of Cardiovascular Medicine Thoracic Institute Cleveland Clinic Heart, Vascular Cleveland OH.,Center for Healthcare Delivery Innovation Thoracic Institute Cleveland Clinic Heart, Vascular Cleveland OH
| | - Nikolas I Krieger
- Department of Quantitative Health Sciences Lerner Research Institute Cleveland Clinic Cleveland OH
| | - Nicholas Kassis
- Department of Cardiovascular Medicine Thoracic Institute Cleveland Clinic Heart, Vascular Cleveland OH.,Center for Healthcare Delivery Innovation Thoracic Institute Cleveland Clinic Heart, Vascular Cleveland OH
| | - Michael Phelan
- Department of Emergency Medicine Emergency Services Institute Cleveland Clinic Cleveland OH
| | - Kathleen Kravitz
- Department of Cardiovascular Medicine Thoracic Institute Cleveland Clinic Heart, Vascular Cleveland OH
| | - Grant W Reed
- Department of Cardiovascular Medicine Thoracic Institute Cleveland Clinic Heart, Vascular Cleveland OH
| | - Amar Krishnaswamy
- Department of Cardiovascular Medicine Thoracic Institute Cleveland Clinic Heart, Vascular Cleveland OH
| | - Samir R Kapadia
- Department of Cardiovascular Medicine Thoracic Institute Cleveland Clinic Heart, Vascular Cleveland OH
| | - Umesh Khot
- Department of Cardiovascular Medicine Thoracic Institute Cleveland Clinic Heart, Vascular Cleveland OH.,Center for Healthcare Delivery Innovation Thoracic Institute Cleveland Clinic Heart, Vascular Cleveland OH
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26
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Daley S, Kajendrakumar B, Nandhakumar S, Personett C, Sholes M, Thapa S, Xue C, Korvink M, Gunn LH. County-Level Socioeconomic Status Adjustment of Acute Myocardial Infarction Mortality Hospital Performance Measure in the U.S. Healthcare (Basel) 2021; 9:healthcare9111424. [PMID: 34828471 PMCID: PMC8620965 DOI: 10.3390/healthcare9111424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 10/01/2021] [Accepted: 10/19/2021] [Indexed: 11/16/2022] Open
Abstract
The U.S. Centers for Medicare and Medicaid Services’ (CMS’s) Hospital Compare (HC) data provides a collection of risk-adjusted hospital performance metrics intended to allow comparison of hospital-provided care. However, CMS does not adjust for socioeconomic status (SES) factors, which have been found to be associated with disparate health outcomes. Associations between county-level SES factors and CMS’s risk-adjusted 30-day acute myocardial infarction (AMI) mortality rates are explored for n = 2462 hospitals using a variety of sources for county-level SES information. Upon performing multiple imputation, a stepwise backward elimination model selection approach using Akaike’s information criteria was used to identify the optimal model. The resulting model, comprised of 14 predictors mostly at the county level, provides an additional 8% explanatory power to capture the variability in 30-day risk-standardized AMI mortality rates, which already account for patient-level clinical differences. SES factors may be an important feature for inclusion in future risk-adjustment models, which will have system and policy implications for distributing resources to hospitals, such as reimbursements. It also serves as a stepping stone to identify and address long-standing SES-related inequities.
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Affiliation(s)
- Sean Daley
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; (S.D.); (B.K.); (S.N.); (C.P.); (M.S.); (S.T.); (C.X.)
- School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
| | - Bakthameera Kajendrakumar
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; (S.D.); (B.K.); (S.N.); (C.P.); (M.S.); (S.T.); (C.X.)
| | - Samyuktha Nandhakumar
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; (S.D.); (B.K.); (S.N.); (C.P.); (M.S.); (S.T.); (C.X.)
- School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
| | - Christine Personett
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; (S.D.); (B.K.); (S.N.); (C.P.); (M.S.); (S.T.); (C.X.)
- School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
| | - Michael Sholes
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; (S.D.); (B.K.); (S.N.); (C.P.); (M.S.); (S.T.); (C.X.)
- School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
| | - Swornim Thapa
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; (S.D.); (B.K.); (S.N.); (C.P.); (M.S.); (S.T.); (C.X.)
- School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
| | - Chen Xue
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; (S.D.); (B.K.); (S.N.); (C.P.); (M.S.); (S.T.); (C.X.)
- School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
| | | | - Laura H. Gunn
- Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; (S.D.); (B.K.); (S.N.); (C.P.); (M.S.); (S.T.); (C.X.)
- School of Data Science, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
- Faculty of Medicine, School of Public Health, Imperial College London, London W6 8RP, UK
- Correspondence:
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27
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Jankowski P, Topór-Mądry R, Gąsior M, Cegłowska U, Eysymontt Z, Gierlotka M, Wita K, Legutko J, Dudek D, Sierpiński R, Pinkas J, Kaźmierczak J, Witkowski A, Szumowski Ł. Innovative Managed Care May Be Related to Improved Prognosis for Acute Myocardial Infarction Survivors. Circ Cardiovasc Qual Outcomes 2021; 14:e007800. [PMID: 34380330 DOI: 10.1161/circoutcomes.120.007800] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Mortality following discharge in myocardial infarction survivors remains high. Therefore, we compared outcomes in myocardial infarction survivors participating and not participating in a novel, nationwide managed care program for myocardial infarction survivors in Poland. METHODS We used public databases. We included all patients hospitalized due to acute myocardial infarction in Poland between October 1, 2017 and December 31, 2018. We excluded from the analysis all patients aged <18 years as well as those who died during hospitalization or within 10 days following discharge from hospital. All patients were prospectively followed. The primary end point was defined as death from any cause. RESULTS The mean follow-up was 324.8±140.5 days (78 034.1 patient-years; 340.0±131.7 days in those who did not die during the observation). Participation in the managed care program was related to higher odds ratio of participating in cardiac rehabilitation (4.67 [95% CI, 4.44-4.88]), consultation with a cardiologist (7.32 [6.83-7.84]), implantable cardioverter-defibrillator (1.40 [1.22-1.61]), and cardiac resynchronization therapy with cardioverter-defibrillator implantation (1.57 [1.22-2.03]) but lower odds of emergency (0.88 [0.79-0.98]) and nonemergency percutaneous coronary intervention (0.88 [0.83-0.93]) and coronary artery bypass grafting (0.82 [0.71-0.94]) during the follow-up. One-year all-cause mortality was 4.4% among the program participants and 6.0% in matched nonparticipants. The end point consisting of all-cause death, myocardial infarction, or stroke occurred in 10.6% and 12.0% (P<0.01) of participants and nonparticipants respectively, whereas all-cause death or hospitalization for cardiovascular reasons in 42.2% and 47.9% (P<0.001) among participants and nonparticipants, respectively. The difference in outcomes between patients participating and not participating in the managed care program could be explained by improved access to cardiac rehabilitation, cardiac care, and cardiac procedures. CONCLUSIONS Managed care following myocardial infarction may be related to improved prognosis as it may facilitate access to cardiac rehabilitation and may provide a higher standard of outpatient cardiac care.
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Affiliation(s)
- Piotr Jankowski
- I Department of Cardiology, Interventional Electrocardiology and Hypertension, Institute of Cardiology, Jagiellonian University Medical College, Krakow, Poland (P.J.)
| | - Roman Topór-Mądry
- Agency for Health Technology Assessment and Tariff System, Warsaw, Poland (R.T.-M., U.C.)
| | - Mariusz Gąsior
- 3rd Department of Cardiology, Faculty of Medical Sciences in Zabrze (M. Gąsior), Medical University of Silesia, Katowice, Poland
| | - Urszula Cegłowska
- Agency for Health Technology Assessment and Tariff System, Warsaw, Poland (R.T.-M., U.C.)
| | - Zbigniew Eysymontt
- Cardiac Rehabilitation Department, Ślaskie Centrum Rehabilitacji w Ustroniu, Ustron, Poland (Z.E.)
| | - Marek Gierlotka
- Department of Cardiology, University Hospital, Institute of Medical Sciences, University of Opole, Poland (M. Gierlotka)
| | - Krystian Wita
- First Department of Cardiology, School of Medicine in Katowice (K.W.), Medical University of Silesia, Katowice, Poland
| | - Jacek Legutko
- Department of Interventional Cardiology, Institute of Cardiology, Jagiellonian University Medical College, John Paul II Hospital, Krakow, Poland (J.L.)
| | - Dariusz Dudek
- Institute of Cardiology, Jagiellonian University, Kopernika 17, Krakow, Poland (D.D.)
| | | | - Jarosław Pinkas
- School of Public Health, Centre of Postgraduate Medical Education, Warsaw, Poland (J.P.)
| | - Jarosław Kaźmierczak
- Department of Cardiology, Pomeranian Medical University, Szczecin, Poland (J.K.)
| | - Adam Witkowski
- Department of Interventional Cardiology and Angiology, Institute of Cardiology, Warsaw, Poland (A.W.)
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Virani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Cheng S, Delling FN, Elkind MSV, Evenson KR, Ferguson JF, Gupta DK, Khan SS, Kissela BM, Knutson KL, Lee CD, Lewis TT, Liu J, Loop MS, Lutsey PL, Ma J, Mackey J, Martin SS, Matchar DB, Mussolino ME, Navaneethan SD, Perak AM, Roth GA, Samad Z, Satou GM, Schroeder EB, Shah SH, Shay CM, Stokes A, VanWagner LB, Wang NY, Tsao CW. Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association. Circulation 2021; 143:e254-e743. [PMID: 33501848 DOI: 10.1161/cir.0000000000000950] [Citation(s) in RCA: 3442] [Impact Index Per Article: 860.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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 2021 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, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease. RESULTS Each of the 27 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, policy makers, 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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Hughes V, Paige E, Welsh J, Joshy G, Banks E, Korda RJ. Education-related variation in coronary procedure rates and the contribution of private health care in Australia: a prospective cohort study. Int J Equity Health 2020; 19:139. [PMID: 32795313 PMCID: PMC7427777 DOI: 10.1186/s12939-020-01235-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 07/03/2020] [Indexed: 11/26/2022] Open
Abstract
Background Contemporary Australian evidence on socioeconomic variation in secondary cardiovascular disease (CVD) care, a possible contributor to inequalities in cardiovascular disease outcomes, is lacking. This study examined the relationship between education, an individual-level indicator of socioeconomic position, and receipt of angiography and revascularisation procedures following incident hospitalisation for acute myocardial infarction (AMI) or angina, and the role of private care in this relationship. Methods Participants aged ≥45 from the New South Wales population-based 45 and Up Study with no history of prior ischaemic heart disease hospitalised for AMI or angina were followed for receipt of angiography or revascularisation within 30 days of hospital admission, ascertained through linked hospital records. Education attainment, measured on baseline survey, was categorised as low (no school certificate/qualifications), intermediate (school certificate/trade/apprenticeship/diploma) and high (university degree). Cox regression estimated the association (hazard ratios [HRs]) between education and coronary procedure receipt, adjusting for demographic and health-related factors, and testing for linear trend. Private health insurance was investigated as a mediating variable. Results Among 4454 patients with AMI, 68.3% received angiography within 30 days of admission (crude rate: 25.8/person-year) and 48.8% received revascularisation (rate: 11.7/person-year); corresponding figures among 4348 angina patients were 59.7% (rate: 17.4/person-year) and 30.8% (rate: 5.3/person-year). Procedure rates decreased with decreasing levels of education. Comparing low to high education, angiography rates were 29% lower among AMI patients (adjusted HR = 0.71, 95% CI: 0.56–0.90) and 40% lower among angina patients (0.60, 0.47–0.76). Patterns were similar for revascularisation among those with angina (0.78, 0.61–0.99) but not AMI (0.93, 0.69–1.25). After adjustment for private health insurance status, the HRs were attenuated and there was little evidence of an association between education and angiography among those admitted for AMI. Conclusions There is a socioeconomic gradient in coronary procedures with the most disadvantaged patients being less likely to receive angiography following hospital admission for AMI or angina, and revascularisation procedures for angina. Unequal access to private health care contributes to these differences. The extent to which the remaining variation is clinically appropriate, or whether angiography is being underused among people with low socioeconomic position or overused among those with higher socioeconomic position, is unclear.
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Affiliation(s)
- Veronica Hughes
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia
| | - Ellie Paige
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia.
| | - Jennifer Welsh
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia
| | - Grace Joshy
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia
| | - Emily Banks
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia.,Sax Institute, Sydney, NSW, Australia
| | - Rosemary J Korda
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia
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Schrage B, Lund LH, Benson L, Stolfo D, Ohlsson A, Westerling R, Westermann D, Strömberg A, Dahlström U, Braunschweig F, Ferreira JP, Savarese G. Lower socioeconomic status predicts higher mortality and morbidity in patients with heart failure. Heart 2020; 107:229-236. [PMID: 32769169 DOI: 10.1136/heartjnl-2020-317216] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 07/05/2020] [Accepted: 07/09/2020] [Indexed: 11/03/2022] Open
Abstract
OBJECTIVE It is not fully understood whether and how socioeconomic status (SES) has a prognostic impact in patients with heart failure (HF). We assessed SES and its association with patient characteristics and outcomes in a contemporary and well-characterised HF cohort. METHODS Socioeconomic risk factors (SERF) were defined in the Swedish HF Registry based on income (low vs high according to the annual median value), education level (no degree/compulsory school vs university/secondary school) and living arrangement (living alone vs cohabitating). RESULTS Of 44 631 patients, 21% had no, 33% one, 30% two and 16% three SERF. Patient characteristics strongly and independently associated with lower SES were female sex and no specialist referral. Additional independent associations were older age, more severe HF, heavier comorbidity burden, use of diuretics and less use of HF devices. Lower SES was associated with higher risk of HF hospitalisation/mortality, and overall cardiovascular and non-cardiovascular events. These associations persisted after extensive adjustment for patient characteristics, treatments and care. The magnitude of the association increased linearly with the increasing number of coexistent SERF: HR (95% CI) 1.09 (1.05 to 1.13) for one, 1.16 (1.12 to 1.20) for two and 1.22 (1.18 to 1.28) for three SERF (p<0.01). CONCLUSIONS In a contemporary and well-characterised HF cohort and after comprehensive adjustment for confounders, lower SES was linked with multiple factors such as less use of HF devices and age, but most strongly with female sex and lack of specialist referral; and associated with greater risk of morbidity/mortality.
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Affiliation(s)
- Benedikt Schrage
- Department of Medicine, Karolinska Institute, Stockholm, Sweden.,German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Hamburg, Germany.,Department of Cardiology, University Heart and Vascular Center Hamburg, Hamburg, Germany
| | - Lars H Lund
- Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Lina Benson
- Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Davide Stolfo
- Department of Medicine, Karolinska Institute, Stockholm, Sweden.,Cardiovascular Department, 'Ospedali Riuniti' and University of Trieste, Trieste, Italy
| | - Anna Ohlsson
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Ragnar Westerling
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Dirk Westermann
- German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Hamburg, Germany.,Department of Cardiology, University Heart and Vascular Center Hamburg, Hamburg, Germany
| | - Anna Strömberg
- Department of Medical and Health Science, Linköping University, Linköping, Sweden
| | - Ulf Dahlström
- Department of Medical and Health Science, Linköping University, Linköping, Sweden
| | | | - João Pedro Ferreira
- Centre d'Investigations Cliniques Plurithématique 1433, Université de Lorraine and CHU de Nancy, INSERM UMR1116, Vandoeuvre-les-nancy, France.,F-CRIN INI-CRCT Cardiovascular and Renal Clinical Trialists, Vandoeuvre-les-Nancy, France
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31
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Association Between Residential Neighborhood Social Conditions and Health Care Utilization and Costs. Med Care 2020; 58:586-593. [DOI: 10.1097/mlr.0000000000001337] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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32
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Wadhera RK, Bhatt DL, Kind AJ, Song Y, Williams KA, Maddox TM, Yeh RW, Dong L, Doros G, Turchin A, Maddox KEJ. Association of Outpatient Practice-Level Socioeconomic Disadvantage With Quality of Care and Outcomes Among Older Adults With Coronary Artery Disease: Implications for Value-Based Payment. Circ Cardiovasc Qual Outcomes 2020; 13:e005977. [PMID: 32228065 PMCID: PMC7259485 DOI: 10.1161/circoutcomes.119.005977] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 02/20/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND Medicare patients with coronary artery disease (CAD) have been a significant focus of value-based payment programs for outpatient practices. Physicians and policymakers, however, have voiced concern that value-based payment programs may penalize practices that serve vulnerable populations. This study evaluated whether outpatient practices that serve socioeconomically disadvantaged populations have worse CAD outcomes, and if this reflects the delivery of lower-quality care or rather, patient and community factors beyond the care provided by physician practices. METHODS AND RESULTS Retrospective cohort study of Medicare fee-for-service patients ≥65 years with CAD at outpatient practices participating in the the Practice Innovation and Clinical Excellence registry from January 1, 2010 to January 1, 2015. Outpatient practices were stratified into quintiles by the proportion of most disadvantaged patients-defined by an area deprivation score in the highest 20% nationally-served at each practice site. Prescription of guideline recommended therapies for CAD as well as clinical outcomes (emergency department presentation for chest pain, hospital admission for unstable angina or acute myocardial infarction [AMI], 30-day readmission after AMI, and 30-day mortality after AMI) were evaluated by practice-level socioeconomic disadvantage with hierarchical logistic regression models, using practices serving the fewest socioeconomically disadvantaged patients as a reference. The study included 453 783 Medicare fee-for-service patients ≥65 years of age with CAD (mean [SD] age, 75.3 [7.7] years; 39.7% female) cared for at 271 outpatient practices. At practices serving the highest proportion of socioeconomically disadvantaged patients (group 5), compared with practices serving the lowest proportion (group 1), there was no significant difference in the likelihood of prescription of antiplatelet therapy (odds ratio [OR], 0.94 [95% CI, 0.69-1.27]), β-blocker therapy if prior myocardial infarction or left ventricular ejection fraction <40% (OR, 0.97 [95% CI, 0.69-1.35]), ACE (angiotensin-converting enzyme) inhibitor or angiotensin receptor blocker if left ventricular ejection fraction <40% and/or diabetes mellitus (OR, 0.93 [95% CI, 0.74-1.19]), statin therapy (OR, 0.88 [95% CI, 0.68-1.14]), or cardiac rehabilitation (OR, 0.45 [95% CI, 0.20-1.00]). Patients cared for at the most disadvantaged-serving practices (group 5) were more likely to be admitted for unstable angina (adjusted OR, 1.46 [95% CI, 1.04-2.05]). There was no significant difference in the likelihood of emergency department presentation for chest pain or hospital admission for AMI between practices. Thirty day mortality rates after AMI were higher among patients at the most disadvantaged-serving practices (aOR, 1.31 [95% CI, 1.02-1.68]), but 30-day readmission rates did not differ. All associations were attenuated after additional adjustment for patient-level area deprivation index. CONCLUSIONS Physician outpatient practices that serve the most socioeconomically disadvantaged patients with CAD perform worse on some clinical outcomes, despite providing similar guideline-recommended care as other practices, and consequently could fare poorly under value-based payment programs. Social factors beyond care provided by outpatient practices may partly explain worse outcomes. Policymakers should consider accounting for socioeconomic disadvantage in value-based payment programs initiatives that target outpatient practices.
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Affiliation(s)
- Rishi K. Wadhera
- Brigham and Women’s Hospital Heart & Vascular Center, Harvard Medical School, Boston, MA
- Richard and Susan Smith Center for Outcomes Research in Cardiology, Division of Cardiology, Beth Israel Deaconess Medical and Harvard Medical School, Boston, MA
| | - Deepak L. Bhatt
- Brigham and Women’s Hospital Heart & Vascular Center, Harvard Medical School, Boston, MA
| | - Amy J.H. Kind
- Geriatrics Division, Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin
| | - Yang Song
- Baim Institute for Clinical Research, Boston, MA
| | - Kim A. Williams
- Division of Cardiology, Department of Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Thomas M. Maddox
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, Saint Louis, MO
| | - Robert W. Yeh
- Richard and Susan Smith Center for Outcomes Research in Cardiology, Division of Cardiology, Beth Israel Deaconess Medical and Harvard Medical School, Boston, MA
| | - Liyan Dong
- Baim Institute for Clinical Research, Boston, MA
| | - Gheorghe Doros
- Baim Institute for Clinical Research, Boston, MA
- Department of Biostatistics, Boston University, Boston, MA
| | - Alexander Turchin
- Baim Institute for Clinical Research, Boston, MA
- Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Karen E. Joynt Maddox
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, Saint Louis, MO
- Center for Health Economics and Policy, Institute for Public Health at Washington University, Saint Louis, MO
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Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Shay CM, Spartano NL, Stokes A, Tirschwell DL, VanWagner LB, Tsao CW. Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association. Circulation 2020; 141:e139-e596. [PMID: 31992061 DOI: 10.1161/cir.0000000000000757] [Citation(s) in RCA: 5302] [Impact Index Per Article: 1060.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports on 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 2020 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, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals. RESULTS Each of the 26 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, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Zhang Y, Grinspan Z, Khullar D, Unruh MA, Shenkman E, Cohen A, Kaushal R. Developing an actionable patient taxonomy to understand and characterize high-cost Medicare patients. HEALTHCARE-THE JOURNAL OF DELIVERY SCIENCE AND INNOVATION 2020; 8:100406. [PMID: 31918975 DOI: 10.1016/j.hjdsi.2019.100406] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 12/17/2019] [Accepted: 12/22/2019] [Indexed: 10/25/2022]
Abstract
BACKGROUND Improving care for high-cost patients requires a better understanding of their characteristics and the ability to effectively target interventions. We developed an actionable taxonomy with clinically meaningful patient categories for high-cost Medicare patients-those in the top 10% of total costs. METHODS A cross-sectional study of a Medicare fee-for-service (FFS) patient cohort in the New York metropolitan area. We merged claims and neighborhood social determinants of health data to map patients into actionable categories. RESULTS Among 428,024 Medicare FFS patients, we mapped the 42,802 high-cost patients into ten overlapping categories, including: multiple chronic conditions, seriously ill, frail, serious mental illness, single condition with high pharmacy cost, chronic pain, end-stage renal disease (ESRD), single high-cost chronic condition, opioid use disorder, and socially vulnerable. Most high-cost patients had multiple chronic conditions (97.4%), followed by serious illness (53.7%) and frailty (48.9%). Patients with ESRD, who were seriously ill, and who were frail were more likely to be high-cost compared to patients in other categories. 72.7% of high-cost patients fell into multiple categories. CONCLUSIONS High-cost patients are highly heterogeneous. A patient taxonomy incorporating medical, behavioral, and social characteristics may help providers better understand their characteristics and health needs. IMPLICATIONS Mapping high-cost patients into clinically meaningful and actionable categories that incorporate medical, behavioral, and social factors could help health systems target interventions. Integrated approaches, including medical care, behavioral health, and social services may be needed to effectively and efficiently care for high-cost patients.
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Affiliation(s)
- Yongkang Zhang
- Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY, USA.
| | - Zachary Grinspan
- Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY, USA; New York-Presbyterian Hospital, New York, NY, USA; Department of Pediatrics, Weill Cornell Medical College, New York, NY, USA
| | - Dhruv Khullar
- Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY, USA; New York-Presbyterian Hospital, New York, NY, USA; Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Mark Aaron Unruh
- Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY, USA
| | - Elizabeth Shenkman
- Department of Health Outcomes & Biomedical Informatics, University of Florida, Gainesville, FL, USA
| | - Andrea Cohen
- Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY, USA
| | - Rainu Kaushal
- Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY, USA; New York-Presbyterian Hospital, New York, NY, USA; Department of Pediatrics, Weill Cornell Medical College, New York, NY, USA; Department of Medicine, Weill Cornell Medical College, New York, NY, USA
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Gabet A, Danchin N, Puymirat E, Tuppin P, Olié V. Early and late case fatality after hospitalization for acute coronary syndrome in France, 2010-2015. Arch Cardiovasc Dis 2019; 112:754-764. [PMID: 31718932 DOI: 10.1016/j.acvd.2019.09.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 08/08/2019] [Accepted: 09/09/2019] [Indexed: 11/29/2022]
Abstract
BACKGROUND Case-fatality data for acute coronary syndromes (ACS) are scarce in unselected French patients. AIMS To analyse early and late case-fatality rates in patients with ACS in France, case fatality determinants and time trends between 2010 and 2015. METHODS For each year from 2010 to 2015, all patients hospitalized for ACS in France and aged>18 years were selected. Multivariable Cox models were used to assess determinants of case fatality at 3 days, 4-30 days and 31-365 days after hospital admission. RESULTS In 2015, cumulative 3-day, 30-day and 1-year case-fatality rates were, respectively, 2.0%, 5.1% and 11.1% for all patients with ACS, and 3.9%, 8.5% and 13.8% for those with ST-segment elevation myocardial infarction (STEMI). Admission through the emergency department was associated with a higher risk of death, particularly at 3 days. Female sex was associated with higher case-fatality rates at 3 days, but with lower case-fatality rates at 31-365 days. Social deprivation was associated with higher case-fatality rates for all periods for all patients with ACS. A significant decrease was found between 2010 and 2015 in case-fatality rates at 31-365 days, particularly for patients with STEMI; this time trend was no longer significant after additional adjustment for hospital management. CONCLUSIONS Case fatality up to 1 year after hospitalization for ACS was non-negligible, highlighting the need to ensure better follow-up after the acute stage, particularly in the most deprived patients. As hospital admission through the emergency department still occurs frequently, health policy should promote a national campaign to increase the awareness and preparedness of the general population regarding ACS. Finally, our results suggest that women need specific attention early after the index event.
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Affiliation(s)
- Amélie Gabet
- French Public Health Agency, 94410 Saint-Maurice, France.
| | - Nicolas Danchin
- Department of cardiology, hôpital européen Georges-Pompidou, AP-HP, 75015 Paris, France
| | - Etienne Puymirat
- Department of cardiology, hôpital européen Georges-Pompidou, AP-HP, 75015 Paris, France
| | - Philippe Tuppin
- General Health Insurance Scheme (Caisse nationale d'assurance maladie), 75020 Paris, France
| | - Valérie Olié
- French Public Health Agency, 94410 Saint-Maurice, France
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Cai A, Dillon C, Hillegass WB, Beasley M, Brott BC, Bittner VA, Perry GJ, Halade GV, Prabhu SD, Limdi NA. Risk of Major Adverse Cardiovascular Events and Major Hemorrhage Among White and Black Patients Undergoing Percutaneous Coronary Intervention. J Am Heart Assoc 2019; 8:e012874. [PMID: 31701784 PMCID: PMC6915255 DOI: 10.1161/jaha.119.012874] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Background Data on racial disparities in major adverse cardiovascular events (MACE) and major hemorrhage (HEM) after percutaneous coronary intervention are limited. Factors contributing to these disparities are unknown. Methods and Results PRiME‐GGAT (Pharmacogenomic Resource to Improve Medication Effectiveness–Genotype‐Guided Antiplatelet Therapy) is a prospective cohort. Patients aged ≥18 years undergoing percutaneous coronary intervention were enrolled and followed for up to 1 year. Racial disparities in risk of MACE and HEM were assessed using an incident rate ratio. Sequential cumulative adjustment analyses were performed to identify factors contributing to these disparities. Data from 919 patients were included in the analysis. Compared with white patients, black patients (n=203; 22.1% of the cohort) were younger and were more likely to be female, to be a smoker, and to have higher body mass index, lower socioeconomic status, higher prevalence of diabetes mellitus and moderate to severe chronic kidney disease, and presentation with acute coronary syndrome and to undergo urgent percutaneous coronary intervention. The incident rates of MACE (34.1% versus 18.2% per 100 person‐years, P<0.001) and HEM (17.7% versus 10.3% per 100 person‐years, P=0.02) were higher in black patients. The incident rate ratio was 1.9 (95% CI, 1.3–2.6; P<0.001) for MACE and 1.7 (95% CI, 1.1–2. 7; P=0.02) for HEM. After adjustment for nonclinical and clinical factors, black race was not significantly associated with outcomes. Rather, differences in socioeconomic status, comorbidities, and coronary heart disease severity were attributed to racial disparities in outcomes. Conclusions Despite receiving similar treatment, racial disparities in MACE and HEM still exist. Opportunities exist to narrow these disparities by mitigating the identified contributors.
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Affiliation(s)
- Anping Cai
- Department of Neurology University of Alabama at Birmingham AL
| | - Chrisly Dillon
- Department of Neurology University of Alabama at Birmingham AL
| | - William B Hillegass
- Department of Data Science and Medicine University of Mississippi Medical Center Jackson MS
| | - Mark Beasley
- Department of Biostatistics University of Alabama at Birmingham AL
| | - Brigitta C Brott
- Division of Cardiovascular Diseases Department of Medicine University of Alabama at Birmingham AL
| | - Vera A Bittner
- Division of Cardiovascular Diseases Department of Medicine University of Alabama at Birmingham AL
| | - Gilbert J Perry
- Division of Cardiovascular Diseases Department of Medicine University of Alabama at Birmingham AL
| | - Ganesh V Halade
- Division of Cardiovascular Diseases Department of Medicine University of Alabama at Birmingham AL
| | - Sumanth D Prabhu
- Division of Cardiovascular Diseases Department of Medicine University of Alabama at Birmingham AL
| | - Nita A Limdi
- Department of Neurology University of Alabama at Birmingham AL
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Udell JA. Socioeconomics and Atherosclerosis: Where There's Smoke, There's Fire. J Am Coll Cardiol 2019; 74:536-537. [PMID: 31345428 DOI: 10.1016/j.jacc.2019.06.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2019] [Accepted: 06/17/2019] [Indexed: 10/26/2022]
Affiliation(s)
- Jacob A Udell
- Cardiovascular Division, Department of Medicine, Peter Munk Cardiac Centre, Toronto General Hospital and Women's College Hospital, University of Toronto, Toronto, Ontario, Canada.
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