Risk factors and their predictive efficacy for early postoperative infection in elderly patients with intertrochanteric femur fracture
10.3760/cma.j.cn501098-20250417-00230
- VernacularTitle:老年股骨转子间骨折患者术后早期感染危险因素及其预测效能
- Author:
Mingwei CHEN
1
;
Wenteng SI
;
Yali YU
;
Xiang LI
;
Shijun ZHAO
;
Aiguo WANG
Author Information
1. 郑州市骨科医院关节病科，郑州 450052
- Publication Type:Journal Article
- Keywords:
Femoral fractures;
Aged;
Infection;
Factor analysis
- From:
Chinese Journal of Trauma
2025;41(9):840-846
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the risk factors and their predictive efficacy for early postoperative infection in elderly patients with intertrochanteric femur fracture.Methods:A retrospective cohort study was conducted to analyze the clinical data of 286 elderly patients with intertrochanteric femur fracture admitted to Zhengzhou Orthopedic Hospital between August 2021 and August 2024, including 154 males and 132 females, aged 60-80 years [(72.5±5.8)years]. Fracture involved the left side in 148 patients and the right side in 138 patients. Internal fixation was performed on 214 patients and joint replacement on 72. Based on the occurrence of infection within two weeks postoperatively, the patients were divided into infection group ( n=25) and non-infection group ( n=261). Data were collected from the two groups, including basic information [gender, age, body mass index (BMI), cause of injury, fracture side], admission data (fasting blood glucose, diastolic blood pressure, systolic blood pressure), preoperative data [American Society of Anesthesiologists (ASA) classification, AO classification, serum C-reactive protein (CRP), serum albumin (Alb), serum CRP/Alb ratio, time from injury to surgery], and treatment-related information (surgical type, duration of surgery, intraoperative blood loss, quality of intraoperative reduction, postoperative antibiotic use). Univariate analysis and multivariate Logistic stepwise regression analysis were used to identify independent risk factors for early postoperative infection in elderly patients with intertrochanteric femur fracture. The receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated to evaluate the predictive efficacy of each factor. Results:Univariate analysis showed significant differences between the two groups in fasting blood glucose on admission, preoperative serum CRP, preoperative serum Alb, preoperative serum CRP/Alb ratio, and duration of surgery ( P<0.01). There were no significant differences between the two groups in the remaining variables ( P>0.05). Multivariate Logistic stepwise regression analysis indicated that fasting blood glucose on admission ( OR=2.65, 95% CI 1.32, 5.32, P<0.01), preoperative serum CRP ( OR=1.10, 95% CI 1.04, 1.18, P<0.01), preoperative serum Alb ( OR=0.79, 95% CI 0.70, 0.90, P<0.01), preoperative serum CRP/Alb ( OR=143.78, 95% CI 4.46, 46.77, P<0.01), and duration of surgery ( OR=1.07, 95% CI 1.02, 1.11, P<0.01) were significantly associated with early postoperative infection in elderly patients with intertrochanteric femur fracture. ROC curve analysis showed that the sensitivity and specificity of preoperative serum CRP/Alb in predicting early postoperative infection in elderly patients with intertrochanteric femur fracture were 88.00% and 88.10%, and that the AUC of preoperative serum CRP/Alb prediction was 0.92, significantly greater than the AUC predicted separately by fasting blood glucose at admission, preoperative serum CRP, preoperative serum Alb and duration of surgery (0.76, 0.75, 0.77, 0.76, respectively). The optimal cut-off value for the preoperative serum CRP/Alb ratio was 1.78. Conclusions:Fasting blood glucose on admission, preoperative serum CRP, Alb, CRP/Alb ratio, and duration of surgery are independent risk factors for early postoperative infection in elderly patients with intertrochanteric femur fracture. These factors all possess certain predictive value for early postoperative infection, but the preoperative serum CRP/Alb ratio demonstrates the best predictive efficacy.
