Researchers Dive Into TBI Data to Better Classify Such Injuries
A patient brought to urgent care and emergency rooms for a traumatic brain injury (TBI) will have their injury sorted into a classification based on its severity. For the most part, a TBI can be considered mild, moderate, or severe, and there are even non-traumatic brain injuries. While the classification system helps doctors decide upon treatments, both immediate and future, University of Arizona researchers are afraid it is still too generalized.
Each traumatic brain injury is significantly different from the next. Even when the cause of one TBI is quite similar to another TBI case, the end results, consequences, and lingering injuries will be unique. To enhance a medical provider’s ability to identify the real extent of a TBI and predict what sort of health complications it will cause down the line, Vignesh Subbian spearheaded in-depth research into TBI datasets with the goal of refining classifications. With clearer and truer classifications and predictions, patient treatments will be elevated.
A TBI patient who survives the initial harm and complications caused by their injury will have an uncertain recovery. If the preexisting TBI classifications can be refined, and potentially splintered into more subsets, then doctors can apply better treatments. Family members, caregivers, and the patient themselves could also be given more direct and realistic expectations regarding the route to maximum medical improvement (MMI). The researchers are also hopeful the study of the datasets will pave the way for successful clinical trials, which will in turn allow for improved sciences and tools for future studies. As a member of the University of Arizona Department of Biomedical Engineering and the Department of Systems and Industrial Engineering, Subbian has bridged multiple departments to collaborate and work towards new solutions that may change the future of TBI treatments around the world.
(Interested in learning more about Subbian’s research? You can click here for a full article from EurekAlert!)
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