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Estimating the probability of abusive head trauma after abuse evaluation

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dc.contributor.author Hymel, Kent P. ; Wang, Ming ; Chinchilli, Vernon M. ; Karst, Wouter A. ; Willson, Douglas F. ; Dias, Mark S. ; Herman, Bruce E. ; Carroll, Christopher L. ; Haney, Suzanne B. ; Isaac, Reena and Pediatric Brain Injury Research Network (PediBIRN) Investigators
dc.date.accessioned 2021-04-20T17:41:38Z
dc.date.available 2021-04-20T17:41:38Z
dc.date.issued 2019
dc.identifier.citation Hymel, Kent P. ; Wang, Ming ; Chinchilli, Vernon M. ; Karst, Wouter A. ; Willson, Douglas F. ; Dias, Mark S. ; Herman, Bruce E. ; Carroll, Christopher L. ; Haney, Suzanne B. ; Isaac, Reena and Pediatric Brain Injury Research Network (PediBIRN) Investigators. (2019). Estimating the probability of abusive head trauma after abuse evaluation. Child Abuse & Neglect, 88, 266–274. en_US
dc.identifier.uri https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6333504/pdf/nihms-1516493.pdf  
dc.identifier.uri http://hdl.handle.net/11212/5053
dc.description.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. (Author Abstract) en_US
dc.language.iso en en_US
dc.publisher Child Abuse & Neglect en_US
dc.subject child abuse en_US
dc.subject physical abuse en_US
dc.subject head trauma en_US
dc.subject diagnosis en_US
dc.subject signs and symptoms en_US
dc.subject medical en_US
dc.subject research en_US
dc.title Estimating the probability of abusive head trauma after abuse evaluation en_US
dc.type Article en_US


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