PT  - JOURNAL ARTICLE
AU  - Vinter, Nicklas
AU  - Gerds, Thomas Alexander
AU  - Cordsen, Pia
AU  - Valentin, Jan Brink
AU  - Lip, Gregory Y H
AU  - Benjamin, Emelia J J
AU  - Johnsen, Søren Paaske
AU  - Frost, Lars
TI  - Development and validation of prediction models for incident atrial fibrillation in heart failure
AID  - 10.1136/openhrt-2022-002169
DP  - 2023 Jan 01
TA  - Open Heart
PG  - e002169
VI  - 10
IP  - 1
4099  - http://openheart.bmj.com/content/10/1/e002169.short
4100  - http://openheart.bmj.com/content/10/1/e002169.full
SO  - Open Heart2023 Jan 01; 10
AB  - Objectives Accurate prediction of heart failure (HF) patients at high risk of atrial fibrillation (AF) represents a potentially valuable tool to inform shared decision making. No validated prediction model for AF in HF is currently available. The objective was to develop clinical prediction models for 1-year risk of AF.Methods Using the Danish Heart Failure Registry, we conducted a nationwide registry-based cohort study of all incident HF patients diagnosed from 2008 to 2018 and without history of AF. Administrative data sources provided the predictors. We used a cause-specific Cox regression model framework to predict 1-year risk of AF. Internal validity was examined using temporal validation.Results The population included 27 947 HF patients (mean age 69 years; 34% female). Clinical experts preselected sex, age at HF, NewYork Heart Association (NYHA) class, hypertension, diabetes mellitus, chronic kidney disease, obstructive sleep apnoea, chronic obstructive pulmonary disease and myocardial infarction. Among patients aged 70 years at HF, the predicted 1-year risk was 9.3% (95% CI 7.1% to 11.8%) for males and 6.4% (95% CI 4.9% to 8.3%) for females given all risk factors and NYHA III/IV, and 7.5% (95% CI 6.7% to 8.4%) and 5.1% (95% CI 4.5% to 5.8%), respectively, given absence of risk factors and NYHA class I. The area under the curve was 65.7% (95% CI 63.9% to 67.5%) and Brier score 7.0% (95% CI 5.2% to 8.9%).Conclusion We developed a prediction model for the 1-year risk of AF. Application of the model in routine clinical settings is necessary to determine the possibility of predicting AF risk among patients with HF more accurately and if so, to quantify the clinical effects of implementing the model in practice.Data may be obtained from a third party and are not publicly available. Permission to access the data used on this study can be obtained following approval from the Danish Health Authority.