Estimating the probability of abusive head trauma after abuse evaluation

Abstract

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.

Keywords: Abusive head trauma; Child abuse; Clinical prediction rule; Non-accidental trauma; Prediction tool.