The Michigan Algorithm for Acute Evaluation of Traumatic Brain Injury
Developing a traumatic brain injury (TBI) database and evaluation algorithm to optimize the clinical care provided to TBI patients.
Project at a Glance
Product Type:
Predictive Analysis
Project Start Date:
7/1/2021
Principal Investigators: Christopher Fung, MD, MS
Katharine Seagly, PhD
Solution Sheet:
Download Solution Sheet (PDF)
Model Validation: Retrospective Validation at Michigan Medicine
Funding History:
$643,449 in non-dilutive funding • 2021 $149,500 Massey Grand Challenge • 2021 $362,856 Abbott Laboratories
• 2022 $131,093 Massey Grand Challenge
• Substantial departmental, school and center based support
Overview
A team of University of Michigan researchers aims to build a highly phenotyped registry of ED patients evaluated for traumatic brain injury. This registry will serve as an important data source for:
• Validating the diagnostic accuracy of GFAP and UCH-L1 in a pragmatic setting;
• Determining whether GFAP and UCH-L1 contribute new diagnostic information to what is known from existing brain CT decision rules;
• Refining the team’s prognostic model for predicting short-term outcomes from TBI;
• Generating preliminary data for future NIH/DoD funded multi-center funded validation of a prognostic model for predicting TBI outcomes;
• Serving as a data source for identifying patients for TBI studies occurring at the University of Michigan;
• Serving as a rich data source for testing novel hypotheses generated by resident physicians and junior faculty.
Significant Need
Acute evaluation of TBI is limited by the following:
• Overuse of brain CT scans both during the initial evaluation of TBI and in reassessing those with traumatic intracranial hemorrhage on the initial brain CT scan;
• Lack of diagnostic tools to guide decisions regarding who needs additional intensive care, or neurocognitive, neuropsychiatric and rehabilitation services.
Several rules exist to guide decisions regarding brain CT utilization in the acute evaluation of TBI. However, these rules are used variably. They also limited in scope because they do not guide decisions for important patient subgroups such as patients who are 65 years and older and have minimal trauma, patients on anticoagulation, and patients presenting >24 after injury.
The FDA has cleared two biomarkers, Glial Fibrillary Acidic Protein (GFAP) and Ubiquitin carboxy-terminal Hydrolase L1 (UCH-L1) measured on the Abbott iSTAT for identifying patients who need a brain CT. However, several gaps exist in our knowledge of how these biomarkers may be used to improve care delivery and outcomes from TBI.
Competitive Advantage
The development of this database will enable the team to develop a novel evaluation algorithm that will optimize the clinical care provided to TBI patients, with an intended goal of improving clinical outcomes.
Funding Organization(s)
Publications
None at this time