Abstract Details

Title Updating the TBI IMPACT Prognostic Model in a Diverse Observational Cohort

Topic Neuro Trauma and Critical Care

Presentation(s) P8 - Poster Session 8 (5:30 PM-6:30 PM)

Poster/Presentation
Number 2-002

Objective

Our primary aim was to externally validate the IMPACT model using a modern, diverse prospective observational cohort: “PROTIPS”.

Background The International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) prognostic model predicts 6 months outcomes after moderate to severe traumatic brain injury (TBI).

Design/Methods We analyzed a cohort of subjects with TBI (GCS 3-12) and evidence of intracranial hemorrhage on initial head CT at a single institution with complete outcome data. We assessed all three versions of the IMPACT model - core, extended, and laboratory - in terms of 6-month mortality and unfavorable outcomes (defined as GOSE 1-4), comparing the original model and a model where the coefficients were refitted.

Results

Almost one third of PROTIPS subjects were female (29%), and 22% were of races other than White. Of the cohort (n=126), 88 subjects had complete 6-month outcome data. There were no missing predictor variables. Significant variables correlating with 6-month GOSE were age (45.7±21.7 years, p<0.001), GCS Motor (5 [1-5]), p<0.005), and glucose (153±63.9 mg/dl, p<0.01). Using the original model, for mortality, model discrimination was: core model (AUC 0.70), extended model (AUC 0.58), and laboratory model (AUC 0.70). For unfavorable outcomes (GOSE 1-4), the performance was: core model (AUC 0.56), CT model (AUC 0.63), and lab model (AUC 0.61). Upon refitting for mortality, model discrimination was: core model (AUC 0.87 [95% CI: 0.86-0.89]), extended model (AUC 0.82 [95% CI: 0.79-0.84]), and laboratory model (AUC 0.84 [95% CI: 0.81-0.89]). For unfavorable outcomes, the performance was: core model (AUC 0.74 [95% CI: 0.65-0.80]), CT model (AUC 0.82 [95% CI: 0.76-0.89]), and lab model (AUC 0.72 [95% CI: 0.69-0.73]).

Conclusions Using the same predictor variables but refitting the coefficients allowed us to achieve improved AUCs comparable to the original coefficients. Predictive accuracy can vary across cohorts, necessitating caution in interpreting model outputs.

Authors/Disclosures
Naoki Takegami, MD (UCSF) PRESENTER	Dr. Takegami has nothing to disclose.
Abel Torres Espin	No disclosure on file
Yoshihito Imagawa	No disclosure on file
Itsunori Watanabe	No disclosure on file
Shannon McWeeney	No disclosure on file
Adam Ferguson	The institution of Adam Ferguson has received research support from NIH. The institution of Adam Ferguson has received research support from VA. The institution of Adam Ferguson has received research support from DoD. The institution of Adam Ferguson has received research support from Wings for Life Foundation. The institution of Adam Ferguson has received research support from Craig H Neilsen Foundation. Adam Ferguson has received intellectual property interests from a discovery or technology relating to health care.
H. E. Hinson, MD, MCR, FAAN (UCSF/Zuckerberg San Francisco General Hospital)	Dr. Hinson has received personal compensation in the range of $5,000-$9,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Neurology. Dr. Hinson has received personal compensation in the range of $5,000-$9,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for American Heart Association.

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