Mobile Digital Pupillometry for Rapid Triage of Patients With Severe Traumatic Brain Injury

Lynn B McGrath, Jessica C Eaton, Anthony Law, Alex Mariakakis, Shwetak Patel, Michael R Levitt
PupilScreen uses convolutional neural networks to track the pupillary light reflex (PLR)


Traumatic brain injury (TBI) is the leading cause of mortality in people under age 45 and accounts for 2.5 million ED visits and $75 billion in healthcare costs each year in the United States. The key to ensuring the best possible clinical outcome for TBI patients is to facilitate their care at a designated trauma center. Unfortunately, up to 60% of severe TBI patients are undertriaged and admitted to non-trauma hospitals, a systemic problem which the National Study on the Costs and Outcomes of Trauma has demonstrated results in an excess mortality of 25%. Evaluation of the pupillary light reflex (PLR) is a crucial factor in triaging TBI patients, but penlight-based manual pupillometry is known to be inaccurate and digital infrared pupillometry impractical for field use. PupilScreen, a pupillometry technology developed for smartphones, integrates the convenience of manual pupillometry with the accuracy of a digital infrared pupillometer and may represent a practical way to improve the triage of severe TBI patients.