In:
Open Heart, BMJ, Vol. 8, No. 1 ( 2021-01), p. e001459-
Abstract:
To validate a multivariable risk prediction model (Cohorts for Heart and Aging Research in Genomic Epidemiology model for atrial fibrillation (CHARGE-AF)) for 5-year risk of atrial fibrillation (AF) in routinely collected primary care data and to assess CHARGE-AF’s potential for automated, low-cost selection of patients at high risk for AF based on routine primary care data. Methods We included patients aged ≥40 years, free of AF and with complete CHARGE-AF variables at baseline, 1 January 2014, in a representative, nationwide routine primary care database in the Netherlands (Nivel-PCD). We validated CHARGE-AF for 5-year observed AF incidence using the C-statistic for discrimination, and calibration plot and stratified Kaplan-Meier plot for calibration. We compared CHARGE-AF with other predictors and assessed implications of using different CHARGE-AF cut-offs to select high-risk patients. Results Among 111 475 patients free of AF and with complete CHARGE-AF variables at baseline (17.2% of all patients aged ≥40 years and free of AF), mean age was 65.5 years, and 53% were female. Complete CHARGE-AF cases were older and had higher AF incidence and cardiovascular comorbidity rate than incomplete cases. There were 5264 (4.7%) new AF cases during 5-year follow-up among complete cases. CHARGE-AF’s C-statistic for new AF was 0.74 (95% CI 0.73 to 0.74). The calibration plot showed slight risk underestimation in low-risk deciles and overestimation of absolute AF risk in those with highest predicted risk. The Kaplan-Meier plot with categories 〈 2.5%, 2.5%–5% and 〉 5% predicted 5-year risk was highly accurate. CHARGE-AF outperformed CHA 2 DS 2 -VASc (Cardiac failure or dysfunction, Hypertension, Age 〉 =75 [Doubled], Diabetes, Stroke [Doubled] -Vascular disease, Age 65-74, and Sex category [Female]) and age alone as predictors for AF. Dichotomisation at cut-offs of 2.5%, 5% and 10% baseline CHARGE-AF risk all showed merits for patient selection in AF screening efforts. Conclusion In patients with complete baseline CHARGE-AF data through routine Dutch primary care, CHARGE-AF accurately assessed AF risk among older primary care patients, outperformed both CHA 2 DS 2 -VASc and age alone as predictors for AF and showed potential for automated, low-cost patient selection in AF screening.
Type of Medium:
Online Resource
ISSN:
2053-3624
DOI:
10.1136/openhrt-2020-001459
Language:
English
Publisher:
BMJ
Publication Date:
2021
detail.hit.zdb_id:
2747269-3
