An injury plausibility assessment model for differentiating abusive from accidental fractures in young children

区分幼儿虐待和意外骨折的伤害合理性评估模型

基本信息

  • 批准号:
    10653078
  • 负责人:
  • 金额:
    $ 64.74万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-09-04 至 2024-06-30
  • 项目状态:
    已结题

项目摘要

PROJECT SUMMARY / ABSTRACT Child abuse is a public health epidemic with devastating consequences for young children. In 2017, there were 676,000 victims of child abuse and neglect in the United States including approximately 1700 deaths. Young children are especially vulnerable - 81% of these deaths occurred among children 0-3 years old. Physical child abuse results in over 120,000 cases a year (less than a quarter of all abuse cases), but accounts for over half of the deaths, speaking to the heightened risk for a child. Fractures are the most common serious injury from physical abuse, occurring more often than abuse-related traumatic brain injury and abdominal injury combined. Each year in the United States there are more than 90,000 emergency department visits for fractures in children age 0-5 years (most often involving the long bones), with abuse-related fractures peaking in the first 3 years of life. It can be extremely difficult for providers to differentiate abuse-related fractures from those associated with an accident in these young children. This difficulty results in a bidirectional problem: under evaluation and missed abuse for some (which may result in re-injury or even death), and over evaluation for abuse and reporting to state child protective services (CPS) for others (which also impacts families negatively, and occurs most often in race/ethnic minority groups). Such “bidirectional” errors in decision making come at a high cost to all involved. These issues highlight the critical need for an evidence-based fracture assessment model to inform medical decision-making when attempting to differentiate abusive from accidental fractures. To address this need, we developed and tested a fracture injury plausibility assessment model (FxIPAM) in 201 children with long bone fractures. We demonstrated its capability to differentiate abuse-related fractures from those resulting from accidental trauma and also demonstrated its theoretical potential to decrease race/ethnic disparities in rates of abuse evaluations, based on model scoring results. Before implementation, validation is required. The goal of this study is to validate an evidence-based model for fracture assessments to improve the clinician’s ability to differentiate abuse from accidental fractures in young children. Therefore, we propose the following aims in a prospective multicenter study of 1000 children, 0-3 years of age, with a long bone fracture: 1) Validate our FxIPAM model by determining its predictive accuracy to differentiate between abuse vs. accidental long bone fractures, and 2) estimate the impact of a hypothetical application of the FxIPAM on abuse assessments and reporting to CPS across race/ethnic groups. Success of this study will result in the first validated model for fracture assessments in young children. The intent of the FxIPAM is not to diagnose abuse but to function as a screening tool to identify children at risk for abuse who require further evaluation and to identify children with plausible injuries where further work for abuse or reporting to CPS may not be require. The potential public health impact of this model is bidirectional: decreased missed abuse and decreased disparities in abuse evaluations and reporting to CPS.
项目概要/摘要 虐待儿童是一种公共卫生流行病,给幼儿带来了毁灭性的后果。 美国有 676,000 名儿童遭受虐待和忽视,其中约 1700 人死亡。 儿童尤其容易受到伤害——其中 81% 的死亡发生在 0-3 岁的儿童中。 每年发生超过 120,000 起虐待案件(不到所有虐待案件的四分之一),但占一半以上 在死亡人数中,骨折是最常见的严重伤害。 身体虐待造成的,比虐待相关的创伤性脑损伤和腹部损伤更常见 美国每年有超过 90,000 人次到急诊室就诊。 0-5 岁儿童骨折(最常见的是长骨),其中与虐待相关的骨折达到顶峰 在生命的最初 3 年里,医疗服务提供者很难区分与虐待相关的骨折。 那些与这些幼儿的事故有关的困难会导致双向问题: 对某些人来说,评估不足并错过了虐待(这可能导致再次受伤甚至死亡),以及评估过度 虐待行为并向州儿童保护服务机构 (CPS) 举报(这也会影响家庭) 负面的,并且最常发生在种族/少数民族群体中)。 这些问题凸显了基于证据的迫切需要。 骨折评估模型可在试图区分虐待行为时为医疗决策提供信息 为了满足这一需求,我们开发并测试了骨折损伤的合理性评估。 我们在 201 名长骨骨折儿童中使用了模型 (FxIPAM),证明了其区分的能力。 意外创伤造成的与虐待相关的骨折,并证明了其理论 根据模型评分结果,有可能减少虐待率评估中的种族/民族差异。 在实施之前,需要进行验证。本研究的目标是验证基于证据的模型。 用于骨折评估,以提高临床医生区分虐待和意外骨折的能力 因此,我们在一项针对 1000 名儿童的前瞻性多中心研究中提出以下目标: 0-3 岁,患有长骨骨折:1) 通过确定其预测来验证我们的 FxIPAM 模型 区分滥用与意外长骨骨折的准确性,以及 2) 估计滥用行为的影响 FxIPAM 在跨种族/族裔滥用评估和向 CPS 报告中的假设应用 这项研究的成功将产生第一个经过验证的幼儿骨折评估模型。 FxIPAM 的目的不是诊断虐待行为,而是作为筛查工具来识别处于危险中的儿童 需要进一步评估的虐待儿童,并确定可能受到伤害的儿童,并进一步开展工作 可能不需要滥用或向 CPS 报告。该模型的潜在公共健康影响是双向的: 减少了漏报的滥用行为,并减少了滥用行为评估和向 CPS 报告的差异。

项目成果

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{{ truncateString('GINA E. BERTOCCI', 18)}}的其他基金

An injury plausibility assessment model for differentiating abusive from accidental fractures in young children
区分幼儿虐待和意外骨折的伤害合理性评估模型
  • 批准号:
    10033417
  • 财政年份:
    2020
  • 资助金额:
    $ 64.74万
  • 项目类别:
An injury plausibility assessment model for differentiating abusive from accidental fractures in young children
区分幼儿虐待和意外骨折的伤害合理性评估模型
  • 批准号:
    10440510
  • 财政年份:
    2020
  • 资助金额:
    $ 64.74万
  • 项目类别:
An injury plausibility assessment model for differentiating abusive from accidental fractures in young children
区分幼儿虐待和意外骨折的伤害合理性评估模型
  • 批准号:
    10254257
  • 财政年份:
    2020
  • 资助金额:
    $ 64.74万
  • 项目类别:
Biomechanical Assessment of Femur Fracture in Pediatric Falls
儿童跌倒股骨骨折的生物力学评估
  • 批准号:
    8838221
  • 财政年份:
    2014
  • 资助金额:
    $ 64.74万
  • 项目类别:
Biomechanical Assessment of Femur Fracture in Pediatric Falls
儿童跌倒股骨骨折的生物力学评估
  • 批准号:
    8618419
  • 财政年份:
    2014
  • 资助金额:
    $ 64.74万
  • 项目类别:
Biomechanical Investigation of Pediatric Accidents
儿科事故的生物力学调查
  • 批准号:
    6623840
  • 财政年份:
    2002
  • 资助金额:
    $ 64.74万
  • 项目类别:
Biomechanical Investigation of Pediatric Accidents
儿科事故的生物力学调查
  • 批准号:
    6470409
  • 财政年份:
    2002
  • 资助金额:
    $ 64.74万
  • 项目类别:
Muscle fatigue in arthritis total hip replacement
关节炎全髋关节置换术中的肌肉疲劳
  • 批准号:
    6356335
  • 财政年份:
    1997
  • 资助金额:
    $ 64.74万
  • 项目类别:

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  • 财政年份:
    2022
  • 资助金额:
    $ 64.74万
  • 项目类别:
An injury plausibility assessment model for differentiating abusive from accidental fractures in young children
区分幼儿虐待和意外骨折的伤害合理性评估模型
  • 批准号:
    10033417
  • 财政年份:
    2020
  • 资助金额:
    $ 64.74万
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