Premium
The COACH risk engine: a multistate model for predicting survival and hospitalization in patients with heart failure
Author(s) -
Postmus Douwe,
Veldhuisen Dirk J.,
Jaarsma Tiny,
Luttik Marie Louise,
Lassus Johan,
Mebazaa Alexandre,
Nieminen Markku S.,
Harjola VeliPekka,
Lewsey James,
Buskens Erik,
Hillege Hans L.
Publication year - 2012
Publication title -
european journal of heart failure
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.149
H-Index - 133
eISSN - 1879-0844
pISSN - 1388-9842
DOI - 10.1093/eurjhf/hfr163
Subject(s) - medicine , heart failure , risk model , prognostic model , intensive care medicine , overall survival , risk analysis (engineering)
Aims Several models for predicting the prognosis of heart failure (HF) patients have been developed, but all of them focus on a single outcome variable, such as all‐cause mortality. The purpose of this study was to develop a multistate model for simultaneously predicting survival and HF‐related hospitalization in patients discharged alive from hospital after recovery from acute HF. Methods and results The model was derived in the COACH (Coordinating Study Evaluating Outcomes of Advising and Counseling in Heart Failure) cohort, a multicentre, randomized controlled trial in which 1023 patients were enrolled after hospitalization because of HF. External validation was attained with the FINN‐AKVA (Finish Acute Heart Failure Study) cohort, a prospective, multicentre study with 620 patients hospitalized due to acute HF. The observed vs. predicted 18‐month survival was 72.1% vs. 72.3% in the derivation cohort and 71.4% vs. 71.2% in the validation cohort. The corresponding values of the c statistic were 0.733 [95% confidence interval (CI) 0.705–0.761] and 0.702 (95% CI 0.663–0.744), respectively. The model's accuracy in predicting HF hospitalization was excellent, with predicted values that closely resembled the values observed in the derivation cohort. Conclusion The COACH risk engine accurately predicted survival and various measures of recurrent hospitalization in (acute) HF patients. It may therefore become a valuable tool in improving and personalizing patient care and optimizing the use of scarce healthcare resources.