A Precision Medicine Approach Based on Discrete Time Windows for Predicting Outcomes of Polytrauma Patients
Abstract
We propose to leverage Precision Medicine approaches in a three-phase study of military and civilian trauma, incorporating 1) Phase I- (Narrow-Window Diagnostic): A novel, time window-based trauma patient stratification scheme will be refined with genomic and admission clinical/inflammation biomarkers using both retrospective and prospective data on patients with polytrauma. We will define the admission variables that most accurately prognosticate for these adverse outcome categories. We can report that a unified Master dataset of retrospective data has been created and the Narrow-Windows patient stratification model has been initiated. In addition, UPITT has begun its recruitment of patients; 12 eligible patients to date. 2) Phase 2- (Wide-Window Diagnostic): The stratification algorithm from Phase 1, which is based on single time point data, will be compared against a wide-window algorithm involving multiple initial readings in the first 24h post-injury, using the dataset obtained in Phase 1. We will test the hypothesis that widening the time window for data acquisition will increase the precision of the prognostication. 3) Phase 3- (Optimized Patient Stratification): a prospective study testing the optimal stratification algorithm in patients with polytrauma + or - TBI.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2021
- Accession Number
- AD1162347
Entities
People
- Timothy R. Billiar
- Yoram Vodovotz
Organizations
- University of Pittsburgh