ArticleESC heart failure2026
Predicting survival in patients with heart failure aged 80 years and older.
Article in ESC heart failure, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionConventional risk scoring systems for patients with heart failure are insufficient for accurately predicting outcomes in older patients. In this study, we aimed to develop a prognostic prediction model specifically for this population.
methodsA total of 5690 patients aged ≥80 years (median age: 86 years, 41.8% were men) from the JROADHF (The Japanese Registry of Acute Decompensated Heart Failure) were followed up for 3 years. A randomly selected 70% of the cohort (derivation cohort, n = 3983) was used to develop the risk prediction model, while the remaining 30% (validation cohort, n = 1707) was employed to evaluate its discriminative ability and calibration. Hazard ratios were estimated using the Cox proportional hazards model. Variables were selected using the backward elimination method (threshold: P < .001). The discrimination of the model was assessed by Harrell's C statistic, and the calibration was assessed by a calibration plot.
resultsDuring the follow-up period, a total of 2382 patients died. In the multivariable model, 11 variables, i.e. age, male sex, Barthel index, history of heart failure, systolic blood pressure, haemoglobin, albumin, blood urea nitrogen, b-type natriuretic peptide, sodium levels, and use of renin-angiotensin system inhibitors were selected from 31 potential risk factors. The developed model for predicting mortality at 3 years demonstrated acceptable discriminative ability (Harrell's C-statistic = 0.68, 95% confidence interval: 0.66-0.70) and calibration (Greenwood-Nam-D'Agostino test, P = .30).
conclusionThe prognostic model developed in this study (JROADHF over 80 Score) demonstrated satisfactory performance in predicting mortality in a cohort of older Japanese patients with heart failure. Estimating prognosis based on factors obtainable in routine clinical practice has the potential for widespread implementation in clinical settings.
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