Department of Anesthesiology, The Third Affiliated Hospital of Southern Medical University, 183 Zhongshan Avenue West, Tianhe District, Guangzhou City, Guangdong Province, China.
Department of Anesthesiology, The First People's Hospital of Foshan, Foshan, Guangdong Province, China.
BMC Anesthesiol. 2024 Sep 28;24(1):345. doi: 10.1186/s12871-024-02727-y.
This study is designed to identify risk factors of postoperative nausea and vomiting (PONV) in patients after gynecologic laparoscopic surgery and establish a nomogram model.
In this retrospective and multicenter study, we collected and analyzed data from 1233 patients who underwent gynecologic laparoscopic surgery. The Lasso algorithm was used to optimize the selection of independent variables in the development group. Multivariate logistic regression analysis was used to explore the risk factors of PONV to develop the predictive nomogram model. Finally, we used an internal and external verification group and machine learning (ML) to evaluate the accuracy and clinical applicability of the model.
The dosage of sufentanil in patient-controlled intravenous analgesia (PCIA), the dosage of remifentanil, the use of neostigmine, duration of surgery and the maximum value of the PCO were risk factors of PONV in patients after gynecologic laparoscopic surgery. In contrast, the dosage of propofol during the surgery and the use of steroids were protective factors. The nomogram was then established to predict the incidence of PONV in these patients based on the above eight indicators. The C-index of the development group, internal, and external verification groups are 0.802, 0.857, and 0.966, respectively.
A nomogram model was developed to predict the incidence of PONV in patients after gynecologic laparoscopic surgery. This model was found to be reliable and of high clinical value.
本研究旨在确定妇科腹腔镜手术后患者术后恶心呕吐（PONV）的风险因素，并建立列线图模型。
在这项回顾性多中心研究中，我们收集并分析了 1233 例接受妇科腹腔镜手术患者的数据。使用 Lasso 算法优化开发组中自变量的选择。多变量逻辑回归分析用于探讨 PONV 的风险因素，以开发预测列线图模型。最后，我们使用内部和外部验证组以及机器学习（ML）来评估模型的准确性和临床适用性。
患者自控静脉镇痛（PCIA）中舒芬太尼的剂量、瑞芬太尼的剂量、新斯的明的使用、手术持续时间和 PCO 的最大值是妇科腹腔镜手术后患者 PONV 的风险因素。相比之下，手术期间使用丙泊酚和使用类固醇是保护因素。然后根据上述 8 个指标建立了预测这些患者 PONV 发生率的列线图。开发组、内部和外部验证组的 C 指数分别为 0.802、0.857 和 0.966。
建立了预测妇科腹腔镜手术后患者 PONV 发生率的列线图模型。该模型被证明是可靠的，具有很高的临床价值。
