Risk stratification for in-hospital mortality in acutely decompensated heart failure: Classification and regression tree analysis

Gregg C. Fonarow*, Kirkwood F. Adams, William T. Abraham, Clyde W. Yancy, W. John Boscardin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1192 Scopus citations


Context: Estimation of mortality risk in patients hospitalized with acute decompensated heart failure (ADHF) may help clinicians guide care. Objective: To develop a practical user-friendly bedside tool for risk stratification for patients hospitalized with ADHF. Design, Setting, and Patients: The Acute Decompensated Heart Failure National Registry (ADHERE) of patients hospitalized with a primary diagnosis of ADHF in 263 hospitals in the United States was queried with analysis of patient data to develop a risk stratification model. The first 33 046 hospitalizations (derivation cohort; October 2001-February 2003) were analyzed to develop the model and then the validity of the model was prospectively tested using data from 32 229 subsequent hospitalizations (validation cohort; March-July 2003). Patients had a mean age of 72.5 years and 52% were female. Main Outcome Measure: Variables predicting mortality in ADHF. Results: When the derivation and validation cohorts are combined, 37 772 (58%) of 65 275 patient-records had coronary artery disease. Of a combined cohort consisting of 52 164 patient-records, 23 910 (46%) had preserved left ventricular systolic function. In-hospital mortality was similar in the derivation (4.2%) and validation (4.0%) cohorts. Recursive partitioning of the derivation cohort for 39 variables indicated that the best single predictor for mortality was high admission levels of blood urea nitrogen (≥43 mg/dL [15.35 mmol/L]) followed by low admission systolic blood pressure (<115 mm Hg) and then by high levels of serum creatinine (≥2.75 mg/dL [243.1 μmol/L]). A simple risk tree identified patient groups with mortality ranging from 2.1% to 21.9%. The odds ratio for mortality between patients identified as high and low risk was 12.9 (95% confidence interval, 10.4-15.9) and similar results were seen when this risk stratification was applied prospectively to the validation cohort. Conclusions: These results suggest that ADHF patients at low, intermediate, and high risk for in-hospital mortality can be easily identified using vital sign and laboratory data obtained on hospital admission. The ADHERE risk tree provides clinicians with a validated, practical bedside tool for mortality risk stratification.

Original languageEnglish (US)
Pages (from-to)572-580
Number of pages9
JournalJournal of the American Medical Association
Issue number5
StatePublished - Feb 2 2005

ASJC Scopus subject areas

  • Medicine(all)


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