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Updated: May 6, 2026

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury
Published on: May 27, 2022
Clinical assessment of a Near-Infrared spectroscopy device for rapid triage in traumatic brain injury
Vedang Bhushan Mahajan1, Vivek Tandon1, Sri Surya Krishna Gour1
1Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi, India.
Background:
Traumatic Brain Injury (TBI) poses a significant public health challenge in India, with nearly 2 million cases annually and limited CT availability causing delays in diagnosis. This study evaluated CEREBO®, a machine learning-enhanced near-infrared spectroscopy (mNIRS) device, as a rapid, non-invasive triage tool for TBI.
Methodology:
A prospective quasi-experimental study was conducted at AIIMS, New Delhi, enrolling 202 suspected TBI patients. Participants were divided into control (standard care) and experimental (standard care + CEREBO®) groups. CEREBO® findings were compared with CT as the gold standard. Diagnostic performance (sensitivity, specificity, accuracy), time to preliminary diagnosis, and potential of impact on triage decisions were assessed.
Results:
CEREBO® demonstrated high diagnostic performance with 98% sensitivity, 90% specificity, and 93.9% accuracy for detecting intracranial pathology. In a post-hoc exploratory simulation, using CEREBO®'s negative result as a hypothetical criterion for deferring CT suggested that CT imaging could have been potentially avoided in 82.1% of red (critical condition) cases and 80.6% of yellow (stable but urgent) cases. These simulations also indicated that CEREBO® may help identify patients whose urgency of care could be underestimated by initial triage classification.
Conclusion:
The NIRS device demonstrated rapid, non-invasive assessment capability across a broad patient population, supporting its potential utility as an adjunct screening tool in resource-limited trauma settings. These findings suggest that the device may help streamline triage, optimize CT utilization, and improve workflow efficiency in high-volume emergency environments.
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