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Citation
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Bennett TD, DeWitt PE, Dixon RR, Kartchner C, Sierra Y, Ladell D, Srivastava R, Riva-Cambrin J, Kempe A, Runyan DK, Keenan HT, Dean JM. Pediatr. Crit. Care Med. 2017; 18(5): 442-451. |
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Affiliation
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1Section of Pediatric Critical Care, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO. 2Children's Hospital Colorado, Aurora, CO. 3Adult and Child Consortium for Health Outcomes Research and Delivery Science (ACCORDS), University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO. 4Division of Pediatric Critical Care, Department of Pediatrics, Colorado School of Public Health, Aurora, CO. 5Pediatric Critical Care, University of Utah School of Medicine, Salt Lake City, UT. 6Department of Bioinformatics and Biostatistics, Primary Children's Hospital, Salt Lake City, UT. 7Division of Pediatric Inpatient Medicine, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT. 8Office of Research, Intermountain Healthcare, Salt Lake City, UT. 9Division of Pediatric Neurosurgery, Department of Clinical Neurosciences, University of Calgary and Alberta Children's Hospital, Calgary, AB, Canada. 10Department of Pediatrics, Kempe Center, University of Colorado School of Medicine, Aurora, CO. |
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Abstract
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OBJECTIVE: To develop and validate case definitions (computable phenotypes) to accurately identify neurosurgical and critical care events in children with traumatic brain injury.
DESIGN: Prospective observational cohort study, May 2013 to September 2015. SETTING: Two large U.S. children's hospitals with level 1 Pediatric Trauma Centers. PATIENTS: One hundred seventy-four children less than 18 years old admitted to an ICU after traumatic brain injury. MEASUREMENTS AND MAIN RESULTS: Prospective data were linked to database codes for each patient. The outcomes were prospectively identified acute traumatic brain injury, intracranial pressure monitor placement, craniotomy or craniectomy, vascular catheter placement, invasive mechanical ventilation, and new gastrostomy tube or tracheostomy placement. Candidate predictors were database codes present in administrative, billing, or trauma registry data. For each clinical event, we developed and validated penalized regression and Boolean classifiers (models to identify clinical events that take database codes as predictors). We externally validated the best model for each clinical event. The primary model performance measure was accuracy, the percent of test patients correctly classified. The cohort included 174 children who required ICU admission after traumatic brain injury. Simple Boolean classifiers were greater than or equal to 94% accurate for seven of nine clinical diagnoses and events. For central venous catheter placement, no classifier achieved 90% accuracy. Classifier accuracy was dependent on available data fields. Five of nine classifiers were acceptably accurate using only administrative data but three required trauma registry fields and two required billing data.
CONCLUSIONS: In children with traumatic brain injury, computable phenotypes based on simple Boolean classifiers were highly accurate for most neurosurgical and critical care diagnoses and events. The computable phenotypes we developed and validated can be used in any observational study of children with traumatic brain injury and can reasonably be applied in studies of these interventions in other patient populations.
Language: en |