Michael J. Bell, MD Stephen R. Wisniewski, PhD University Of Pittsburgh National Institute Of Health National Institute Of Neurological Disorders And Stroke.

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Michael J. Bell, MD Stephen R. Wisniewski, PhD University Of Pittsburgh National Institute Of Health National Institute Of Neurological Disorders And Stroke (NINDS) United States Approaches and Decisions for Acute Pediatric TBI (ADAPT) Trial

What are key accomplishments in the past year? NOA – July 1, 2013  No planning grant, start up planned for first 9 months of funding timeline First patient enrollment – February 20, 2014 Expansion of sites from 32 to 42 to ensure meeting of enrollment goals As of June 25, 35 clinical sites activated for enrollment As of June 25, 71 subjects enrolled (240% of expected) First FITBIR download accomplished on June 30, 2014 Ancillary study submitted for funding (Seizure Treatment after TBI [STAT] Study) to NINDS in June, 2014

What are the major challenges or issues, if any? Aggressive enrollment goal (n = 1000) that dwarfs previous studies in this patient population  Near constant assessment of the quality and quantity of sites  Predictability of eligible patients at various sites Negotiations with Universities regarding language in contracted service agreements Negotiations with IRBs regarding consent process Future challenges  Ensuring complete data entry from sites  Ensuring follow-up visits  Generating statistical models for testing of primary/secondary hypotheses

What percentage of your data is comprised of the International TBI Common Data Elements and what percentage are unique data elements? ADAPT Collection Classification YesNoIndirectlyTotal Core Basic Supplemental Total ADAPT collects a total of 1151 unique data elements Many of these elements are collected over time (ICP, CPP, etc) or several times (neurological exam elements) Therefore, the number of elements collected in ADAPT is more than 1151 and is dependent upon how many days of data collection occurs for each subject

Core CDEs Not Collected in ADAPT Not relevant to the child population  Self-identified gender – we are collecting biological sex of the subject  Employment status of the subject – all will be school-aged or younger and not employed  GCS using adult variables Not relevant for severity of injury  Length of time unconscious – in severe TBI, all children are in prolonged comas Unknown elements  ICD-9 codes?  SNOWMED CT scans?