Observational studyPediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies2017
Development and Prospective Validation of Tools to Accurately Identify Neurosurgical and Critical Care Events in Children With Traumatic Brain Injury.
Observational study in Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Linking the Virtual Pediatric System and Pediatric Hospital Information System Databases to Create Novel PICU Research Datasets.Critical care explorations · 2026Article
- Predicting intracranial pressure monitor placement in children with traumatic brain injury: a prospective cohort study to develop a clinical decision support tool.Journal of the American Medical Informatics Association : JAMIA · 2026Observational
- Considerations and Challenges When Using Clinical and Vital Record Review for Suicide Research.Journal of patient safety · 2025Article
- Open source and reproducible and inexpensive infrastructure for data challenges and education.Scientific data · 2024Article
- Commentary: Characteristics and Outcomes of Children with Cerebral Sinus Venous Thrombosis.Neurocritical care · 2023Article
- Sociodemographic factors associated with tracheostomy and mortality in bronchopulmonary dysplasia.Pediatric pulmonology · 2023Article
- Clinical Characteristics and Outcomes of Children with Acute Catastrophic Brain Injury: A 13-Year Retrospective Cohort Study.Neurocritical care · 2022Article
- Respiratory Syncytial Virus and All-Cause Bronchiolitis Hospitalizations Among Preterm Infants Using the Pediatric Health Information System (PHIS).The Journal of infectious diseases · 2022Observational
- Social Factors Predictive of Intensive Care Utilization in Technology-Dependent Children, a Retrospective Multicenter Cohort Study.Frontiers in pediatrics · 2021Article
- Factors Associated With Neurobehavioral Complications in Pediatric Abdominal Organ Transplant Recipients Identified Using Computable Composite Definitions.Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2020Article
- Untangling the complexity of multimorbidity with machine learning.Mechanisms of ageing and development · 2020Review
- Data Science for Child Health.The Journal of pediatrics · 2019Review
- The Burden of Pediatric Neurocritical Care in the United States.Pediatric neurology · 2018Article
- Phenotyping in Pediatric Traumatic Brain Injury.Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2018Article
- Identification of patients with hemoglobin SS/SβBlood advances · 2018Article
- Hospital Readmissions After Pediatric Trauma.Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2018Article
- Functional Outcome After Intracranial Pressure Monitoring for Children With Severe Traumatic Brain Injury.JAMA pediatrics · 2017Article
- Why Everyone Should Care About "Computable Phenotypes".Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2017Article
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12 authors.
Funding
Abstract
objectiveTo develop and validate case definitions (computable phenotypes) to accurately identify neurosurgical and critical care events in children with traumatic brain injury.
designProspective observational cohort study, May 2013 to September 2015.
settingTwo 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
resultsProspective 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.
conclusionsIn 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.
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