Predictors for mortality after lower-extremity amputations in geriatric patients

Background: The identification of independent predictors for operative and long-term mortality after lower-extremity amputations in the geriatric Population would allow targeted management for high-risk patients and appropriate allocation of resources. Methods: Univariate and multivariate logistic regression analyses were used to identify independent predictors for operative mortality. Life tables and Kaplan-Meier Survival Curves were generated. Independent predictors for long-term mortality were tested by log-rank test followed by Cox regression analysis. Results: Female gender, congestive heart failure, and high-level amputation were identified as independent predictors for operative mortality (odds ratios 4.14, 4.59, and 4.77, respectively). The logistic regression model showed good calibration and discriminative power. Female gender, high-level amputation, cerebrovascular accident. congestive heart failure, noncommunity ambulation, and institutionalization before amputation were associated with an increased risk for long-term mortality. However, only high-level amputation, congestive heart failure, and noncommunity ambulation remained as independent risk factors after Cox regression analysis (relative risks 1.68, 2.08. and 2.10, respectively). Conclusions: Extra care should be given to patients identified with independent predictors for operative and long-term mortality. (c) 2006 Excerpta Medica Inc. All rights reserved.