From the Department of Pediatric Emergency Care.
Department of Biostatistics and Medical Information.
Pediatr Emerg Care. 2021 Dec 1;37(12):e1075-e1081. doi: 10.1097/PEC.0000000000001904.
The objective of this study was to evaluate physical examinations, imaging, and laboratory analyses individually and combined using innovative statistical analysis methods for the accurate diagnosis of pediatric appendicitis.
Patients admitted to hospital with symptoms of abdominal pain whose pediatric appendicitis scores greater than 3 were included in the study. Clinical, radiologic, and laboratory findings and as a new biomarker calprotectin (CPT) concentrations were evaluated individually and combined using artificial neural networks (ANNs), which revealed latent relationships for a definitive diagnosis.
Three hundred twenty patients were evaluated (190 appendicitis [43 perforated] vs 130 no appendicitis). The mean ± SD age was 11.3 ± 3.6 years and 63% were male. Pediatric appendicitis scores, white blood cell (WBC) count, absolute neutrophil count (ANC), C-reactive protein (CRP) level, procalcitonin (PCT) and CPT concentrations were higher in the appendicitis group; however, only WBC and ANC were higher in first 24 hours of pain. White blood cells and CRP were diagnostic markers in patients whose appendix could not be visualized using ultrasonography (US). On classic receiver operating characteristic (ROC) analysis, the areas under the curve (AUCs) were not strong enough for differential diagnosis (WBC, 0.73; ANC, 0.72; CRP, 0.65; PCT and CPT, 0.61). However, when the physical examination, US, and laboratory findings were analyzed in a multivariate model and the ROC analysis obtained from the variables with ANN, an ROC curve could be obtained with 0.91 AUC, 89.8% sensitivity, and 81.2% specificity. C-reactive protein and PCT were diagnostic for perforated appendicitis with 0.83 and 0.75 AUC on ROC.
Although none of the biomarkers were sufficient for an accurate diagnosis of appendicitis individually, a combination of physical examination and laboratory and US was a good diagnostic tool for pediatric appendicitis.
本研究旨在评估体格检查、影像学和实验室分析单独使用和结合创新统计分析方法对小儿阑尾炎的准确诊断价值。
纳入因腹痛症状住院且小儿阑尾炎评分＞3 分的患儿。评估临床、影像学和实验室检查结果以及新型生物标志物钙卫蛋白（calprotectin，CPT）浓度，使用人工神经网络（ANN）单独和联合评估，以揭示明确诊断的潜在关系。
共评估了 320 例患者（190 例阑尾炎[43 例穿孔]与 130 例非阑尾炎）。平均年龄为 11.3±3.6 岁，63%为男性。阑尾炎组的小儿阑尾炎评分、白细胞（white blood cell，WBC）计数、绝对中性粒细胞计数（absolute neutrophil count，ANC）、C 反应蛋白（C-reactive protein，CRP）水平、降钙素原（procalcitonin，PCT）和 CPT 浓度较高，但疼痛最初 24 小时内仅 WBC 和 ANC 较高。WBC 和 CRP 是超声检查（ultrasonography，US）不能显示阑尾的患者的诊断标志物。在经典的接受者操作特征（receiver operating characteristic，ROC）分析中，各指标的曲线下面积（area under the curve，AUC）不足以进行鉴别诊断（WBC，0.73；ANC，0.72；CRP，0.65；PCT 和 CPT，0.61）。然而，当在多变量模型中分析体格检查、US 和实验室检查结果，并在 ANN 获得的变量进行 ROC 分析时，可获得 AUC 为 0.91、灵敏度为 89.8%和特异度为 81.2%的 ROC 曲线。CRP 和 PCT 对穿孔性阑尾炎的诊断 AUC 分别为 0.83 和 0.75。
尽管单独使用任何一种生物标志物都不足以准确诊断阑尾炎，但体格检查和实验室及 US 联合检查是小儿阑尾炎的一种良好诊断工具。
