周熠 1谢建森 1陈世荣 1张绪锋 1黄宜锋 1高恒毅 1贺更生1
作者信息
- 1. 深圳市龙华区人民医院肝胆胰外科,广东 深圳 518000
- 折叠
摘要
Abstract
Objective To establish a nomogram model for predicting complicated cholecystitis in patients with gallstones and cholecystitis.Methods A retrospective analysis was conducted on 465 patients who underwent laparoscopic cholecystectomy for gallstones and cholecystitis in the People's Hospital of Longhua from January 1,2022 to June 30,2023.Patients were randomly allocated into a training cohort(310 cases)and a validation cohort(155 cases).Univariate and multivariate Logistic regression was used to identify risk factors for complicated cholecystitis,followed by Logistic stepwise regression to construct the nomogram prediction model.The model was evaluated by receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis(DCA).Results Among the 465 patients,54(11.61％)were diagnosed with complicated cholecystitis.There was no statistically significant difference in baseline data between the training cohort and the validation cohort(P＞0.05).Multivariate Logistic regression showed that,in the training chort the neutrophil percentage(NEU％)＞75.0％(OR=11.702,95％CI 4.162 to 32.901),gallbladder wall thickness(OR=1.543,95％CI 1.169 to 2.036),INR＜0.8(OR=97.216,95％CI 4.617 to 2 046.964),gallbladder width(OR=1.077,95％CI 1.011 to 1.147),and BMI≥30 kg/m2(OR=5.237,95％CI 1.209 to 22.680),were independent risk factors for gallstones with complicated cholecystitis.The final nomogram was constructed by Logistic stepwise regression,which incorporating:NEU％,gallbladder wall thickness,INR,gallbladder width and BMI.In the training cohort,the area under the ROC curve(AUC)was 0.895(95％CI 0.828 to 0.961),with a sensitivity of 0.818 and a specificity of 0.902.In the validation cohort,the ROC AUC was 0.889(95％CI 0.815 to 0.963),with a sensitivity of 0.750 and a specificity of 0.897.Calibration curves of both the training and validation cohorts showed a good agreement between the actual values and predicted values.DCA demonstrated that the nomogram prediction model exhibited a favorable clinical decision-making utility.Conclusion The nomogram constructed using five factors(NEU％,gallbladder wall thickness,INR,gallbladder width and BMI)for predicting gallstones with complicated cholecystitis exhibits excellent accuracy and practical clinical value.关键词
胆囊结石/复杂胆囊炎/列线图/预测模型Key words
gallstone/complicated cholecystitis/nomogram/prediction model分类
临床医学
