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      Sex-Based Disparities in Acute Myocardial Infarction Treatment Patterns and Outcomes in Older Adults Hospitalized Across 6 High-Income Countries: An Analysis From the International Health Systems Research Collaborative

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          Abstract

          BACKGROUND:

          Sex differences in acute myocardial infarction treatment and outcomes are well documented, but it is unclear whether differences are consistent across countries. The objective of this study was to investigate the epidemiology, use of interventional procedures, and outcomes for older females and males hospitalized with ST-segment–elevation myocardial infarction (STEMI) and non–ST-segment–elevation myocardial infarction (NSTEMI) in 6 diverse countries.

          METHODS:

          We conducted a serial cross-sectional cohort study of 1 508 205 adults aged ≥66 years hospitalized with STEMI and NSTEMI between 2011 and 2018 in the United States, Canada, England, the Netherlands, Taiwan, and Israel using administrative data. We compared females and males within each country with respect to age-standardized hospitalization rates, rates of cardiac catheterization, percutaneous coronary intervention, and coronary artery bypass graft surgery within 90 days of hospitalization, and 30-day age- and comorbidity-adjusted mortality.

          RESULTS:

          Hospitalization rates for STEMI and NSTEMI decreased between 2011 and 2018 in all countries, although the hospitalization rate ratio (rate in males/rate in females) increased in virtually all countries (eg, US STEMI ratio, 1.58:1 in 2011 and 1.73:1 in 2018; Israel NSTEMI ratio, 1.71:1 in 2011 and 2.11:1 in 2018). Rates of cardiac catheterization, percutaneous coronary intervention, and coronary artery bypass graft surgery were lower for females than males for STEMI in all countries and years (eg, US cardiac catheterization in 2018, 88.6% for females versus 91.5% for males; Israel percutaneous coronary intervention in 2018, 76.7% for females versus 84.8% for males) with similar findings for NSTEMI. Adjusted mortality for STEMI in 2018 was higher for females than males in 5 countries (the United States, Canada, the Netherlands, Israel, and Taiwan) but lower for females than males in 5 countries for NSTEMI.

          CONCLUSIONS:

          We observed a larger decline in acute myocardial infarction hospitalizations for females than males between 2011 and 2018. Females were less likely to receive cardiac interventions and had higher mortality after STEMI. Sex disparities seem to transcend borders, raising questions about the underlying causes and remedies.

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          Most cited references69

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          Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019

          Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019. Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019. Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost all countries outside high-income countries, and alarmingly, the age-standardized rate of CVD has begun to rise in some locations where it was previously declining in high-income countries. There is an urgent need to focus on implementing existing cost-effective policies and interventions if the world is to meet the targets for Sustainable Development Goal 3 and achieve a 30% reduction in premature mortality due to noncommunicable diseases.
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            2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation

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              Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

              Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define Charlson and Elixhauser comorbidities in administrative data and assess the performance of the resulting algorithms. ICD-10 coding algorithms were developed by "translation" of the ICD-9-CM codes constituting Deyo's (for Charlson comorbidities) and Elixhauser's coding algorithms and by physicians' assessment of the face-validity of selected ICD-10 codes. The process of carefully developing ICD-10 algorithms also produced modified and enhanced ICD-9-CM coding algorithms for the Charlson and Elixhauser comorbidities. We then used data on in-patients aged 18 years and older in ICD-9-CM and ICD-10 administrative hospital discharge data from a Canadian health region to assess the comorbidity frequencies and mortality prediction achieved by the original ICD-9-CM algorithms, the enhanced ICD-9-CM algorithms, and the new ICD-10 coding algorithms. Among 56,585 patients in the ICD-9-CM data and 58,805 patients in the ICD-10 data, frequencies of the 17 Charlson comorbidities and the 30 Elixhauser comorbidities remained generally similar across algorithms. The new ICD-10 and enhanced ICD-9-CM coding algorithms either matched or outperformed the original Deyo and Elixhauser ICD-9-CM coding algorithms in predicting in-hospital mortality. The C-statistic was 0.842 for Deyo's ICD-9-CM coding algorithm, 0.860 for the ICD-10 coding algorithm, and 0.859 for the enhanced ICD-9-CM coding algorithm, 0.868 for the original Elixhauser ICD-9-CM coding algorithm, 0.870 for the ICD-10 coding algorithm and 0.878 for the enhanced ICD-9-CM coding algorithm. These newly developed ICD-10 and ICD-9-CM comorbidity coding algorithms produce similar estimates of comorbidity prevalence in administrative data, and may outperform existing ICD-9-CM coding algorithms.
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                Author and article information

                Contributors
                Journal
                Circulation: Cardiovascular Quality and Outcomes
                Circ: Cardiovascular Quality and Outcomes
                Ovid Technologies (Wolters Kluwer Health)
                1941-7713
                1941-7705
                March 2024
                March 2024
                : 17
                : 3
                Affiliations
                [1 ]John Sealy School of Medicine, University of Texas Medical Branch, Galveston, TX (H.L., P.C.).
                [2 ]Department of Health Care Policy, Harvard Medical School, Boston, MA (L.A.H., C.F., G.W., B.E.L.).
                [3 ]Division of General Medicine, Beth Israel Deaconess Medical Center (L.A.H., B.E.L.).
                [4 ]George & Fay Yee Centre for Healthcare Innovation (S.A.-A., L.M.L.), University of Manitoba, Winnipeg, Canada.
                [5 ]Erasmus School of Health Policy & Management, Erasmus University, Rotterdam, the Netherlands (P.B., R.H., C.A.U.G.).
                [6 ]Institute of Health Informatics, University College London, United Kingdom (A.B., L.P.).
                [7 ]Consultant in Cardiology, University College London Hospitals, United Kingdom (A.B.).
                [8 ]Clinical Research Center, Soroka University Medical Center, Faculty of Health Sciences, Ben Gurion University of the Negev, Beersheba, Israel (N.B., M.G., V.N.).
                [9 ]Institute of Hospital and Health Care Administration, National Yang-Ming University, Taipei, Taiwan (Y.-C.C., N.H.).
                [10 ]ICES, Toronto, ON (D.T.K., F.Q., T.A.S., P.C.).
                [11 ]Schulich Heart Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada (D.T.K.).
                [12 ]Faculty of Medicine (D.T.K., P.C.), University of Toronto, ON, Canada.
                [13 ]Department of Community Health Sciences (L.M.L.), University of Manitoba, Winnipeg, Canada.
                [14 ]Institute for Health Management Policy and Evaluation (T.A.S.), University of Toronto, ON, Canada.
                Article
                10.1161/CIRCOUTCOMES.123.010144
                8e357f5d-6d81-425e-9550-c086d23baec1
                © 2024
                History

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