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中华肩肘外科电子杂志 ›› 2020, Vol. 08 ›› Issue (04) : 335 -339. doi: 10.3877/cma.j.issn.2095-5790.2020.04.008

所属专题: 文献

论著

肩关节镜手术患者术中低体温预测模型的构建及验证
吴晓舟1, 魏彦姝1, 闵玉娣1, 刘晓黎1,()   
  1. 1. 100044 北京大学人民医院手术室
  • 收稿日期:2020-09-13 出版日期:2020-11-05
  • 通信作者: 刘晓黎
  • 基金资助:
    北京大学人民医院研究发展基金(RDN2019-07)

Establishment and validation of a prediction equation to estimate risk of intraoperative hypothermia in patients undergoing shoulder arthroscopy

Xiaozhou Wu1, Yanshu Wei1, Yudi Min1, Xiaoli Liu1,()   

  1. 1. Central Operating Room, Peking University People's Hospital, Beijing 100044, China
  • Received:2020-09-13 Published:2020-11-05
  • Corresponding author: Xiaoli Liu
引用本文:

吴晓舟, 魏彦姝, 闵玉娣, 刘晓黎. 肩关节镜手术患者术中低体温预测模型的构建及验证[J]. 中华肩肘外科电子杂志, 2020, 08(04): 335-339.

Xiaozhou Wu, Yanshu Wei, Yudi Min, Xiaoli Liu. Establishment and validation of a prediction equation to estimate risk of intraoperative hypothermia in patients undergoing shoulder arthroscopy[J]. Chinese Journal of Shoulder and Elbow(Electronic Edition), 2020, 08(04): 335-339.

目的

构建肩关节镜手术患者术中低体温风险预测模型并检验其预测效果。

方法

选取2019年1月至2020年7月北京大学人民医院261例肩关节镜手术患者为研究对象,其中2019年1月至12月为建模组(n=174),2020年1月至7月为验证组(n=87),采用单因素分析筛选变量,通过Logistic回归建立模型,并进行Hosmer-Lemeshow拟合优度检验,采用受试者操作特征曲线下面积评价模型的预测效果。

结果

建模组患者术中低体温发生率为56.32%(98/174),验证组为42.53% (37/87);最终模型包括3个预测因子:基础体温(OR=0.033)、麻醉时间(OR=1.002)和BMI(OR=0.845)。Hosmer-Lemeshow检验P=0.377,AUC为0.858,Youden指数为0.603,灵敏度为0.735,特异度为0.868。模型验证显示正确率为83.84%。

结论

本研究构建的模型具有较好的预测效果,可为临床评估肩关节镜手术患者术中低体温风险提供参考。

Background

Inadvertent perioperative hypothermia, defined as a core body temperature lower than 36.0℃, is common in the perioperative period and may be associated with adverse effects. Shoulder arthroscopy is a well-established technique in dealing with a variety of shoulder disorders. During the operation, a large amount of irrigation fluid is required to ensure clear visibility. Considering the shoulder joint is quite close to the core body structure, the irrigation fluid temperature could adversely affect the core body temperature, resulting in hypothermia-related problems. Accurate risk assessment of individuals may help physicians identify patients at the risk of hypothermia and take preventive measures. However, there is no specific risk assessment tool for shoulder arthroscopy.

Objective

To establish a risk prediction model of intraoperative hypothermia in patients undergoing shoulder arthroscopy and to test its predictive effect.

Methods

From January 2019 to July 2020, a total of 261 patients were conveniently selected as study objects in our hospital. The patients who received shoulder arthroscopy were divided into the modeling group (January 2019 to December 2019, n=174) and the verification group (January 2020 to July 2020, n=87) . Variables were screened by univariate analysis, and the model was established by Logistic regression.Hosmer-Lemeshow goodness of fit test was carried out, and the area under the receiver operator characteristic curve was used to evaluate the predictive effect of the model.

Results

The incidence of intraoperative hypothermia was 56.32% (98/174) in the modeling group and 42.53% (37/87) in the verification group. The ultimate model included three predictors: basal body temperature (OR=0.033) , anesthesia duration (OR=1.002) and BMI (OR=0.845) . Hosmer-Lemeshow test: P=0.377, AUC: 0.858, Youden index: 0.603, sensitivity: 0.735, and specificity: 0.868. The accuracy of model verification is 83.84%.

Conclusion

The model established in this study has a good predictive effect and can provide a reference for clinical evaluation of intraoperative hypothermia in patients undergoing shoulder arthroscopy.

表1 建模组术中低体温的单因素分析
表2 Logistic回归自变量赋值表
表3 肩关节镜术中低体温二元Logistic回归分析(n=174)
图1 预测肩关节镜患者术中低体温的ROC曲线
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