1 Citation (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)266-274
Number of pages9
JournalChild Abuse and Neglect
Volume88
DOIs
StatePublished - Feb 1 2019

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Craniocerebral Trauma
Decision Support Techniques
Critical Care
Logistic Models
Child Abuse
ROC Curve
Cross-Sectional Studies
Head
Pediatrics
Physicians

All Science Journal Classification (ASJC) codes

  • Pediatrics, Perinatology, and Child Health
  • Developmental and Educational Psychology
  • Psychiatry and Mental health

Cite this

for the Pediatric Brain Injury Research Network (PediBIRN) Investigators (2019). Estimating the probability of abusive head trauma after abuse evaluation. Child Abuse and Neglect, 88, 266-274. https://doi.org/10.1016/j.chiabu.2018.11.015
for the Pediatric Brain Injury Research Network (PediBIRN) Investigators. / Estimating the probability of abusive head trauma after abuse evaluation. In: Child Abuse and Neglect. 2019 ; Vol. 88. pp. 266-274.
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title = "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.",
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for the Pediatric Brain Injury Research Network (PediBIRN) Investigators 2019, 'Estimating the probability of abusive head trauma after abuse evaluation', Child Abuse and Neglect, vol. 88, pp. 266-274. https://doi.org/10.1016/j.chiabu.2018.11.015

Estimating the probability of abusive head trauma after abuse evaluation. / for the Pediatric Brain Injury Research Network (PediBIRN) Investigators.

In: Child Abuse and Neglect, Vol. 88, 01.02.2019, p. 266-274.

Research output: Contribution to journalArticle

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T1 - Estimating the probability of abusive head trauma after abuse evaluation

AU - for the Pediatric Brain Injury Research Network (PediBIRN) Investigators

AU - Hymel, Kent

AU - Wang, Ming

AU - Chinchilli, Vernon

AU - Karst, Wouter A.

AU - Willson, Douglas F.

AU - Dias, Mark

AU - Herman, Bruce E.

AU - Carroll, Christopher L.

AU - Haney, Suzanne B.

AU - Isaac, Reena

PY - 2019/2/1

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N2 - 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.

AB - 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.

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for the Pediatric Brain Injury Research Network (PediBIRN) Investigators. Estimating the probability of abusive head trauma after abuse evaluation. Child Abuse and Neglect. 2019 Feb 1;88:266-274. https://doi.org/10.1016/j.chiabu.2018.11.015