Predicting Early Mortality After Hip Fracture Surgery: The Hip Fracture Estimator of Mortality Amsterdam
- PMID: 28906306
- DOI: 10.1097/BOT.0000000000001025
Predicting Early Mortality After Hip Fracture Surgery: The Hip Fracture Estimator of Mortality Amsterdam
Abstract
Objectives: Early mortality after hip fracture surgery is high and preoperative risk assessment for the individual patient is challenging. A risk model could identify patients in need of more intensive perioperative care, provide insight in the prognosis, and allow for risk adjustment in audits. This study aimed to develop and validate a risk prediction model for 30-day mortality after hip fracture surgery: the Hip fracture Estimator of Mortality Amsterdam (HEMA).
Methods: Data on 1050 consecutive patients undergoing hip fracture surgery between 2004 and 2010 were retrospectively collected and randomly split into a development cohort (746 patients) and validation cohort (304 patients). Logistic regression analysis was performed in the development cohort to determine risk factors for the HEMA. Discrimination and calibration were assessed in both cohorts using the area under the receiver operating characteristic curve (AUC), the Hosmer-Lemeshow goodness-of-fit test, and by stratification into low-, medium- and high-risk groups.
Results: Nine predictors for 30-day mortality were identified and used in the final model: age ≥85 years, in-hospital fracture, signs of malnutrition, myocardial infarction, congestive heart failure, current pneumonia, renal failure, malignancy, and serum urea >9 mmol/L. The HEMA showed good discrimination in the development cohort (AUC = 0.81) and the validation cohort (AUC = 0.79). The Hosmer-Lemeshow test indicated no lack of fit in either cohort (P > 0.05).
Conclusions: The HEMA is based on preoperative variables and can be used to predict the risk of 30-day mortality after hip fracture surgery for the individual patient.
Level of evidence: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.
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