Estimating the probability of abusive head trauma after abuse evaluation
Estimating the probability of abusive head trauma after abuse evaluation
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DOI：
10.1016/j.chiabu.2018.11.015
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发表时间：
2019-02-01
影响因子：
4.8
通讯作者：
Hyden, Phil
中科院分区：
文献类型：
--
作者：
Hymel, Kent P.;Wang, Ming;Hyden, Phil
背景：基于证据的、针对患者的虐待性头部创伤概率估计可以为医生评估、确认、排除和/或报告疑似儿童虐待的决定提供信息。目的：推导儿童虐待性头部创伤的临床预测规则，该规则结合了患者完成的骨骼调查和视网膜检查的（阳性或阴性）预测贡献。参与者和环境：2010年至2013年期间，在18个地点之一住院接受重症监护的500名3岁以下急性头部受伤儿童。方法:对现有的横断面前瞻性数据集进行二次分析，包括：(1)多变量逻辑回归来推算从未排序或完成的虐待评估的结果；(2)正则化逻辑回归来推导一种新的临床预测规则，该规则包含已完成的虐待评估的结果；(3)应用新的预测规则对其预测变量的观察组合计算患者对虐待性头部创伤概率的具体估计。结果：本研究建立的7变量临床预测规则，采用平均概率阈值> 0.5对滥用患者进行分类，敏感性0.73 (95% CI: 0.66 ~ 0.79)，特异性0.87 （95% CI: 0.82 ~ 0.90）。受试者工作特征曲线下面积为0.88 （95% CI: 0.85 ~ 0.92）。72个观察到的7个预测变量组合的患者特异性虐待性头部创伤概率估计范围为0.04 （95% CI: 0.02-0.08）至0.98 （95% CI: 0.96-0.99）。结论：七个变量有助于重症监护环境中虐待评估后的虐待头部创伤概率的患者特异性估计。
Background: Evidence-based, patient-specific estimates of abusive head trauma probability can inform physicians' decisions to evaluate, confirm, exclude, and/or report suspected child abuse.Objective: To derive a clinical prediction rule for pediatric abusive head trauma that incorporates the (positive or negative) predictive contributions of patients' completed skeletal surveys and retinal exams.Participants and Setting: 500 acutely head-injured children under three years of age hospitalized for intensive care at one of 18 sites between 2010 and 2013.Methods: Secondary analysis of an existing, cross-sectional, prospective dataset, including (1) multivariable logistic regression to impute the results of abuse evaluations never ordered or completed, (2) regularized logistic regression to derive a novel clinical prediction rule that incorporates the results of completed abuse evaluations, and (3) application of the new prediction rule to calculate patient-specific estimates of abusive head trauma probability for observed combinations of its predictor variables.Results: Applying a mean probability threshold of > 0.5 to classify patients as abused, the 7 variable clinical prediction rule derived in this study demonstrated sensitivity 0.73 (95% CI: 0.66-0.79) and specificity 0.87 (95% CI: 0.82-0.90). The area under the receiver operating characteristics curve was 0.88 (95% CI: 0.85-0.92). Patient-specific estimates of abusive head trauma probability for 72 observed combinations of its seven predictor variables ranged from 0.04 (95% CI: 0.02-0.08) to 0.98 (95% CI: 0.96-0.99).Conclusions: Seven variables facilitate patient-specific estimation of abusive head trauma probability after abuse evaluation in intensive care settings.