Ding Xiaoting, Li Yongteng, Yu Daiyue, Huang Qiwei, Wang ShaoMei, Bai Jian, Pan Yongbin, Adam Mahamat Djibril, Yang Liucheng, Wu Kai
Department of Pediatric Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, Guangdong, China.
Department of Pediatric Surgery, Nanhai Maternity & Child Healthcare Hospital of Foshan, Foshan, 528403, Guangdong, China.
Pediatr Surg Int. 2025 May 4;41(1):129. doi: 10.1007/s00383-025-06032-8.
This study aimed to develop a diagnostic model utilizing clinical and laboratory data to identify complicated appendicitis in pediatric patients, improving acute appendicitis management.
Retrospective analysis of pediatric acute appendicitis cases (2018-2023) at two hospitals collected medical history, clinical criteria, and blood samples. Patients were divided into complicated and uncomplicated appendicitis groups for comparison. Significant variables were identified using the Least Absolute Shrinkage and Selection Operator (LASSO), and incorporated into a logistic regression model to construct a nomogram. The effectiveness of the model was assessed based on sensitivity, specificity, accuracy, and comparison with existing scoring systems.
Among 323 patients, four variables (neutrophil (NEU), C-reactive protein (CRP), fibrinogen (Fg), and chlorine (Cl)) were identified as significant. The recommended cutoff value of nomogram was 0.730, exceeding that of Alvarado and PAS, with higher sensitivity (81.7%), specificity (82.6%), and accuracy (82.0%), as well as better performance in both internal and external validations. Furthermore, it demonstrated excellent calibration and clinical utility.
NEU, CRP, Fg, and Cl are effective markers for diagnosing complicated appendicitis in children. The nomogram model can be considered to be incorporated into the diagnosis process of appendicitis as an auxiliary means of surgical intervention decision-making in complex appendicitis cases.
本研究旨在利用临床和实验室数据开发一种诊断模型，以识别小儿复杂阑尾炎，改善急性阑尾炎的管理。
对两家医院2018 - 2023年小儿急性阑尾炎病例进行回顾性分析，收集病史、临床标准和血样。将患者分为复杂阑尾炎组和非复杂阑尾炎组进行比较。使用最小绝对收缩和选择算子（LASSO）识别显著变量，并纳入逻辑回归模型以构建列线图。基于敏感性、特异性、准确性以及与现有评分系统的比较来评估模型的有效性。
在323例患者中，四个变量（中性粒细胞（NEU）、C反应蛋白（CRP）、纤维蛋白原（Fg）和氯（Cl））被确定为显著变量。列线图的推荐截断值为0.730，超过了阿尔瓦拉多评分和小儿阑尾炎严重程度（PAS）评分，具有更高的敏感性（81.7%）、特异性（82.6%）和准确性（82.0%），并且在内部和外部验证中均表现更好。此外，它还具有出色的校准和临床实用性。
NEU、CRP、Fg和Cl是诊断小儿复杂阑尾炎的有效标志物。列线图模型可被考虑纳入阑尾炎的诊断过程，作为复杂阑尾炎病例手术干预决策的辅助手段。
