PURPOSE: The purposes of this study are to identify the strongest clinical parameters in relation to in-hospital mortality, which are available in the earliest phase of the hospitalization of patients, and to create an easy tool for the early identification of patients at risk. MATERIALS AND METHODS: The classification and regression tree analysis was applied to data from the Acute Heart Failure Database-Main registry comprising patients admitted to specialized cardiology centers with all syndromes of acute heart failure. The classification model was built on derivation cohort (n = 2543) and evaluated on validation cohort (n = 1387). RESULTS: The classification tree stratifies patients according to the presence of cardiogenic shock (CS), the level of creatinine, and the systolic blood pressure (SBP) at admission into the 5 risk groups with in-hospital mortality ranging from 2.8% to 66.2%. Patients without CS and creatinine level of 155 μmol/L or less were classified into very-low-risk group; patients without CS, creatinine level greater than 155 μmol/L, and SBP greater than 103 mm Hg, into low-risk group, whereas patients without CS, creatinine level greater than 155 μmol/L, and SBP of 103 mm Hg or lower, into intermediate-risk group. The high-risk group patients had CS and creatinine of 140 μmol/L or less; patients with CS and creatinine level greater than 140 μmol/L belong to very-high-risk group. The area under receiver operating characteristic curve was 0.823 and 0.832, and the value of Brier's score was estimated on level 0.091 and 0.084, for the derivation and the validation cohort, respectively. CONCLUSIONS: The presented classification model effectively stratified patients with all syndromes of acute heart failure into in-hospital mortality risk groups and might be of advantage for clinical practice.

Institute of Biostatistics and Analyses Faculty of Medicine Masaryk University Kamenice 126 3 625 00 Brno Czech Republic

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