In:
Circulation, Ovid Technologies (Wolters Kluwer Health), Vol. 142, No. Suppl_3 ( 2020-11-17)
Abstract:
Objective: This is a large prospective study aimed to develop risk prediction models of CVD and all-cause mortality in patients who survived MI. Methods: Using 2002-2012 national electronic health record data from the Veterans Health Administration, sex-specific risk prediction models for CVD and all-cause death were developed from the 5-year follow-up data of 100,601 first MI survivors aged 〉 30 years. Model performance was evaluated using a 5-fold cross-validation approach. Results: We followed 98,657 male and 1,944 female MI survivors up to 5 years (407,199 person-years). There were 31,622 deaths (men 31,147, women 475) and 12,901 CVD deaths (men 12,752, women 149) observed during follow up. Among men, greater age, current smoking, diabetes, atrial fibrillation, heart failure, peripheral artery disease, geographic region, and lower BMI ( 〈 20kg/m 2 ) were associated with increased risk of subsequent CVD and all-cause-mortality, while statin treatment, hypertension medication, beta-blocker, eGFR level, and high BMI (≥25 kg/m 2 ) were significantly associated with reduced risk of CVD and all-cause-mortality. Similar associations were generally observed among women. We observed U-shaped relations between total cholesterol and outcomes, and HDL cholesterol and outcomes. The prediction models demonstrated good discrimination and calibration. The estimated Harrell’s C-statistics of the final models versus the cross-validation estimates were similar, ranging from 0.75 to 0.81. The predicted risk of death was well-calibrated compared to observed risk. Conclusions: We developed and validated risk prediction models of 5-year risk for CVD and all-cause death for patients following MI. Traditional risk factors, co-morbidity, lack of blood pressure or lipid treatment, and geographic region were all associated with greater risk of CVD and all-cause mortality.
Type of Medium:
Online Resource
ISSN:
0009-7322
,
1524-4539
DOI:
10.1161/circ.142.suppl_3.15663
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2020
detail.hit.zdb_id:
1466401-X
