Purpose: Quantitative - PowerPoint Presentation

1. Purpose: Quantitative pupillometry (qPLR) is a promising method of detecting and characterizing the severity of traumatic brain injuries. However, the specific extent to which the pupillary light reflex (PLR) can be expected to change as a normal part of the aging process is not known. We hypothesized that PLR parameters, specifically the pupil’s constriction latency, velocity, amplitude, and recovery time, as well as the discordance in each of these parameters between the left and right eyes, would quantifiably change with increasing age. This data will aid us in making a correction factor for a patient’s age when developing qPLR as a diagnostic tool in the future.Methods: A prospective cross-sectional study was conducted. 153 adults were enrolled from the University of Michigan Hospital Emergency Department. Utilizing a Gaze Point High Definition Eye Tracker, a device that continuously records the size of the pupils, two sets of PLR parameters were measured in both the right and left eyes of each subject. Demographics, current medications, and medical and neurological history were obtained from patient interviews and medical records. SPSS statistics were utilized to perform linear regression analyses with age as a continuous variable being the main predictor for the PLR parameter outcomes. Potential confounding variables were examined and analyzed using linear regression.Results: Among all PLR parameters, age was a significant predictor of right eye latency (p=0.019), discordance between right and left eye latencies (p=0.043), and discordance between right and left amplitudes (p=0.015). We can predict that right eye latency will increase by a factor of 1.147 ms/year, discordance between right and left eye latencies will increase by 0.9569 ms/year, and discordance between right and left eye amplitudes will increase by 0.007 mm/year. Age was not a significant predictor of latency of the left eye, or velocity, amplitude, or recovery of either eye. Age was also not a significant predictor of discordance between left and right eye velocity or recovery. Conclusions: We can tentatively predict that when utilizing qPLR to evaluate for brain injury, an age-based correction factor should be accounted for when evaluating right eye latency as well as discordances in latency and amplitude between eyes. Further analysis will be conducted following additional patient enrollment to solidify predictions and to elicit why age seems to be predictive of increased latency in the right but not left eye. However, these preliminary results show that less correction for the natural aging process may be needed than previously expected, as most of the parameters we analyzed did not significantly change with age. Discordance between left and right eye measurements: Age was a significant predictor of discordance between right and left eye latencies (p=0.043). Discordance between right and left eye latencies will increase by 0.9569 ms/year.Age was a significant predictor of discordance between right and left amplitudes (p=0.015). Discordance between right and left eye amplitudes will increase by 0.007 mm/year. Age was not a significant predictor of discordance between left and right eye velocity or time to recovery. An Investigation of the Relationship Between Pupillary Light Reflex and Age, Utilizing Quantitative Pupillometry Jacqueline Vidosh; Uzma Umar, MPH; Matthew Lewis, PhD; Brigid Rowell, MA; William Meurer, MD, MSDepartment of Emergency Medicine, University of Michigan, Ann Arbor, MI INTRODUCTIONMETHODSFUTURE RESEARCHCONCLUSIONSRESULTSABSTRACTCONTACTJacqueline Vidosh University of Michigan Medical SchoolEmail: jvidosh@med.umich.eduFigure 1. PLR Parameters, including: the onset latency , which measures the time between the light stimulus and start of constriction; the time to maximal constriction, ; the recovery time, , which measures the time it takes for the pupil to recover to 50% of its original value; and maximal/minimal constriction amplitudes, and .SPSS statistics were utilized to perform linear regression analyses with age as a continuous variable being the main predictor for the PLR parameter outcomes. Potential confounding variables were examined and analyzed using linear regression. Quantitative pupillometry (qPLR) is a promising method of detecting and characterizing the severity of traumatic brain injury (TBI). The pupillometer delivers a light stimulus to the eye and measures the subsequent pupillary light reflex (PLR) with a camera; this method has been shown to be significantly more accurate than trained providers in detecting abnormalities in pupillary evaluation. However, there is currently no research that quantifies the expected ranges of PLR parameters that are normal in individuals as they age.We hypothesized that pupillary light reflexes, specifically the pupil’s constriction latency, velocity, amplitude, and recovery time, as well as the discordance in each of these parameters between the left and right eyes, would quantifiably change with increasing age. This data will aid us in making a correction factor for a patient’s age when developing qPLR as a diagnostic tool for TBI.Age was a significant predictor of right eye latency (p=0.019). We can predict that right eye latency will increase by a factor of 1.147 ms/year. Age was not a significant predictor of left eye latency.Figure 2. Latency vs. Age Figure 3. Velocity vs. Age Figure 4. Amplitude vs. Age Age was not a significant predictor of right or left eye velocity.Age was not a significant predictor of right or left eye amplitude.Figure 5. Time to Recovery vs. Age Age was not a significant predictor of right or left eye time to recovery.RESULTSWe can tentatively predict that when utilizing qPLR to evaluate for brain injury, an age-based correction factor should be accounted for when evaluating right eye latency as well as discordances in latency and amplitude between eyes. Further analysis will be conducted following additional patient enrollment to solidify predictions and to elicit why age seems to be predictive of increased latency in the right but not left eye. However, these preliminary results show that less correction for the natural aging process may be needed than previously expected, as most of the parameters we analyzed did not significantly change with age.REFERENCESCouret, D., D. Boumaza, C. Grisotto, T. Triglia, L. Pellegrini, P. Ocquidant, N. J. Bruder and L. J. Velly (2016). "Reliability of standard pupillometry practice in neurocritical care: an observational, double-blinded study." Critical Care 20(1): 1-9.Clusmann, H., C. Schaller, and J. Schramm (2001). “Fixed and dilated pupils after trauma, stroke, and previous intracranial surgery: management and outcome.” Journal of Neurology, Neurosurgery & Psychiatry 72(2): 175-181. Marmarou A, J. Lu, I. Butcher, G.S. McHugh, Murray G.D, E.W. Steyerberg, N.A Mushkudiani, S. Choi, A. I. Maas (2007). “Prognostic value of the Glasgow Coma Scale and pupil reactivity in traumatic brain injury assessed pre-hospital and on enrollment: an IMPACT analysis.” Journal of Neurotrauma 24(2): 270-280.Meeker M, R. Du, P. Bacchetti, C.M. Privitera, M.D. Larson, M.C. Holland, and G. Manley (2005). “Pupil examination: validity and clinical utility of an automated pupillometer.” Journal of Neuroscience Nursing 37(1): 34-40. Muppidi, S. B .Adams-Huet, E. Tajzoy, et al (2013) “Dynamic pupillometry as an autonomic testing tool.” Clinical Autonomic Research 23(6): 297. Sharma, S., M. Baskaran, A.V. Rukmini, et al (2016). “Factors influencing the pupillary light reflex in healthy individuals.” Graefe’s Archive for Clinical and Experimental Ophthalmology 254(7): 1353. Photo 1. Johnny-6, a Gaze-Point High Definition Eye Tracker Device, was utilized to obtain two sets of PLR parameters from 153 adults in the UM Emergency Department.Preliminary results have shown significant differences in the PLR responses between TBI and non-TBI patients.Figure 6. There is a significant decrease in the constriction latency of TBI patients compared to non-TBI patients (p = 0.004).Figure 7. There is a significant decrease in the constriction velocity of TBI patients compared to non-TBI patients (p < 0.001).Figure 8. There is a significant decrease in constriction amplitude of TBI patients compared to non-TBI patients (p < 0.001).