Wu Hongsheng, Ma Keqiang, Liao Biling, Ji Tengfei, Zheng Zongmin, Yan Yong, Yu Jiongbiao, Yu Haitao, Liu Yue, Zhou Yanyuan, Huang Guangrong, Gu Weili, Cao Tiansheng
Department of Hepatobiliary Pancreatic Surgery, Huadu District People's Hospital of Guangzhou, Guangzhou, China.
Department of General Surgery, Guangzhou Red Cross Hospital, Guangzhou, China.
Sci Rep. 2025 May 27;15(1):18481. doi: 10.1038/s41598-025-03687-0.
This study aimed to investigate risk factors associated with conversion from early laparoscopic cholecystectomy (ELC) to open cholecystectomy in patients diagnosed with acute calculous cholecystitis (ACC). A retrospective analysis was conducted on 3,191 ACC patients who underwent ELC at eight clinical centers between January 2013 and December 2023. To evaluate risk factors for conversion during ELC, least absolute shrinkage and selection operator (LASSO) regression with ten-fold cross-validation was employed to identify and select the most relevant variables. Subsequently, a binary logistic regression model was built using the variables selected from LASSO regression to develop a nomogram for prediction. The model's performance was evaluated using external validation through receiver operating characteristic (ROC) curves for discrimination, Hosmer-Lemeshow test and calibration curves for calibration, and decision curve analysis (DCA) for clinical practicality. LASSO regression analysis identified five optimal variables from a total of twenty-nine for model development: preoperative C-reactive protein (CRP) level, anesthesia American Society of Anesthesiologists (ASA) classification, calculus location, Tokyo Guidelines 2018 (TG18) classification, and surgeon seniority. External validation of the model using the area under the curve (AUC) from ROC curves yielded moderate discrimination in both the training set (AUC = 0.868) and validation set (AUC = 0.833). Calibration plots indicated good agreement between predicted and observed probabilities, suggesting good calibration of the nomogram. Additionally, DCA analysis supported the model's potential clinical usefulness. This study identified high preoperative CRP level, presence of gallbladder neck calculus, high grades in both anesthesia ASA and TG18 classifications, and junior surgeon as factors that can be used to predict the need for conversion to open surgery during ELC procedures for ACC patients.
本研究旨在调查急性结石性胆囊炎（ACC）患者早期腹腔镜胆囊切除术（ELC）转为开腹胆囊切除术的相关危险因素。对2013年1月至2023年12月期间在八个临床中心接受ELC的3191例ACC患者进行了回顾性分析。为评估ELC期间转为开腹手术的危险因素，采用最小绝对收缩和选择算子（LASSO）回归及十折交叉验证来识别和选择最相关变量。随后，使用从LASSO回归中选择的变量构建二元逻辑回归模型，以制定预测列线图。通过受试者工作特征（ROC）曲线进行鉴别、Hosmer-Lemeshow检验和校准曲线进行校准以及决策曲线分析（DCA）评估模型在临床实用性方面的性能，从而进行外部验证。LASSO回归分析从总共29个变量中确定了5个用于模型构建的最佳变量：术前C反应蛋白（CRP）水平、美国麻醉医师协会（ASA）麻醉分级、结石位置、2018年东京指南（TG18）分级和外科医生年资。使用ROC曲线下面积（AUC）对模型进行外部验证，结果显示在训练集（AUC = 0.868）和验证集（AUC = 0.833）中均具有中等鉴别能力。校准图表明预测概率与观察概率之间具有良好的一致性，提示列线图校准良好。此外，DCA分析支持该模型具有潜在的临床实用性。本研究确定，术前CRP水平高、存在胆囊颈部结石、ASA麻醉分级和TG18分级均为高级别以及外科医生年资低是可用于预测ACC患者ELC手术期间转为开腹手术必要性的因素。
