Shuchami Adi, Lazebnik Teddy, Ashkenazi Shai, Cohen Avner Herman, Reichenberg Yael, Shkalim Zemer Vered
Department of Mathematics, Ariel University, Ariel 4070000, Israel.
Department of Cancer Biology, Cancer Institute, University College London, London WC1 9BT, UK.
Diagnostics (Basel). 2025 Jul 28;15(15):1885. doi: 10.3390/diagnostics15151885.
: Laboratory tests conducted in community settings are occasionally repeated within hours of presentation to pediatric emergency departments (PEDs). Reducing unnecessary repetitions can ease child discomfort and alleviate the healthcare burden without compromising the diagnostic process or quality of care. The aim of this study was to develop a decision tree (DT) model to guide physicians in minimizing unnecessary repeat blood tests in PEDs. The minimal decision tree (MDT) algorithm was selected for its interpretability and capacity to generate optimally pruned classification trees. Children aged 3 months to 18 years with community-based complete blood count (CBC), electrolyte (ELE), and C-reactive protein (CRP) measurements obtained between 2016 and 2023 were included. Repeat tests performed in the pediatric emergency department within 12 h were evaluated by comparing paired measurements, with tests considered justified when values transitioned from normal to abnormal ranges or changed by ≥20%. Additionally, sensitivity analyses were conducted for absolute change thresholds of 10% and 30% and for repeat intervals of 6, 18, and 24 h. Among 7813 children visits in this study, 6044, 1941, and 2771 underwent repeated CBC, ELE, and CRP tests, respectively. The mean ages of patients undergoing CRP, ELE, and CBC testing were 6.33 ± 5.38, 7.91 ± 5.71, and 5.08 ± 5.28 years, respectively. The majority were of middle socio-economic class, with 66.61-71.24% living in urban areas. Pain was the predominant presented complaint (83.69-85.99%), and in most cases (83.69-85.99%), the examination was conducted by a pediatrician. The DT model was developed and evaluated on training and validation cohorts, and it demonstrated high accuracy in predicting the need for repeat CBC and ELE tests but not CRP. Performance of the DT model significantly exceeded that of the logistic regression model. The data-driven guide derived from the DT model provides clinicians with a practical, interpretable tool to minimize unnecessary repeat laboratory testing, thereby enhancing patient care and optimizing healthcare resource utilization.
在社区环境中进行的实验室检查偶尔会在患儿就诊于儿科急诊科（PEDs）数小时内重复进行。减少不必要的重复检查可以减轻患儿的不适并减轻医疗负担，同时又不影响诊断过程或医疗质量。本研究的目的是开发一种决策树（DT）模型，以指导医生尽量减少儿科急诊科中不必要的重复血液检查。选择最小决策树（MDT）算法是因为其具有可解释性以及生成最优剪枝分类树的能力。纳入了2016年至2023年间在社区进行全血细胞计数（CBC）、电解质（ELE）和C反应蛋白（CRP）测量的3个月至18岁儿童。通过比较配对测量值来评估在儿科急诊科12小时内进行的重复检查，当数值从正常范围转变为异常范围或变化≥20%时，检查被认为是合理的。此外，还针对10%和30%的绝对变化阈值以及6、18和24小时的重复间隔进行了敏感性分析。在本研究的7813次儿童就诊中，分别有6044、1941和2771例接受了重复的CBC、ELE和CRP检查。接受CRP、ELE和CBC检查的患者平均年龄分别为6.33±5.38岁、7.91±5.71岁和5.08±5.28岁。大多数属于社会经济中等阶层，66.61 - 71.24%居住在城市地区。疼痛是最主要的就诊主诉（83.69 - 85.99%），并且在大多数情况下（83.69 - 85.99%），检查由儿科医生进行。DT模型在训练和验证队列上进行了开发和评估，它在预测重复CBC和ELE检查的必要性方面表现出高准确性，但对CRP检查的预测准确性不高。DT模型的性能显著超过逻辑回归模型。从DT模型得出的数据驱动指南为临床医生提供了一种实用、可解释的工具，以尽量减少不必要的重复实验室检查，从而改善患者护理并优化医疗资源利用。
