Abstract

Background: Neck of femur fractures have a high incidence in old people, and they come together with a high mortality rate. Nottingham Hip Fracture Score (NHFS) was validated as a tool to predict the mortality in patients with a hip fracture. Methods: The predictive capability of NHFS for 30-day mortality for Greek patients who had an operation on a neck of femur fracture was assessed, and then the original NHFS model was compared to a modified one. Practically, we performed the NHFS to the Greek population, and at the same time, we implemented a modified model of the NHFS by replacing the institution with the New Mobility Score (NMS) (Parker and Palmer, 1993) to the evaluated parameters. From April 2009 to November 2012, we ran a prospective study in our institution, collecting full details from 349 patients. We used Statistical Package for Social Sciences (SPSS), version 20 to analyze data. Univariate logistic regression analysis was utilized for expressing the significance, and the odds ratio for every risk factor participated in our research. Multinomial logistic regression analysis was used for predicting statistical indexes for finding the suitability between two important models consisted of just about the same risk factors. Results: Only 85 (24.4%) of a total of 349 patients (average age 80, 82 years) were men. Follow-up for all patients was at least 30 days. NHFS and modified NHFS predictability were compared with the actual mortality rate of the patients. NMS, Admission Abbreviated Mental Test score (AMTS), Sex, Age, and malignancy were found to be the most important individual factors in hip fracture 30-day mortality. We found both the original and the modified NHFS significant predictors of 30-day mortality, but the modified one with the NMS was better for the Greek population. Conclusions: NHFS is a useful tool to predict the mortality in elderly patients with a neck of femur fracture. Replacing the parameter institution with the NMS improves the predictive capacity of the NHFS to the Greek population.

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