Traumatic Brain Injury: What Happens Next?


When a patient sustains a traumatic brain injury, or TBI, and is admitted to a trauma center, clinicians classify the severity of the injury as either mild, moderate or severe – the same way they assess the consciousness level of anyone who walks into the emergency room.

But the differences between TBIs, from when they first happen to the days following the primary injury to their outcomes years later, are hugely variable. One side effect of using such broad classifications for these injuries is that clinicians are unable to reliably predict both short- and long-term outcomes for patients.

“Every traumatic brain injury is unique,” said Vignesh Subbian, assistant professor in the UA Department of Biomedical Engineering and the UA Department of Systems and Industrial Engineering. “Let’s say two people fall down the stairs the same way and get hit in the exact same place. They’re still going to have different traumatic brain injuries. We can’t change what happened – the primary injury – but there is room to prevent further damage to the brain.”

Subbian, who is also a member of the UA BIO5 Institute, is principal investigator on a new grant from the National Science Foundation, or NSF, to help better characterize TBIs and predict their outcomes – and therefore, more effectively treat them. The grant brings together key researchers and clinicians from other institutions, including Emory University, the University of Cincinnati and Virginia Tech, with nearly $1.2 million in support from NSF overall.

“This NSF award exemplifies a successful collaboration among systems and industrial engineering, biomedical engineering, computer science and health sciences to work on a complex, interdisciplinary problem that has a high impact on our society,” said Young-Jun Son, department head of systems and industrial engineering.

Traumatic brain injury is an area in dire need of better predictive tools and further research. It is the leading cause of death and disability for individuals under age 44, and an estimated 1.7 million cases of TBI occur in the United States every year.

“TBIs pose a significant public health burden, often resulting in long-term disability and poor quality of life,” said Subbian, who has been working in TBI research for nearly eight years.

Delving Into Large Clinical Datasets

Using analytical techniques and data gathered from advanced monitoring of brain injury patients, researchers will develop methods to better classify TBI patients and predict what might happen next.

“This will allow clinicians to provide the right care to the right TBI patient at the right time,” Subbian said.

Currently, if patients survive their time in the intensive care unit, the extent of their recovery is uncertain. The tools developed through this research could allow for targeted allocation of resources and help set expectations for family members and other caregivers. It could also inform clinical researchers on how to select patients for TBI clinical trials, 100 percent of which have failed over the past 30 years.

“In the future, we might be able to identify patients best suited for specific TBI clinical trials,” Subbian said. “Not accounting for the wide variation in TBI cases is one of the reasons all clinical trials failed in the past.”

A Stepping Stone to Wider Applications

Although this work will initially be focused on TBIs, the methods researchers develop will be applicable to other critically ill patients, such as those with cardiovascular disorders.

“This project is a stepping stone,” Subbian said. “We’re going to use this project to generate a wide range of prototypical tools, and then we’re really going to push for generalizability.”

The research is funded by the Smart and Connected Health Program, a partnership between multiple federal agencies, including the NSF and the National Institutes of Health, or NIH, that aims to transform health and medicine by integrating methods from different disciplines, including computing and information sciences and engineering. Subbian, who is the university’s first and only joint appointee between the departments of biomedical engineering and systems and industrial engineering, serves as a bridge between computational and systems engineering methods and biomedical problems.

“NSF and NIH developed this program to catalyze multidisciplinary collaborations and facilitate fundamental, integrative research that will address large, grand-challenge problems in medicine and healthcare,’” Subbian said. “Our project is an example of one of the cross-cutting areas I was recruited to lead.”

Biomedical engineering department head Art Gmitro said Subbian has been a fantastic addition to the department’s faculty.

“Not only has he developed an active research program in the area of medical informatics and health care systems engineering, as evidenced by this grant, but he has also proven to be an outstanding teacher and mentor for our students,” he said.

A version of this article originally appeared on the UA College of Engineering website:

Resources for the Media