ED Manag. 2017 Jun;29(6):65-66.
A new clinical index tool designed specifically for the emergency environment predicts the risk for future firearms violence in young people 14-24 years of age. The approach employs a brief, 10-point instrument that can be administered in one to two minutes, according to investigators. They also note that while the tool is based on data from a single ED in Flint, Ml, the tool should be applicable to urban EDs in regions that have similar characteristics. To create the tool, investigators used data from the Flint Youth Injury Study, an investigation of a group of patients 14-24 years of age who reported using drugs in the previous six months and accessed care at a Level I trauma center. Using a machine learning classification approach, investigators combed through the data, finding that the most predictive factors for firearm violence could be categorized into four domains: peer and partner violence victimization, community violence exposure, peer/family influences, and fighting. Ideally, investigators note the tool will be employed along with interventions targeted toward patients at high risk for future firearms violence.
一种专门为急诊环境设计的新型临床指标工具可预测14至24岁年轻人未来发生枪支暴力的风险。据调查人员称,该方法采用了一种简短的10分制工具,可在一到两分钟内完成。他们还指出,虽然该工具基于密歇根州弗林特市一家急诊科的数据,但该工具应适用于具有相似特征地区的城市急诊科。为了创建该工具,调查人员使用了弗林特青少年伤害研究的数据,该研究对一组14至24岁的患者进行了调查,这些患者报告在过去六个月内使用过毒品,并在一级创伤中心接受治疗。通过机器学习分类方法,调查人员梳理了这些数据,发现枪支暴力最具预测性的因素可分为四个领域:同伴和伴侣暴力受害、社区暴力暴露、同伴/家庭影响和打架。调查人员指出,理想情况下,该工具将与针对未来发生枪支暴力高风险患者的干预措施一起使用。