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Walk the Even Hospital Database by book and chapter — the raw source passages that ground Ask, DDx, and the rest.

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abstractpubmed· Abstract· item 41206900

Coronary Computed Tomography Angiography in Prediction of First Coronary Events. IMPORTANCE: Risk stratification strategies in primary prevention of coronary events lack precision. OBJECTIVE: To determine whether prediction of first coronary events is improved by adding information on coronary atherosclerosis from coronary computed tomography angiography (CCTA) to a model using the pooled cohort equation (PCE) risk score tool and the coronary artery calcification score (CACS). DESIGN, SETTING, AND PARTICIPANTS: Observational cohort study including individuals aged 50 to 64 years randomly recruited from the general population and examined at 6 university hospitals in Sweden from 2013 to 2018, with a median follow-up of 7.8 years. A sample of 30 154 individuals underwent cardiopulmonary imaging, physical examinations, routine laboratory tests, questionnaires, and/or functional tests. This study included 24 791 individuals without previous cardiovascular disease for whom high-quality CCTA images were available. Events were followed up via registers until September 2024. EXPOSURES: The information used from the CCTA images was the extent of coronary atherosclerosis (segment involvement score), presence of noncalcified atherosclerosis, and presence of coronary obstructive disease (stenosis ≥50%). MAIN OUTCOMES AND MEASURES: The outcome was a composite of first occurrence of nonfatal myocardial infarction or death from coronary heart disease. RESULTS: During follow-up, 304 coronary events occurred. Segment involvement scores of 3 to 4 and greater than 4 and presence of noncalcified atherosclerosis were associated with hazard ratios of 2.71 (95% CI, 1.34-5.44), 5.27 (95% CI, 2.50-11.07), and 1.66 (95% CI, 1.23-2.22), respectively. In a model based on the PCE and CACS, CCTA-derived data improved risk discrimination (C statistic improved from 0.764 to 0.779; P = .004) and risk reclassification (net reclassification improvement of 0.133 [95% CI, 0.031-0.165]), conferred a net correct upward reclassification of 14.2% in those with events and incorrectly classified 1.6% of participants not experiencing an event into a higher-risk category. Because of the low event rate in the cohort, reclassification mainly occurred in the group classified as at low risk (<5%) according to the PCE. CONCLUSIONS AND RELEVANCE: Information on coronary atherosclerosis from CCTA modestly improved risk prediction beyond traditional risk factors and CACS in identifying individuals at risk of coronary events and in need of primary prevention.