Key points are not available for this paper at this time.
AIMS: We aimed to identify a 'frequent admitter' phenotype among patients admitted for acute decompensated heart failure (HF). METHODS AND RESULTS: We studied 10 363 patients in a population-based prospective HF registry (2008-2012), segregated into clusters based on their 3-year HF readmission frequency trajectories. Using receiver-operating characteristic analysis, we identified the index year readmission frequency threshold that most accurately predicts HF admission frequency clusters. Two clusters of HF patients were identified: a high frequency cluster (90.9%, mean 2.35 ± 3.68 admissions/year) and a low frequency cluster (9.1%, mean 0.50 ± 0.81 admission/year). An index year threshold of two admissions was optimal for distinguishing between clusters. Based on this threshold, 'frequent admitters', defined as patients with ≥ 2 HF admissions in the index year (n = 2587), were of younger age (68 ± 13 vs 69 ± 13 years), more often male (58% vs. 54%), smokers (38.4% vs. 34.4%) and had lower left ventricular ejection fraction (37 ± 17 vs. 41 ± 17%) compared to 'non-frequent admitters' (< 2 HF admissions in the index year; n = 7776) (all P < 0.001). Despite similar rates of advanced care utilization, frequent admitters had longer length of stay (median 4.3 vs. 4.0 days), higher annual inpatient costs (€ 7015 vs. € 2967) and higher all-cause mortality at 3 years compared to the non-frequent admitters (adjusted odds ratio 2.33, 95% confidence interval 2.11-2.58; P < 0.001). CONCLUSION: 'Frequent admitters' have distinct clinical characteristics and worse outcomes compared to non-frequent admitters. This study may provide a means of anticipating the HF readmission burden and thereby aid in healthcare resource distribution relative to the HF admission frequency phenotype.
Building similarity graph...
Analyzing shared references across papers
Loading...
Yun Yun Go
National Heart Centre Singapore
Reinhard Sellmair
Technical University of Munich
John Carson Allen
Duke-NUS Medical School
European Journal of Heart Failure
Karolinska Institutet
National University of Singapore
Technical University of Munich
Building similarity graph...
Analyzing shared references across papers
Loading...
Go et al. (Thu,) studied this question.
synapsesocial.com/papers/6a1e61ce28971e550d408f1a — DOI: https://doi.org/10.1002/ejhf.1348
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: