A logistic regression model incorporating age, medication history, cognitive performance, albumin, and hematocrit can predict the risk of postoperative delirium in elderly patients undergoing hip fracture surgery.
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May support preoperative risk stratification in elderly hip fracture patients; leaves open prospective validation before clinical adoption.
Background: Delirium in elderly patients with hip fracture has a significant negative influence on the disease course. Awareness of risk factors for postoperative delirium (POD) may lead to the development of effective preventive strategies. The aims of this study were: to find patients’ features that are predictors of POD, and; to develop a model predicting the risk for POD. Patients and methods: Seventy‐seven elderly patients (81.9 years of age, SD 7.5 years) were non‐delirious prior to surgery and enrolled in the study. Delirium was diagnosed by Confusion Assessment Method and Algorrhithm. Patients’ characteristics as potential predictors of POD were analyzed by logistic regression analysis on SAS software. Results: Postoperative delirium was diagnosed in 37 patients. Use of multiple (>3) medications, lower scores on cognitive tests (<20 on Set Test and <24 on Mini‐mental Status Exam), albumin level less than 3.5 g/dL, hematocrit level less than 33% and age over 81 years were predictors of POD. A logistic regression formula including these predictors weighed by their parameter estimates can be used to calculate the probability of POD. The model had a good fit and a good predictive power. A Delirium Predicting Scale was derived based on parameter estimates of these predictors. Patients can be classified as low‐, intermediate‐ or high‐risk for POD. Conclusions: A logistic regression model, which includes patients’ age, medication history, cognitive performance measured by Set Test and Mini‐Mental Status Exam, albumin and hematocrit levels, can be used to predict risk for POD after surgical repair of fractured hip in elderly patients.
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Goldenberg et al. (2006) studied this question.
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