Abstract

Several mortality-predicting tools for hip fracture patients are available, but all consist of a high number of variables, require a time-consuming evaluation and/or are difficult to calculate. The aim of this study was to develop and validate an easy-to-use score, which depends mostly on routine data. Patients from the Registry for Geriatric Trauma were divided into a development and a validation group. Logistic regression models were used to build a model for in-house mortality and to obtain a score. Candidate models were compared using Akaike information criteria (AIC) and likelihood ratio tests. The quality of the model was tested using the area under the curve (AUC) and the Hosmer-Lemeshow test. 38,570 patients were included, almost equal distributed to the development and to the validation dataset. The AUC was 0.727 (95% CI 0.711 - 0.742) for the final model, AIC resulted in a significant reduction in deviance compared to the basic model, and the Hosmer-Lemeshow test showed no significant lack of fit (p = 0.07). The GeRi-Score predicted an in-house mortality of 5.3% vs. 5.3% observed mortality in the development dataset and 5.4% vs. 5.7% in the validation dataset. The GeRi-Score was able to distinguish between mild, moderate and high risk groups. The GeRi-Score is an easy-to-use mortality-predicting tool with an acceptable discrimination and no significant lack of fit. The GeRi-Score might have the potential to distribute the intensity of perioperative medical care in hip fracture surgery and can be used in quality management programs as benchmark tool.

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