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Background There is a paucity of contemporary data estimating the incidence of major adverse cardiovascular events (MACE) in patients with established atherosclerotic disease or multiple risk factors managed in routine practice. We estimated 1- and 4-year incidences of MACE and the association between MACE and vascular beds affected in these patients. Methods and Results Using US IBM MarketScan data from January 1, 2013 to December 31, 2017, we identified patients ≥45 years old with established coronary artery disease, cerebrovascular disease, peripheral artery disease, or the presence of ≥3 risk factors for atherosclerosis during 2013 with a minimum of 4 years of follow-up. We calculated 1- and 4-year incidences of MACE (cardiovascular death or hospitalization for myocardial infarction or ischemic stroke). A Cox proportional hazards regression model adjusted for age and sex was used to evaluate the association between vascular bed number/location(s) affected and MACE. We identified 1 302 856 patients with established atherosclerotic disease or risk factors for atherosclerosis. Coronary artery disease was present in 16.9% of patients, cerebrovascular disease in 7.6%, peripheral artery disease in 13.6%, and risk factors for atherosclerosis only in 66.0%. The 1- and 4-year incidences of MACE were 1.4% and 6.9%, respectively. At 4 years, MACE was more frequent in patients with atherosclerotic disease in a single (hazard ratio=1.51, 95% CI=1.48-1.55), 2-(hazard ratio=2.35, 95% CI=2.27-2.44), or all 3 vascular beds (hazard ratio=3.30, 95% CI=2.97-3.68) compared with having risk factors for atherosclerosis. Conclusions Patients with established atherosclerotic disease or who have multiple risk factors and are treated in contemporary, routine practice carry a substantial risk for MACE at 1- and 4- years of follow-up. MACE risk was shown to vary based on the number and location of vascular beds involved.
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http://dx.doi.org/10.1161/JAHA.119.014402 | DOI Listing |
World J Pediatr Congenit Heart Surg
September 2025
Postgraduate Program in Health Sciences, Medical School, Federal University of Amazonas (UFAM), Manaus, Amazonas, Brazil.
To analyze in-hospital mortality in children undergoing congenital heart interventions in the only public referral center in Amazonas, North Brazil, between 2014 and 2022. This retrospective cohort study included 1041 patients undergoing cardiac interventions for congenital heart disease, of whom 135 died during hospitalization. Records were reviewed to obtain demographic, clinical, and surgical data.
View Article and Find Full Text PDFJAMA Netw Open
September 2025
Social and Behavioral Sciences Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland.
Importance: Higher intellectual abilities have been associated with lower mortality risk in several longitudinal cohort studies. However, these studies did not fully account for early life contextual factors or test whether the beneficial associations between higher neurocognitive functioning and mortality extend to children exposed to early adversity.
Objective: To explore how the associations of child neurocognition with mortality changed according to the patterns of adversity children experienced.
Int J Surg
September 2025
Department of Gynecology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.
Background: Ovarian cancer remains the most lethal gynecological cancer, with fewer than 50% of patients surviving more than five years after diagnosis. This study aimed to analyze the global epidemiological trends of ovarian cancer from 1990 to 2021 and also project its prevalence to 2050, providing insights into these evolving patterns and helping health policymakers use healthcare resources more effectively.
Methods: This study comprehensively analyzes the original data related to ovarian cancer from the GBD 2021 database, employing a variety of methods including descriptive analysis, correlation analysis, age-period-cohort (APC) analysis, decomposition analysis, predictive analysis, frontier analysis, and health inequality analysis.