目的:探索基于二元 Logistics 回归模型分析机器人辅助子宫内膜癌患者术后并发症的危险因素。 方法:回顾性分析 2021 年 5 月—2022 年 5 月在空军军医大学第一附属医院收治的 96 例子宫内膜癌患者的临床资料, 根据手术方式将所有患者分为常规组(n=47)和机器人组(n=49),并比较两组患者并发症发生率。同时,经二元 Logistics 回归模型分析影响术后并发症的危险因素。结果:机器人组术后并发症发生率低于常规组(6.12% Vs 31.91%, P<0.05)。经二元 Logistic 回归模型分析,年龄 >60 岁、BMI>24 kg/m2 、术中出血量 >200 ml、有贫血史、常规手术是影 响患者术后出现并发症的独立危险因素(P<0.05)。利用 Bootstrap 法内验证,预测模型 AUC 为 0.818,特异性 71.8%, 灵敏性 77.8%,95% CI 0.720~0.917。结论:影响机器人辅助子宫内膜癌术后并发症的主要因素为贫血史、手术时间、 BMI、年龄、手术方式,针对合并此类危险因素的患者需采用相应的干预措施,从而降低患者术后并发症,改善预后。
Objective: To explore the risk factors for postoperative complications in patients underwent robot-assisted surgery for endometrial cancer based on binary Logistics regression model. Methods: Clinical data of 96 patients with endometrial cancer admitted to the First Affiliated Hospital of Air Force Military Medical University from May 2021 to May 2022 were retrospectively analyzed. All patients were divided into the conventional group (n=47) and robotic group (n=49) according to different surgical methods, and the complication rate of the two groups was compared. Meanwhile, the risk factors of postoperative complications were analyzed by binary Logistics regression model. Results: The incidence of postoperative complications in the robotic group was lower than that in the conventional group (6.12% Vs 31.91%, P<0.05). The binary Logistic regression analysis results showed that age>60 years old, BMI>24 kg/m2 , intraoperative blood loss>200 ml, history of anemia, and conventional operation were independent risk factors for postoperative complications (P<0.05). Using the Bootstrap method for internal validation, the AUC of the predicted model is 0.818, with specificity of 71.8%, sensitivity of 77.8%, and 95% CI of 0.720-0.917. Conclusion: The main factors affecting postoperative complications of robot-assisted surgery for endometrial cancer are anemia history, operative time, BMI, age, and operation approach. Therefore, appropriate intervention measures should be taken to reduce postoperative complications and improve prognosis of patients.
收稿日期:2023-12-04 录用日期:2024-02-19
Received Date: 2023-12-04 Accepted Date: 2024-02-19
基金项目:陕西省重点研发计划项目(2019SF-165);陕西省卫生健康科研基金项目(2018D068)
Foundation Item: Key R&D Program of Shaanxi Province (2019SF-165); Health Research Foundation of Shaanxi Province (2018D068)
通讯作者:王运萍,Email:164020733@qq.com
Corresponding Author: WANG Yunping, Email: 164020733@qq.com
引用格式:郭倩,徐佳,綦春蕾,等 . 基于二元 Logistics 回归模型分析机器人辅助子宫内膜癌术后并发症危险因素 [J]. 机器人外 科学杂志(中英文),2024,5(3):432-438.
Citation: GUO Q, XU J, QI C L, et al. Analysis of risk factors for postoperative complications in robot-assisted surgery for endometrial cancer based on a binary Logistics regression model [J]. Chinese Journal of Robotic Surgery, 2024, 5(3): 432-438.
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