Pupillometry
[7] In 2019, the first smartphone based pupillometer was released as an accurate and economical way to determine pupil size and dynamic response objectively.
Numerous studies have shown the importance of pupil evaluation in the clinical setting, and pupillary information is used extensively in patient management and as an indication for possible medical intervention.
[10][2][11][12][13][14][15][16][17][18][19][20] Blood flow imaging has shown that pupil changes are highly correlated with brainstem oxygenation and perfusion,[19][18][21] and anisocoria can be an indicator of a pathological process or neurological dysfunction.
Numeric scales allow for a more rigorous interpretation and classification of the pupil response and are a primary feature of both hardware and software based pupillometers.
Automated pupillometry removes subjectivity from the pupillary evaluation, providing more accurate and trendable pupil data, and allowing earlier detection of changes for more timely patient treatment.
With an automated pupillometer and an algorithm analyzing the pupil continuously for 5 seconds, the Quantitative Pupillometry Index (QPi) can measure pupillary reactivity and provides a numerical value.
The NeuroLight pupillometer (IDMED), on the other hand, provides this pupillary unrest in ambient light (PUAL) function, which is described as a consistent indicator of opioid effect and is the gold standard in this field of research.
This design feature not only enhances the accuracy of the pupillary measurements[7] but also reduces the overall cost of usage to the initial purchase of the device.
According to the new American Heart Association guidelines, most deaths attributable to post-cardiac arrest brain injury are due to active withdrawal of life-sustaining treatment based on a predicted poor neurological outcome.
The NPi and automated pupillometry have recently been included in the updated 2020 American Heart Association (AHA) Guidelines for Cardiopulmonary Resuscitation (CPR) and Emergency Cardiovascular Care (ECC) as an object measurement supporting brain injury prognosis in patients following cardiac arrest.
[36] A study published in the Journal of Neurosurgery found that automated pupillometers may signal an early warning of potential delayed cerebral ischemia and enable preemptive escalation of care.
It concluded that automated pupillometry is a necessary tool for accuracy and consistency, and that it might facilitate earlier detection of subtle pupil changes, allowing more effective and timely diagnostic and treatment interventions.
[1] In addition, a study from The University of Texas Southwestern Medical Center compared 2,329 manual pupillary exams performed simultaneously by two examiners (neurology and neurosurgery attending and resident physicians, staff nurses, and mid-level practitioners) under identical conditions and showed low inter-examiner reliability.
Advancements in mobile-based automated pupillometry have been made in recent years to accommodate for the growing number of mobile phones being used in healthcare.
[40] Smartphone pupillometry has been clinically validated in the context of traumatic brain injury,[41][42] sports related concussion,[43] and acute large vessel occlusion.
[53] Vacchiano and colleagues (1968) found that pupillary responses were associated with visual exposure to words with high, neutral or low value.
