摘要
目的:探讨妇科恶性肿瘤全身麻醉患者出现围手术期意外低体温(IPH)的危险因素,并建立预测模型。方法:选取2022年6月至2023年12月我院收治的妇科恶性肿瘤全身麻醉手术患者420例,依据6∶4比例将患者分为建模集与验证集。收集患者一般人口学资料、既往病史、手术相关资料、实验室资料等,依据患者是否出现IPH分为IPH组、非IPH组。应用单因素及二元Logistic回归分析筛选妇科恶性肿瘤全身麻醉患者出现IPH的影响因素,通过R语言建立列线图预测模型,应用受试者工作特征(ROC)曲线、Hosmer-Lemeshow拟合优度检验与校准曲线评定模型区分度与校准能力,决策曲线判定模型临床有效性。结果:在建模集,单因素分析显示,IPH组年龄≥60岁占比、手术时间、麻醉时间、术中输液量、术中腹腔冲洗量高于非IPH组,体质指数、术前血细胞比容、术前血红蛋白水平低于非IPH组(P<0.05)。二元Logistic回归分析显示,年龄、手术时间、麻醉时间、术中输液量、术中腹腔冲洗量均为妇科恶性肿瘤全身麻醉手术患者出现IPH的危险因素,体质指数、术前血细胞比容为保护因素(P<0.05)。建模集的ROC曲线显示,列线图预测模型预测妇科恶性肿瘤全身麻醉手术患者出现IPH的曲线下面积(AUC)为0.927(0.894~0.960),验证集的ROC曲线显示,列线图预测模型的预测AUC为0.941(0.904~0.978),提示模型的区分度良好。建模集与验证集的Hosmer-Lemeshow拟合优度检验、校准曲线显示模型校准能力较好。决策曲线显示,模型具有良好临床净获益。结论:妇科恶性肿瘤全身麻醉患者出现IPH的影响因素包括年龄、体质指数、手术时间、麻醉时间、术中输液量、术中腹腔冲洗量、术前血细胞比容,且据此建立的预测模型预测性能与临床实用性良好。
Objective:To investigate the risk factors for inadvertent perioperative hypothermia(IPH)in gynecological malignancy patients under general anesthesia and establish a prediction model.Methods:A total of 420 gynecological malignancy patients who underwent surgery under general anesthesia at our hospital from June 2022 to December 2023 were selected and divided into modeling set and validation set at a ratio of 6∶4.General demographic data,past medical history,surgery-related information,laboratory findings,and other data were collected.Patients were classified into IPH group and non-IPH group based on whether IPH occurred.Univariate and binary Logistic regression analyses were used to screen for influencing factors of IPH in gynecological malignancy patients under general anesthesia.A nomogram prediction model was established using R language,and its discriminative ability and calibration were evaluated using receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve.Decision curve analysis was used to determine the clinical effectiveness of the model.Results:In the modeling set,univariate analysis showed that the IPH group had higher proportions of age≥60 years,longer operation time,longer anesthesia time,larger intraoperative fluid infusion volume,and larger intraoperative peritoneal lavage volume compared with the non-IPH group,while body mass index,preoperative hematocrit,and preoperative hemoglobin levels were lower(P<0.05).Binary Logistic regression analysis showed that age,operation time,anesthesia time,intraoperative fluid infusion volume,and intraoperative peritoneal lavage volume were risk factors for IPH in gynecological malignancy patients under general anesthesia,while body mass index and preoperative hematocrit were protective factors(P<0.05).The ROC curve of the modeling set showed that the area under the curve(AUC)of the nomogram prediction model was 0.927(0.894-0.960),and the ROC curve of the validation set showed that the AUC was 0.941(0.904-0.978),indicating good discriminative ability of the model.The Hosmer-Lemeshow goodness-of-fit test and calibration curve of both modeling and validation sets showed good calibration ability of the model.Decision curve analysis showed that the model had good clinical net benefit.Conclusion:The influencing factors for IPH in gynecological malignancy patients under general anesthesia included age,body mass index,operation time,anesthesia time,intraoperative fluid infusion volume,intraoperative peritoneal lavage volume,and preoperative hematocrit.Based on these factors,the prediction model was established and demonstrated good predictive performance and clinical utility.
作者
包明雪
刘双源
BAO Mingxue;LIU Shuangyuan(Department of Anesthesia and Perioperative Medicine,Jiangsu Provincial People's Hospital,Nanjing 210029,China)
出处
《现代医学》
2025年第5期821-828,共8页
Modern Medical Journal
关键词
妇科
恶性肿瘤
全身麻醉
围手术期意外低体温
危险因素
预测模型
gynecology
malignant tumor
general anesthesia
inadvertent perioperative hypothermia
risk factors
prediction model
