大出血患者术后手术部位感染的危险因素及预测模型
Risk factors and predictive models for postoperative surgical site infection in patients with massive hemorrhage.
作者信息
Zheng Wei-Chao, Bai Yang, Ge Jian-Lei, Lv Lei-Shuai, Zhao Bin, Wang Hong-Li, Zhang Li-Min
机构信息
Department of Anesthesiology, Hebei Province Cangzhou Hospital of Integrated Traditional and Western Medicine, Cangzhou, China.
Hebei Key Laboratory of Integrated Traditional and Western Medicine in Osteoarthrosis Research (Preparing), China.
出版信息
J Orthop. 2024 Aug 11;69:61-67. doi: 10.1016/j.jor.2024.08.005. eCollection 2025 Nov.
BACKGROUND
This study aimed to identify risk factors associated with postoperative surgical site infection (SSI) in patients experiencing massive hemorrhage and develop a predictive model.
METHODS
A retrospective analysis of 121 orthopedic surgery patients and experienced massive hemorrhage was conducted. According to postoperative SSI occurrence, the patients were divided into two groups: the infection group (n = 12) and the non-infection group (n = 109). Clinical data were collected, and a predictive model was developed using logistic regression analysis in patients with massive hemorrhage.
RESULTS
Independent risk factors for postoperative SSI included ASA grade, urine volume, and type 2 diabetes. An area under the curve for the prediction of postoperative SSI based on the Receiver Operating Characteristic (ROC) curve for the risk score was 0.916.
CONCLUSIONS
Patients with a urine volume of ≥3.49 ml/kg/h, higher ASA grade, and type 2 diabetes are at an increased risk of developing postoperative SSI after experiencing massive hemorrhage.
LEVEL OF EVIDENCE
Level III.
背景
本研究旨在确定大量出血患者术后手术部位感染（SSI）的相关危险因素，并建立一个预测模型。
方法
对121例经历大量出血的骨科手术患者进行回顾性分析。根据术后SSI的发生情况，将患者分为两组：感染组（n = 12）和非感染组（n = 109）。收集临床数据，并使用逻辑回归分析为大量出血患者建立预测模型。
结果
术后SSI的独立危险因素包括美国麻醉医师协会（ASA）分级、尿量和2型糖尿病。基于风险评分的受试者工作特征（ROC）曲线预测术后SSI的曲线下面积为0.916。
结论
尿量≥3.49 ml/kg/h、ASA分级较高和患有2型糖尿病的患者在经历大量出血后发生术后SSI的风险增加。
证据级别
三级。
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