4.7 Article

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

Journal

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
Volume 293, Issue 5, Pages 572-580

Publisher

AMER MEDICAL ASSOC
DOI: 10.1001/jama.293.5.572

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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 (greater than or equal to43 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.

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