From the Rutgers-New Jersey Medical School, Newark, NJ (Dr. Zhao, Dr. Starke, and Dr. Tompson), and the Department of Clinical Orthopedics, University of California, San Francisco, Benioff Children's Hospital of Oakland, Oakland, CA (Dr. Sabharwal).
J Am Acad Orthop Surg. 2020 Feb 15;28(4):e164-e171. doi: 10.5435/JAAOS-D-18-00502.
Despite heightened awareness and multidisciplinary efforts, a predictive model to help the clinician quantify the likelihood of nonaccidental trauma (NAT) in a child presenting with a fracture does not exist. The purpose of this study was to develop an evidence-based likelihood of NAT in a child presenting with a fracture.
Using the 2012 Kids' Inpatient Database, we identified all available pediatric inpatients admitted with an extremity or spine fracture. Children with a fracture were subcategorized based on the diagnosis of NAT. Multivariate analysis using multiple logistic regression was used to generate odds ratios and create a predictive model for the probability of NAT in a child with a fracture.
Of the 57,183 pediatric fracture cases, 881 (1.54%) had a concurrent diagnosis of NAT. Of these children, those presenting with multiple fractures had the highest rate of NAT (2.8%). The overall mortality rate in patients presenting with fractures and abuse was 1.8%, which was twice as high as patients without abuse (odds ratio [OR] = 2.0). Based on multivariate analysis, younger age (OR = 0.5), black race (OR = 1.7), intracranial injury (OR = 3.7), concomitant rib fracture (OR = 7.2), and burns (OR = 8.3) were positive predictors of NAT in a child with a fracture. A weighted equation using regression coefficients was generated and plotted on a receiver operative characteristic curve, demonstrating excellent correlation and probability of NAT (area under curve = 0.962). (Equation - ln (P/(1 - P)) = -1.79 - 0.65 (age in years) + 0.51 (black race) + 1.97 (rib fracture) + 1.31 (intracranial injury) + 2.12 (burn)).
Using a large, national inpatient database, we identified an overall prevalence of 1.54% of NAT in children admitted to the hospital with a fracture. Based on five independent predictors of NAT, we generated an estimated probability chart that can be used in the clinical workup of a child with a fracture and possible NAT. This evidence-based algorithm needs to be validated in clinical practice.
Prognostic study, Level III (case-control study).
尽管人们的意识有所提高,并且多学科也做出了努力,但仍缺乏一种预测模型来帮助临床医生量化儿童骨折时非意外伤害(NAT)的可能性。本研究旨在建立一种基于证据的儿童骨折时 NAT 可能性的预测模型。
我们使用 2012 年儿童住院数据库,确定了所有因四肢或脊柱骨折住院的儿科患者。根据 NAT 的诊断,对骨折患儿进行分类。采用多变量逻辑回归进行多变量分析,生成比值比并为骨折患儿 NAT 发生概率创建预测模型。
在 57183 例儿科骨折病例中,881 例(1.54%)同时诊断为 NAT。在这些儿童中,多发性骨折的患儿 NAT 发生率最高(2.8%)。骨折伴虐待患儿的总死亡率为 1.8%,是无虐待患儿的两倍(比值比[OR] = 2.0)。多变量分析显示,年龄较小(OR = 0.5)、黑种人(OR = 1.7)、颅内损伤(OR = 3.7)、合并肋骨骨折(OR = 7.2)和烧伤(OR = 8.3)是儿童骨折时 NAT 的阳性预测因素。使用回归系数生成加权方程,并绘制在接收者操作特征曲线(ROC 曲线)上,显示出极好的相关性和 NAT 概率(曲线下面积[AUC] = 0.962)。[方程-ln(P/(1-P))=-1.79-0.65(年龄)+0.51(黑种人)+1.97(肋骨骨折)+1.31(颅内损伤)+2.12(烧伤)]。
使用大型全国住院患者数据库,我们发现因骨折住院的儿童中 NAT 的总体患病率为 1.54%。根据 NAT 的五个独立预测因素,我们生成了一个估计概率图表,可用于骨折伴可能 NAT 的儿童的临床评估。这种基于证据的算法需要在临床实践中进行验证。
预后研究,III 级(病例对照研究)。