基于临床及 CT 特征的列线图模型评估 急性复杂性阑尾炎风险.

Objective To explore the diagnostic accuracy of risk nomogram model based on clinical and CT features for acute complicated appendicitis(ACA). Methods 478 patients with pathologically confirmed acute appendicitis(AA)from December 2020 to December 2022 were retrospectively classified as ACA(acute gangrenous appendicitis,acute perforated appendicitis,appendiceal abscess requiring surgery)and acute uncomplicated appendicitis(AUA:acute simple appendicitis,acute suppurative appendicitis). The clinical features,laboratory findings,and preoperative CT appearance between ACA and AUA groups were compared using single factor analysis. The high-risk factors were screened by multivariate logistic regression analysis and the corresponding nomogram model was constructed. Data from a separate group of 146 patients with AA from January 2023 to August 2023 were used to construct the validation model. Receiver operating characteristic(ROC)curve and decision curve analysis were used for internal validation of model results and compared with traditional Alvarado and the appendicitis inflammatory response(AIR)scoring methods. Results Of the 624 patients,13. 5％(84/624)had ACA. Regression analysis showed that age,duration of appendicitis symptoms,body temperature,percentage of neutrophil,and preoperative CT features were high risk factors for ACA. The nomogram model based on these factors had better diagnostic performance with area under the ROC curve(AUC)of 0. 831(95％CI:0. 783-0. 876),82. 0％sensitivity,72. 2％specificity,and 77. 1％accuracy compared to the Alvarado scoring method(AUC:0. 640,95％CI:0. 585-0. 696;sensitivity:73. 4％;specificity:46. 2％;accuracy:59. 8％)and AIR scoring method(AUC:0. 738,95％CI:0. 585-0. 890;sensitivity:66. 8％;specificity:72. 7％;accuracy:69. 8％). Conclusion Risk nomogram model based on clinical and CT features has high accuracy and reliability in diagnosing ACA. [ABSTRACT FROM AUTHOR]