Tunthanathip Thara, Duangsuwan Jarunee, Wattanakitrungroj Niwan, Tongman Sasiporn, Phuenpathom Nakornchai
Division of Neurosurgery, Department of Surgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Thailand.
Department of Computer Science, Faculty of Science, Prince of Songkla University, Hat Yai, Thailand.
J Pediatr Neurosci. 2020 Oct-Dec;15(4):409-415. doi: 10.4103/jpn.JPN_11_20. Epub 2021 Jan 19.
There are differences in injured mechanisms among pediatric traumatic brain injury (TBI) in developing countries. This study aimed to develop and validate clinical nomogram for predicting intracranial injury in pediatric TBI that will be implicated in balancing the unnecessary investigation in the general practice.
The retrospective study was conducted in all patients who were younger than 15 years old and underwent computed tomography (CT) of the brain after TBI in southern Thailand. Injured mechanisms and clinical characteristics were identified and analyzed with binary logistic regression for predicting intracranial injury. Using random sampling without replacement, the total data was split into nomogram developing dataset (80%) and testing dataset (20%). Therefore, a nomogram was constructed and applied via the web-based application from the developing dataset. Using testing dataset, validation as binary classifiers was performed by various probabilities levels.
A total of 900 victims were enrolled. The mean age was 87.2 (standard deviation [SD] 57.4) months, and 65.3% of all patients injured were from road traffic accidents. The rate of positive findings in CT of the brain was 32.8%. A nomogram was developed from the significant variables, including age groups, road traffic accidents, loss of consciousness, scalp hematoma/laceration, motor weakness, signs of basilar skull fraction, low Glasgow Coma Scale score, and pupillary light reflex.Therefore, a nomogram was developed from 80% of data and was validated from 20% of data. The accuracy, sensitivity, specificity, positive, and negative predictive values of the nomogram were 0.83, 0.42, 1.00, 1.00, and 0.81 at a cutoff value of 0.5 probability.
This study provides a clinical nomogram that will be applied to making decisions in general practice as a diagnostic tool from high specificity.
发展中国家儿童创伤性脑损伤(TBI)的损伤机制存在差异。本研究旨在开发并验证用于预测儿童TBI颅内损伤的临床列线图,这将有助于在全科医疗中平衡不必要的检查。
对泰国南部所有15岁以下且在TBI后接受脑部计算机断层扫描(CT)的患者进行回顾性研究。确定损伤机制和临床特征,并通过二元逻辑回归分析预测颅内损伤情况。采用无放回随机抽样,将全部数据分为列线图开发数据集(80%)和测试数据集(20%)。因此,根据开发数据集构建列线图并通过基于网络的应用程序进行应用。使用测试数据集,在不同概率水平下作为二元分类器进行验证。
共纳入900名受害者。平均年龄为87.2(标准差[SD]57.4)个月,所有受伤患者中有65.3%来自道路交通事故。脑部CT检查阳性率为32.8%。根据包括年龄组、道路交通事故、意识丧失、头皮血肿/裂伤、运动无力、颅底骨折体征、低格拉斯哥昏迷量表评分和瞳孔对光反射等显著变量开发了列线图。因此,根据80%的数据开发了列线图,并根据20%的数据进行了验证。在概率临界值为0.5时,列线图的准确性、敏感性、特异性、阳性预测值和阴性预测值分别为0.83、0.42、1.00、1.00和0.81。
本研究提供了一种临床列线图,作为具有高特异性的诊断工具,将应用于全科医疗决策。