Development and Prospective Validation of Tools to Accurately Identify Neurosurgical and Critical Care Events in Children With Traumatic Brain Injury.
Development and Prospective Validation of Tools to Accurately Identify Neurosurgical and Critical Care Events in Children With Traumatic Brain Injury.
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DOI：
10.1097/pcc.0000000000001120
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发表时间：
2017-05
期刊：
影响因子：
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通讯作者：
Dean JM
中科院分区：
文献类型：
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作者：
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
To develop and validate case definitions (“computable phenotypes”) to accurately identify neurosurgical and critical care events in children with traumatic brain injury (TBI). Prospective observational cohort study, May 2013 – September 2015 Two large U.S. children’s hospitals with level 1 Pediatric Trauma Centers 174 children < 18 years old admitted to an intensive care unit (ICU) after TBI Prospective data were linked to database codes for each patient. The outcomes were prospectively identified acute TBI, 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 TBI. Simple Boolean classifiers were ≥ 94% accurate for 7/9 clinical diagnoses and events. For central venous catheter placement, no classifier achieved 90% accuracy. Classifier accuracy was dependent on available data fields. 5/9 classifiers were acceptably accurate using only administrative data, but three required trauma registry fields and two required billing data. In children with TBI, 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 utilized in any observational study of children with TBI, and can reasonably be applied in studies of these interventions in other patient populations.
