The Admit-AF risk score: A clinical risk score for predicting hospital admissions in patients with atrial fibrillation. (31st March 2020) - Meyre, Pascal; Aeschbacher, Stefanie; Blum, Steffen; Coslovsky, Michael; Beer, Jürg H; Moschovitis, Giorgio; Rodondi, Nicolas; Baretella, Oliver; Kobza, Richard; Sticherling, Christian; Bonati, Leo H; Schwenkglenks, Matthias; et al.
Abstract: Aims: To develop and externally validate a risk score for all-cause hospital admissions in patients with atrial fibrillation. Methods and results: We used a prospective cohort of 2387 patients with established atrial fibrillation as derivation cohort. Independent risk factors were selected from a broad range of variables using the least absolute shrinkage and selection operator method fit to a Cox model. The risk score was validated in a separate prospective cohort of 1300 atrial fibrillation patients. The incidence of all-cause hospital admission was 19.1 per 100 person-years in the derivation cohort and it was 26.1 per 100 person-years in the validation cohort. The most important predictors for admission were age (75–79 years: adjusted hazard ratio (aHR), 1.34; 95% confidence interval (CI), 1.01–1.78; 80–84 years: aHR, 1.50; 95% CI, 1.11–2.03; ≥85 years: aHR, 1.88; 95% CI, 1.36–2.62), prior pulmonary vein isolation (aHR, 0.72; 95% CI, 0.58–0.88), hypertension (aHR, 1.16; 95% CI, 0.99–1.36), diabetes (aHR, 1.38; 95% CI, 1.17–1.62), coronary heart disease (aHR, 1.17; 95% CI, 1.02–1.36), prior stroke/transient ischaemic attack (aHR, 1.26; 95% CI, 1.18–1.47), heart failure (aHR, 1.19; 95% CI, 1.03–1.39), peripheral artery disease (aHR, 1.35; 95% CI, 1.08–1.67), cancer (aHR, 1.33; 95% CI, 1.12–1.57), renal failure (aHR, 1.17; 95% CI, 0.99–1.37) and previous falls (aHR, 1.40; 95% CI, 1.13–1.74). A risk score with these variables was well calibrated, and achieved a C-index of 0.64 in the derivation and 0.59 in the validation cohort. Conclusions: Multiple risk factors were associated with hospital admissions in atrial fibrillation patients. This prediction tool selects high-risk patients who may benefit from preventive interventions.