Oearsakul Thakul, Tunthanathip Thara
Department of Surgery, Division of Neurosurgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand.
Turk J Emerg Med. 2022 Jan 20;22(1):15-22. doi: 10.4103/2452-2473.336107. eCollection 2022 Jan-Mar.
Traumatic brain injury (TBI) in children has become the major cause of mortality and morbidity in Thailand that has had an impact with economic consequences. This study aimed to develop and internally validate a nomogram for a 6-month follow-up outcome prediction in moderate or severe pediatric TBI.
This retrospective cohort study involved 104 children with moderate or severe TBI. Various clinical variables were reviewed. The functional outcome was assessed at the hospital discharge and at a 6-month follow-up based on the King's Outcome Scale for Childhood Head Injury classification. Predictors associated with the 6-month follow-up outcome were developed from the predictive model using multivariable binary logistic regression to estimate the performance and internal validation. A nomogram was developed and presented as a predictive model.
The mean age of the samples was 99.75 months (standard deviation 59.65). Road traffic accidents were the highest injury mechanism at 84.6%. The predictive model comprised Glasgow Coma Scale of 3-8 (odds ratio [OR]: 16.07; 95% confidence interval [CI]: 1.27-202.42), pupillary response in one eye (OR 7.74; 95% CI 1.26-47.29), pupillary nonresponse in both eyes (OR: 57.74; 95% CI: 2.28-145.81), hypotension (OR: 19.54; 95%: CI 3.23-117.96), and subarachnoid hemorrhage (OR: 9.01, 95% CI: 1.33-60.80). The concordance statistic index (C-index) of the model's discrimination was 0.931, while the C-index following the bootstrapping and 5-cross validation were 0.920 and 0.924, respectively.
The performance of a clinical nomogram for predicting 6-month follow-up outcomes in pediatric TBI patients was assessed at an excellent level. However, further external validation would be required for the confirmation of the tool's performance.
儿童创伤性脑损伤（TBI）已成为泰国儿童死亡和发病的主要原因，并产生了经济影响。本研究旨在开发并内部验证一个用于预测中度或重度小儿TBI 6个月随访结果的列线图。
这项回顾性队列研究纳入了104例中度或重度TBI患儿。回顾了各种临床变量。根据儿童头部损伤国王预后量表分类，在出院时和6个月随访时评估功能结局。使用多变量二元逻辑回归从预测模型中得出与6个月随访结果相关的预测因素，以评估其性能并进行内部验证。开发了一个列线图并将其作为预测模型呈现。
样本的平均年龄为99.75个月（标准差59.65）。道路交通事故是最主要的损伤机制，占84.6%。预测模型包括格拉斯哥昏迷量表评分为3 - 8分（比值比[OR]：16.07；95%置信区间[CI]：1.27 - 202.42）、单眼瞳孔反应（OR 7.74；95% CI 1.26 - 47.29）、双眼瞳孔无反应（OR：57.74；95% CI：2.28 - 145.81）、低血压（OR：19.54；95%：CI 3.23 - 117.96）和蛛网膜下腔出血（OR：9.01，95% CI：1.33 - 60.80）时。该模型判别能力的一致性统计指数（C指数）为0.931，而经过自抽样和5折交叉验证后的C指数分别为0.920和0.924。
用于预测小儿TBI患者6个月随访结果的临床列线图性能评估为优秀水平。然而，需要进一步进行外部验证以确认该工具的性能。
