Kent P Hymel1, Ming Wang2, Vernon M Chinchilli2, Wouter A Karst3, Douglas F Willson4, Mark S Dias5, Bruce E Herman6, Christopher L Carroll7, Suzanne B Haney8, Reena Isaac9. 1. Department of Pediatrics, Penn State College of Medicine, Penn State Health Children's Hospital, Hershey, PA, United States. Electronic address: kphymel@gmail.com. 2. Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, United States. 3. Department of Forensic Medicine, Netherlands Forensic Institute, The Hague, the Netherlands. 4. Department of Pediatrics, Children's Hospital of Richmond, Richmond, VA, United States. 5. Departments of Neurosurgery and Pediatrics, Penn State College of Medicine, Hershey, PA, United States. 6. Department of Pediatrics, University of Utah School of Medicine, Primary Children's Medical Center, Salt Lake City, UT, United States. 7. Department of Pediatrics, Connecticut Children's Medical Center, Hartford, CT, United States. 8. Department of Pediatrics, University of Nebraska Medical Center, Children's Hospital and Medical Center, Omaha, NE, United States. 9. Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, TX, United States.
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.
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.
Authors: Rolf H H Groenwold; A Rogier T Donders; Kit C B Roes; Frank E Harrell; Karel G M Moons Journal: Am J Epidemiol Date: 2011-12-23 Impact factor: 4.897
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Authors: Kent P Hymel; Veronica Armijo-Garcia; Matthew Musick; Mark Marinello; Bruce E Herman; Kerri Weeks; Suzanne B Haney; Terra N Frazier; Christopher L Carroll; Natalie N Kissoon; Reena Isaac; Robin Foster; Kristine A Campbell; Kelly S Tieves; Nina Livingston; Ashley Bucher; Maria C Woosley; Dorinda Escamilla-Padilla; Nancy Jaimon; Lucinda Kustka; Ming Wang; Vernon M Chinchilli; Mark S Dias; Jennie Noll Journal: J Pediatr Date: 2021-03-31 Impact factor: 6.314
Authors: Jill R McTavish; Andrea Gonzalez; Nancy Santesso; Jennifer C D MacGregor; Chris McKee; Harriet L MacMillan Journal: BMC Pediatr Date: 2020-03-07 Impact factor: 2.125