Development and validation of prediction models for incident atrial fibrillation in heart failure.

Vinter, Nicklas ORCID: 0000-0003-0558-8483, Gerds, Thomas Alexander ORCID: 0000-0002-5955-816X, Cordsen, Pia, Valentin, Jan Brink ORCID: 0000-0002-8205-7179, Lip, Gregory YH ORCID: 0000-0002-7566-1626, Benjamin, Emelia JJ, Johnsen, Søren Paaske ORCID: 0000-0002-2787-0271 and Frost, Lars ORCID: 0000-0001-9215-9796 (2023) Development and validation of prediction models for incident atrial fibrillation in heart failure. Open heart, 10 (1). e002169-.

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Official URL: http://dx.doi.org/10.1136/openhrt-2022-002169

Abstract

<h4>Objectives</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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%).<h4>Conclusion</h4>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.

Item Type:	Article
Uncontrolled Keywords:	Heart, Humans, Atrial Fibrillation, Risk Factors, Cohort Studies, Aged, Female, Male, Heart Failure
Divisions:	Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences
Depositing User:	Symplectic Admin
Date Deposited:	29 Sep 2023 10:50
Last Modified:	18 Mar 2024 03:31
DOI:	10.1136/openhrt-2022-002169
Open Access URL:	http://dx.doi.org/10.1136/openhrt-2022-002169
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3173218