The pupillary light reflex (PLR) is an important biomarker for the detection and management of traumatic brain injury (TBI). We investigated the performance of PupilScreen, a smartphone-based pupillometry app, in classifying healthy control subjects and subjects with severe TBI in comparison to the current gold standard NeurOptics pupillometer (NPi-200 model with proprietary Neurological Pupil Index [NPi] TBI severity score). A total of 230 PLR video recordings taken using both the PupilScreen smartphone pupillometer and NeurOptics handheld device (NPi-200) pupillometer were collected from 33 subjects with severe TBI (sTBI) and 132 subjects who were healthy without self-reported neurological disease. Severe TBI status was determined by Glasgow Coma Scale (GCS) at the time of recording. The proprietary NPi score was collected from the NPi-200 pupillometer for each subject. Seven PLR curve morphological parameters were collected from the PupilScreen app for each subject. A comparison via t-test and via binary classification algorithm performance using NPi scores from the NPi-200 and PLR parameter data from the PupilScreen app was completed. This was used to determine how the frequently used NPi-200 proprietary NPi TBI severity score compares to the PupilScreen app in ability to distinguish between healthy and sTBI subjects. Binary classification models for this task were trained for the diagnosis of healthy or severe TBI using logistic regression, k-nearest neighbors, support vector machine, and random forest machine learning classification models. Overall classification accuracy, sensitivity, specificity, area under the curve, and F1 score values were calculated. Median GCS was 15 for the healthy cohort and 6 (interquartile range 2) for the severe TBI cohort. Smartphone app PLR parameters as well as NPi from the digital infrared pupillometer were significantly different between healthy and severe TBI cohorts; 33% of the study cohort had dark eye colors defined as brown eyes of varying shades. Across all classification models, the top performing PLR parameter combination for classifying subjects as healthy or sTBI for PupilScreen was maximum diameter, constriction velocity, maximum constriction velocity, and dilation velocity with accuracy, sensitivity, specificity, area under the curve (AUC), and F1 score of 87%, 85.9%, 88%, 0.869, and 0.85, respectively, in a random forest model. The proprietary NPi TBI severity score demonstrated greatest AUC value, F1 score, and sensitivity of 0.648, 0.567, and 50.9% respectively using a random forest classifier and greatest overall accuracy and specificity of 67.4% and 92.4% using a logistic regression model in the same classification task on the same dataset. The PupilScreen smartphone pupillometry app demonstrated binary healthy versus severe TBI classification ability greater than that of the NPi-200 proprietary NPi TBI severity score. These results may indicate the potential benefit of future study of this PupilScreen smartphone pupillometry application in comparison to the NPi-200 digital infrared pupillometer across the broader TBI spectrum, as well as in other neurological diseases.

We examined the associations between the Neurological Pupillary Index (NPi) and disposition at hospital discharge in patients admitted to the neurocritical care unit with acute brain injury (ABI) due to acute ischemic stroke (AIS), spontaneous intracerebral hemorrhage (sICH), aneurysmal subarachnoid hemorrhage (SAH), and traumatic brain injury (TBI). The primary outcome was discharge disposition (home/acute rehabilitation vs. death/hospice/skilled nursing facility). Secondary outcomes were tracheostomy tube placement and transition to comfort measures. Among 2258 patients who received serial NPi assessments within the first seven days of ICU admission, 47.7% (n = 1078) demonstrated NPi ≥ 3 on initial and final assessments, 30.1% (n = 680) had initial NPI < 3 that never improved, 19% (n = 430) had initial NPi ≥ 3, which subsequently worsened to <3 and never recovered, and 3.1% (n = 70) had initial NPi < 3, which improved to ≥3. After adjusting for age, sex, admitting diagnosis, admission Glasgow Coma Scale score, craniotomy/craniectomy, and hyperosmolar therapy, NPi values that remained <3 or worsened from ≥3 to <3 were associated with poor outcomes (adjusted odds ratio, aOR 2.58, 95% CI [2.03; 3.28]), placement of a tracheostomy tube (aOR 1.58, 95% CI [1.13; 2.22]), and transition to comfort measures only (aOR 2.12, 95% CI [1.67; 2.70]). Our study suggests that serial NPi assessments during the first seven days of ICU admission may be helpful in predicting outcomes and guiding clinical decision-making in patients with ABI. Further studies are needed to evaluate the potential benefit of interventions to improve NPi trends in this population.

Background: Traumatic brain injury (TBI) is a leading cause of disability but one of the least recognized health problems in the world, affecting up to 69 million people annually. The associated lifelong disability in survivors, the loss of economic productivity, and being a risk factor for dementia consume 0.5% of global economic activity. Yet TBI is still largely invisible in national surveillance systems and not well represented in chronic disease frameworks. Consequently, governments are not equipped to provide proportional financing of acute care and long-term care of survivors, nor to build health care systems and resources for improving outcomes of TBI through policy frameworks targeting prevention, treatment, and equitable access. Objective: This commentary aims to provide a comprehensive picture of the global effort to formally recognize TBI as a notifiable and chronic condition, including the justifications for recognition, the formation of an international coalition of stakeholders, and the strategic plan for resolution at WHA79 of the World Health Assembly, one of the first concerted multinational efforts that occurred as a side event during the 78th World Health Assembly (WHA78) in May 2025. Methods: This commentary integrates information from epidemiological studies, global registries, and testimonies from people with lived experience of TBI. We analyze these data to develop policy needs and corresponding initiatives to address key needs. These include coordinated efforts to advocate change, such as technical briefings, consultations with stakeholders, and storytelling led by survivors, all of which informed and formed a part of the WHA78 side event. Our efforts have garnered wide, multi-sector support. Results: The WHA78 side event showed that ministries of health, neurosurgical, neurological, and rehabilitation societies, academic researchers, WHO representatives, and survivors all unprecedentedly support the recognition of the importance of TBI, facilitating national policies for its prevention and treatment via standardized surveillance. More than 30 non-governmental groups officially supported the campaign. A sponsoring member state made a public commitment to co-sponsor a WHA resolution, which set the stage for ongoing diplomatic progress and engagement across regions. Conclusion: To improve global brain health equity, access to long-term care, and the resilience of health systems, it is important to recognize TBI as a notifiable and chronic condition. A dedicated WHA resolution would make TBI a part of global health governance, making sure that it is counted, tracked, and dealt with as quickly and comprehensively as possible. It is both a technical necessity and a moral duty to help survivors and families and fight for justice in global health systems.

An electronic survey was administered to multidisciplinary neurocritical care providers at 365 hospitals in 32 countries to describe intrahospital transport (IHT) practices of neurocritically ill patients at their institutions. The reported IHT practices were stratified by World Bank country income level. Variability between high-income (HIC) and low/middle-income (LMIC) groups, as well as variability between hospitals within countries, were expressed as counts/percentages and intracluster correlation coefficients (ICCs) with a 95% confidence interval (CI). A total of 246 hospitals (67% response rate; n = 103, 42% HIC and n = 143, 58% LMIC) participated. LMIC hospitals were less likely to report a portable CT scanner (RR 0.39, 95% CI [0.23; 0.67]), more likely to report a pre-IHT checklist (RR 2.18, 95% CI [1.53; 3.11]), and more likely to report that intensive care unit (ICU) physicians routinely participated in IHTs (RR 1.33, 95% CI [1.02; 1.72]). Between- and across-country variation were highest for pre-IHT external ventricular drain clamp tolerance (reported by 40% of the hospitals, ICC 0.22, 95% CI 0.00–0.46) and end-tidal carbon dioxide monitoring during IHT (reported by 29% of the hospitals, ICC 0.46, 95% CI 0.07–0.71). Brain tissue oxygenation monitoring during IHT was reported by only 9% of the participating hospitals. An IHT standard operating procedure (SOP)/hospital policy (HP) was reported by 37% (n = 90); HIC: 43% (n= 44) vs. LMIC: 32% (n = 46), p = 0.56. Amongst the IHT SOP/HPs reviewed (n = 13), 90% did not address the continuation of hemodynamic and neurophysiological monitoring during IHT. In conclusion, the development of a neurocritical-care-specific IHT SOP/HP as well as the alignment of practices related to the IHT of neurocritically ill patients are urgent unmet needs. Inconsistent standards related to neurophysiological monitoring during IHT warrant in-depth scrutiny across hospitals and suggest a need for international guidelines for neurocritical care IHT.