Evaluating the utility of quantitative pupillometry in a neuro-critical care setting for the monitoring of intracranial pressure: A prospective cohort study.

INTRODUCTION: Assessment of the pupillary light reflex (PLR) is key in intensive care monitoring of neurosurgical patients, particularly for monitoring intracranial pressure (ICP). Quantitative pupillometry using a handheld pupillometer is a reliable method for PLR assessment. However, many variables are derived from such devices. We therefore aimed to assess the performance of these variables at monitoring ICP. METHODS: Sedated patients admitted to neurocritical care in a tertiary neurosurgical centre with invasive ICP monitoring were included. Hourly measurement of ICP, subjective pupillometry (SP) using a pen torch device, and quantitative pupillometry (QP) using a handheld pupillometer were performed. RESULTS: 561 paired ICP, SP and QP pupillary observations from nine patients were obtained (1122 total pupillary observations). SP and QP had a moderate concordance for pupillary size (κ=0.62). SP performed poorly at detecting pupillary size changes (sensitivity=24%). In 40 (3.6%) observations, SP failed to detect a pupillary response whereas QP did. Moderate correlations with ICP were detected for maximum constriction velocity (MCV), dilation velocity (DV), and percentage change in pupillary diameter (%C). Discriminatory ability at an ICP threshold of >22 mmHg was moderate for MCV (AUC=0.631), DV (AUC=0.616), %C (AUC=0.602), and pupillary maximum size (AUC=0.625). CONCLUSION: QP is superior to SP at monitoring pupillary reactivity and changes to pupillary size. Although effect sizes were moderate to weak across assessed variables, our data indicates MCV and %C as the most sensitive variables for monitoring ICP. Further study is required to validate these findings and to establish normal range cut-offs for clinical use.

Prediction for the prognosis of diffuse axonal injury using automated pupillometry.

OBJECTIVE: Previous studies have reported various predictive indicators of diffuse axonal injury (DAI), but no consensus has not been reached. Although the efficiency of automated pupillometry in patients with consciousness disorder has been widely reported, there are few reports of its use in patients with DAI. This study aimed to investigate the significance of pupillary findings in predicting the prognosis of DAI. PATIENTS AND METHODS: We included patients admitted to our center with a diagnosis of DAI from June 1, 2021 to June 30, 2022. Pupillary findings in both eyes were quantitatively measured by automated pupillometry every 2 hours after admission. We statistically examined the correlations between automated pupillometry parameters, the patients' characteristics, and outcomes such as the Glasgow Outcome Scale Extended (GOSE) after 6 months from injury, the time to follow command, and so on. RESULTS: Among 22 patients included in this study, five had oculomotor nerve palsy. Oculomotor nerve palsy was correlated with all outcomes, whereas Marshall computed tomography (CT) classification, Injury severity score (ISS) and DAI grade were correlated with few outcomes. Some of the automated pupillometry parameters were significantly correlated with GOSE at 6 months after injury, and many during the first 24 hours of measurement were correlated with the time to follow command. Most of these results were not affected by adjustment using sedation period, ISS or Marshall CT classification. A subgroup analysis of patients without oculomotor nerve palsy revealed that many of the automated pupillometry parameters during the first 24 hours of measurement were significantly correlated with most of the outcomes. The cutoff values that differentiated a good prognosis (GOSE 5-8) from a poor prognosis (GOSE 1-4) were constriction velocity (CV) 1.43 (AUC = 0.81(0.62-1), p = 0.037) and maximum constriction velocity (MCV) 2.345 (AUC = 0.78 (0.58-0.98), p = 0.04). The cutoff values that differentiated the time to follow command into within 7 days and over 8 days were percentage of constriction 8 (AUC = 0.89 (0.68-1), p = 0.011), CV 0.63 (AUC = 0.92 (0.78-1), p = 0.013), MCV 0.855 (AUC = 0.9 (0.74-1), p = 0.017) and average dilation velocity 0.175 (AUC = 0.95 (0.86-1), p = 0.018). CONCLUSIONS: The present results indicate that pupillary findings in DAI are a strong predictive indicator of the prognosis, and that quantitative measurement of them using automated pupillometry could facilitate enhanced prediction for the prognosis of DAI.

Pupillary Responses Reflect Dynamic Changes in Multiple Cognitive Factors During Associative Learning in Primates.

Associative learning involves complex interactions of multiple cognitive factors. While adult subjects can articulate these factors verbally, for model animals such as macaques, we rely on behavioral outputs. In our study, we used pupillary responses as an alternative measure to capture these underlying cognitive changes. We recorded the dynamic changes in the pupils of three male macaques when they learned the associations between visual stimuli and reward sizes under the classical Pavlovian experimental paradigm. We found that during the long-term learning process, the gradual changes in the pupillary response reflect the changes in the cognitive state of the animals. The pupillary response can be explained by a linear combination of components corresponding to multiple cognitive factors. These components reflect the impact of visual stimuli on the pupils, the prediction of reward values associated with the visual stimuli, and the macaques' understanding of the current experimental reward rules. The changing patterns of these factors during interday and intraday learning clearly demonstrate the enhancement of current reward-stimulus association and the weakening of previous reward-stimulus association. Our study shows that the dynamic response of pupils can serve as an objective indicator to characterize the psychological changes of animals, understand their learning process, and provide important tools for exploring animal behavior during the learning process.

Prospective study examining the impact of cerebral angiography on quantitative pupillometer values in the interventional radiology suite.

OBJECTIVES: The purpose of this pilot study was to obtain baseline quantitative pupillometry (QP) measurements before and after catheter-directed cerebral angiography (DCA) to explore the hypothesis that cerebral angiography is an independent predictor of change in pupillary light reflex (PLR) metrics. DESIGN: This was a prospective, observational pilot study of PLR assessments obtained using QP 30 min before and after DCA. All patients had QP measurements performed with the NPi-300 (Neuroptics) pupillometer. SETTING: Recruitment was done at a single-centre, tertiary-care academic hospital and comprehensive stroke centre in Dallas, Texas. PARTICIPANTS: Fifty participants were recruited undergoing elective or emergent angiography. Inclusion criteria were a physician-ordered interventional neuroradiological procedure, at least 18 years of age, no contraindications to PLR assessment with QP, and nursing transport to and from DCA. Patients with a history of eye surgery were excluded. MAIN OUTCOME MEASURES: Difference in PLR metric obtained from QP 30 min before and after DCA. RESULTS: Statistically significant difference was noted in the pre and post left eye readings for the minimum pupil size (a.k.a., pupil diameter on maximum constriction). The mean maximum constriction diameter prior to angiogram of 3.2 (1.1) mm was statistically larger than after angiogram (2.9 (1.0) mm; p<0.05); however, this was not considered clinically significant. Comparisons for all other PLR metrics pre and post angiogram demonstrated no significant difference. Using change in NPi pre and post angiogram (Δpre=0.05 (0.77) vs Δpost=0.08 (0.67); p=0.62), we calculated the effect size as 0.042. Hence, detecting a statistically significant difference in NPi, if a difference exists, would require a sample size of ~6000 patients. CONCLUSIONS: Our study provides supportive data that in an uncomplicated angiogram, even with intervention, there is no effect on the PLR.

The value of pupillary diameter in evaluating pain perception after awakening in patients undergoing general anesthesia during orthopedic surgery.

BACKGROUND: The pupillary response to tetanic electrical stimulation reflects the balance between nociceptive stimulation and analgesia. Although pupillary pain index (PPI) was utilized to predict postoperative pain, it depended on tetanic stimulation and was complex. We aim to describe the potential relationship between PD in the presence of surgical stimulation and pain levels after awakening. METHODS: According to the Verbal Rating Scale (VRS) score after extubation, the patients were divided into painless group (VRS = 0) and pain group (VRS ≥ 1). Pupillary diameter (PD) and pupillary light reflex velocity (PLRV) were compared between two groups when patients entered the operating room (T1), before incision (T2), 10 s after incision (T3), 30 s after incision (T4), 1 h after incision (T5), at the end of surgery (T6), shortly after extubation (T7), and when patients expressed pain clearly (T8). The magnitude of PD change (ΔPD) compared to the baseline value after anesthesia induction (T2) was calculated. The correlations between pupillary parameters and pain after awakening were calculated. RESULTS: Patients with VRS ≥ 1 had greater PD than painless patients at T3-7 (P = 0.04, 0.04, 0.003, <0.001, <0.001), and it was positively correlated with VRS score after awakening at T4-7 (r = 0.188, 0.217, 0.684, 0.721). The ability of T6ΔPD to predict VRS ≥ 1 was strong [threshold: 20.53%, area under the curve (AUC): 0.93, 95% confidence interval (CI): 0.89-0.97 ]. CONCLUSION: Our study indicates that PD is a useful index to direct the individualized analgesics used during operation, to better avoid the occurrence of pain during the postoperative emergence period. TRIAL REGISTRATION: This study was registered with the Chinese Clinical Trial Registry (registration number: ChiCTR2000040908, registration date: 15/12/2020).

The use of quantitative pupillometry in brain death determination: preliminary findings.

PURPOSE: Quantitative pupillometry (QP) has been increasingly applied in neurocritical care as an easy-to-use and reliable technique for evaluating the pupillary light reflex (PLR). Here, we report our preliminary findings on using QP for clinical brain death (BD) determination. MATERIALS: This retrospective study included 17 patients ≥ 18 years (mean age, 57.3 years; standard deviation, 15.8 years) with confirmed BD, as defined by German Guidelines for the determination of BD. The PLR was tested using the NPi®-200 Pupillometer (Neuroptics, Laguna Hill, USA), a handheld infrared device automatically tracking and analyzing pupil dynamics over 3 s. In addition, pupil diameter and neurological pupil index (NPi) were also evaluated. RESULTS: Intracerebral bleeding, subarachnoid hemorrhage, and hypoxic encephalopathy were the most prevalent causes of BD. In all patients, the NPi was 0 for both eyes, indicating the cessation of mid-brain function. The mean diameter was 4.9 mm (± 1.3) for the right pupil and 5.2 mm (±1.2) for the left pupil. CONCLUSIONS: QP is a valuable tool for the BD certification process to assess the loss of PLR due to the cessation of brain stem function. Furthermore, implementing QP before the withdrawal of life-sustaining therapy in brain-injured patients may reduce the rate of missed organ donation opportunities. Further studies are warranted to substantiate the feasibility and potential of this technique in treating patients and identify suitable candidates for this technique during the BD certification process.

Feasibility of USG-Guided Objective Initial Assessment of Pupillary Size and Pupillary Reflexes Versus Clinical Examination in Patients With Altered Mental Status: A Cross-Sectional Study.

BACKGROUND: Pupillary assessment is an important part of the neurological assessment which provides vital information in critically ill patients. However, clinical pupillary assessment is subjective. The ultrasound-guided pupillary examination is objective. There are limited pieces of literature regarding its use in assessing patients with altered mental status. So, we studied the extent of agreement of B-mode ultrasound with clinical examination for assessment of the pupillary size and reflex in patients with altered mental status. OBJECTIVES: The primary objective was to determine the extent of agreement between clinical examination and ultrasound-based examination for assessing pupillary reflex and size in patients with altered mental status in two settings (trauma and non-trauma patients). METHODS: Exactly 200 subjects (158 males, mean [range] age 43.56 [18-92 years]) with no history of partial globe rupture or dementia were included in this cross-sectional study from March 2019 to March 2020. B-mode ultrasound was performed with the subject's eyes closed using a 7-12 MHz linear probe and a standardized light stimulus. ICC score, paired t-test, kappa, Wilcoxon signed-rank test, and Bland-Altman plots were used for statistical analysis. RESULTS: The clinical-USG agreement for pupillary light reflex examination (Pupillary Diameter [PD] at rest, after direct light stimulation [Dstim ] and consensual light stimulation [Cstim ]) was excellent (ICC, 0.93-0.96). The Kappa coefficient (0.74 ± 0.07) showed an agreement of 87.36% between clinical and USG examination for pupillary reflex (reactive or non-reactive). CONCLUSION: USG-guided pupillary examination proves to be a better adjunct to neurological assessment in patients with altered mental status.

Overlooked evidence for transmission deficit of pupillary light reflex can be secondary to trigeminal nerve ganglion degeneration following subarachnoid hemorrhage; preliminary experimental study.

OBJECTIVE: Although the effect of oculomotor and cervical sympathetic networks on pupil diameter is well known; the effect of the trigeminal nerve on pupil diameter has not been investigated yet. This subject was investigated. MATERIALS AND METHODS: Five of 23 rabbits were used as a control group (GI; n = 5); 0.5 ccs saline solution into cisterna magna injected animals used as SHAM (GII; n = 5); autologous blood injected to produce SAH used as the study group (GIII; n = 13) and followed up three weeks. Light-stimulated pupil diameters were measured with an ocular tomography device before, middle, and at the end of the experiment. Considering the sclera area/pupil area ratio index (PRI) as the pupillary reaction area, we used this equation for the pupil's rush to light. Degenerated neuron densities of trigeminal ganglia and pupil diameters compared with the Mann-Whitney U test. RESULTS: The PRI, degenerated neuron density of trigeminal ganglia (n/mm3) were: (2.034 ± 0.301)/(13 ± 3) in GI; (1.678 ± 0.211)/(46 ± 9) in GII; and (0.941 ± 0.136)/(112 ± 21) in GIII. P-values between groups as: p < 0.005 in GI/GII; p < 0.0001 in GII/GIII and p < 0.00001 in GI/GIII. CONCLUSION: Light stimulates the cornea which is innervated by the trigeminal nerves. This experimental study indicates that the pupil remains mydriatic as the cornea is damaged by trigeminal ischemia following SAH and blocks the light flow.

The pupillary dilation reflex to a nociceptive stimulus as a tool for analgesia management: A diagnostic study.

BACKGROUND: More than 70% of patients demonstrate pain after endotracheal aspiration. Tools are needed to objectify the need for analgesia in non-communicative critically ill patients. OBJECTIVE: The objective of this study was to identify the lowest intensity electrical stimulus for detecting pain before daily care interventions. METHODS: Study of diagnostic tests to assess pupillometry to detect pain through the pupillary dilation response to noxious stimuli versus the Behavioural Pain Scale. Patients older than 18 years, under analgosedation, subjected to invasive ventilation, baseline Behavioural Pain Scale of 3, and Richmond Agitation-Sedation Scale between -1 and -4 were studied. We assessed the Behavioural Pain Scale and the pupillary dilation response to 10, 20, 30, and 40 mA stimuli. We studied the diagnostic performance based on sensitivity and specificity, negative predictive value, positive predictive value, and accuracy of the selected points after the different stimulations. AlgiScan® Pupillometer measured the pupillary dilation response. The presence of pain was considered as a Behavioural Pain Scale score of ≥4. Significance was defined as p <0.05. RESULTS: Measurements were performed on 31 patients. In the 20 mA stimulus, we found an area under the curve of 0.85 (0.69-1.0). The cut-off point of pupillary dilation was 11.5%, with a sensitivity of 100% (34.2-100) and a specificity of 75.9% (57.9-87.8). This point had an accuracy of 77.4 (60.2-88.6) and a Youden's Index of 0.8. CONCLUSIONS: Pupillary variation measurement during a 20 mA stimulus could help assess the need for analgesia before potentially painful interventions. Further studies are needed to confirm this. REGISTRATION: Phase 1 of the project PUPIPAIN ClinicalTrials.gov Identifier: NCT04078113.

Nociception assessment with videopupillometry in deeply sedated intensive care patients: Discriminative and criterion validations.

BACKGROUND: Nociceptive assessment in deeply sedated patients is challenging. Validated instruments are lacking for this unresponsive population. Videopupillometry is a promising tool but has not been established in intensive care settings. AIM/OBJECTIVE: To test the discriminate validity of pupillary dilation reflex (PDR) between non-noxious and noxious procedures for assessing nociception in non-neurological intensive care unit (ICU) patients and to test the criterion validity of pupil dilation using recommended PDR cut-off points to determine nociception. METHODS: A single-centre prospective observational study was conducted in medical-surgical ICU patients. Two independent investigators performed videopupillometer measurements during a non-noxious and a noxious procedure, once a day (up to 7 days), when the patient remained deeply sedated (Richmond Agitation-Sedation Scale score: -5 or -4). The non-noxious procedures consisted of a gentle touch on each shoulder and the noxious procedures were endotracheal suctioning or turning onto the side. Bivariable and multivariable general linear mixed models were used to account for multiple measurements in same patients. Sensitivity and specificity, and areas under the curve of the receiver operating characteristic curve were calculated. RESULTS: Sixty patients were included, and 305 sets of 3 measurements (before, during, and after), were performed. PDR was higher during noxious procedures than before (mean difference between noxious and non-noxious procedures = 31.66%). After testing all variables of patient and stimulation characteristics in bivariable models, age and noxious procedures were kept in the multivariable model. Adjusting for age, noxious procedures (coefficient = -15.14 (95% confidence interval = -20.17 to -15.52, p < 0.001) remained the only predictive factor for higher pupil change. Testing recommended cut-offs, a PDR of >12% showed a sensitivity of 65%, and a specificity of 94% for nociception prediction, with an area under the receiver operating curve of 0.828 (95% confidence interval = 0.779-0.877). CONCLUSIONS: In conclusion, PDR is a potentially appropriate measure to assess nociception in deeply sedated ICU patients, and we suggest considering its utility in daily practices. REGISTRATION: This study was not preregistered in a clinical registry. TWEETABLE ABSTRACT: Pupillometry may help clinicians to assess nociception in deeply sedated ICU patients.

Linear integration of multisensory signals in the pupil.

The pupil of the eye responds to various salient signals from different modalities, but there is no consensus on how these pupillary responses are integrated when multiple signals appear simultaneously. Both linear and nonlinear integration have been found previously. The current study aimed to reexamine the nature of pupillary integration, and specifically focused on the early, transient pupillary responses due to its close relationship with orienting. To separate the early pupillary responses out of the pupil time series, we adopted a pupil oscillation paradigm in which sensory stimuli were periodically presented. The simulation analysis confirmed that the amplitude of the pupil oscillation, induced by stimuli repeatedly presented at relatively high rates, can precisely reflect the early, transient pupillary responses without involving the late and sustained pupillary responses. The experimental results then showed that the amplitude of pupil oscillation induced by a series of simultaneous audiovisual stimuli equaled to a linear summation of the oscillatory amplitudes when unisensory stimuli were presented alone. Moreover, the tonic arousal levels, indicated by the baseline pupil size, cannot shift the summation from linear to nonlinear. These findings together support the additive nature of multisensory pupillary integration for the early, orienting-related pupillary responses. The additive nature of pupillary integration further implies that multiple pupillary responses may be independent of each other, irrespective of their potential cognitive and neural drivers.

Functional benefits of cognitively driven pupil-size changes.

Pupil-size changes are typically associated with the pupil light response (PLR), where they are driven by the physical entry of light into the eye. However, pupil-size changes are also influenced by various cognitive processes, where they are driven by higher-level cognition. For example, the strength of the PLR is not solely affected by physical properties of the light but also by cognitive factors, such as whether the source of light is attended or not, which results in an increase or decrease in the strength of the PLR. Surprisingly, although cognitively driven pupil-size changes have been the focus of extensive research, their possible functions are rarely discussed. Here we consider the relative (dis)advantages of small versus large pupils in different situations from a theoretical point of view, and compare these to empirical results showing how pupil size actually changes in these situations. Based on this, we suggest that cognitively driven pupil-size changes optimize vision either through preparation, embodied representations, or a differential emphasis on central or peripheral vision. More generally, we argue that cognitively driven pupil-size changes are a form of sensory tuning: a subtle adjustment of the eyes to optimize vision for the current situation and the immediate future. This article is categorized under: Neuroscience > Cognition Neuroscience > Physiology Neuroscience > Behavior.

A smartphone pupillometry tool for detection of acute large vessel occlusion.

OBJECTIVES: Pupillary light reflex (PLR) parameters can be used as quantitative biomarkers of neurological function. Since digital infrared pupillometry is expensive, we sought to examine alterations in PLR parameters using a smartphone quantitative pupillometry platform in subjects with acute ischemic stroke (AIS). MATERIALS AND METHODS: Patients were enrolled if they presented to the emergency department as a stroke code activation and had evidence of a large vessel occlusion (LVO) on computed tomography angiography. Controls were enrolled from hospital staff. A smartphone pupillometer was used in AIS patients with LVO pre-mechanical thrombectomy, immediately post-thrombectomy, and at 24 h post-thrombectomy. Clinical and demographic data were collected, along with the proprietary Neurological Pupil index (NPi) score from the NPi-200 digital infrared pupillometer. PLR parameters were compared using mean differences. The absolute and non-absolute inter-eye difference in each parameter for each subject were also analyzed by measuring 1 - (R:L) to determine alteration in the equilibrium between subject pupils. The NPi was analyzed for mean differences between cohorts. RESULTS: Healthy controls (n = 132) and AIS patients (n = 31) were enrolled. Significant differences were observed in PLR parameters for healthy subjects when compared to pre-thrombectomy subjects in both mean and absolute inter-eye differences after post hoc Bonferroni correction. The proprietary NPi score was not significantly different for all groups and comparisons. CONCLUSIONS: Significant alterations in the PLR were observed in AIS patients with LVO before thrombectomy, indicating the potential use of smartphone pupillometry for detection of LVO.

The photic blink reflex as an index of photophobia.

Two recent studies of eye closure triggered by intense luminance increase suggest that this behavior reflects the melanopsin-based retinal activity known to underlie photophobia, the pathological aversion to light (Kardon, 2012; Kaiser et al., 2021). Early studies of the photic blink reflex (PBR) are reviewed to help guide future research on this possible objective index of photophobia. Electromyographic recordings of the lid-closure muscle, orbicularis oculi, reveal distinct bursts with typical onset latencies of 50 and 80 ms, R50 and R80, respectively. The latter component appears to be especially sensitive to visual signals from intrinsically photosensitive retinal ganglion cells (ipRGCs) and to prior trigeminal nociceptive stimuli. The authors argue that the R80's function, in addition to protecting the eyeballs from physical contact, is to shape the upper and lower eyelids into a narrow slit to restrict incoming light. This serves to prevent retinal bleaching or injury, while allowing continued visual function.

Chromatic Pupillometry - a New Technique for Assessing Function in Glaucoma? / Chromatische Pupillometrie ­ ein neuer Weg zur funktionellen Glaukomdiagnostik?

Chromatic pupillometry allows quantification of photoreceptor-driven (extrinsic) and melanopsin-driven (intrinsic) responses of the intrinsic-photosensitive retinal ganglion cells (ipRGCs). This small subpopulation of retinal ganglion cells is also affected by glaucoma, making chromatic pupillometry a potential diagnostic tool. Studies show reduced phasic and tonic responses in glaucoma patients. The diagnostic value in earlier studies depended on the technical details and the study design. The purpose of this article is to give an introduction into the principles of chromatic pupillometry and to discuss the potential applications in the management of glaucoma.

Effect of Light Intensity on the Relative Afferent Pupillary Defect in Unilateral Neuro-ophthalmic Pathology.

SIGNIFICANCE: Objective pupillometry with standardized light intensities allows a comprehensive assessment of the relative afferent pupillary defect in patients with unilateral neuro-ophthalmic pathology. PURPOSE: This study aimed to determine the impact of varying light intensities on the grade of relative afferent pupillary defect in unilateral neuro-ophthalmic pathology vis-à-vis healthy controls. METHODS: Monocular pupillary light reflexes of 20 controls (14 to 50 years) and 31 cases (12 to 72 years) with clinically diagnosed relative afferent pupillary defect were measured thrice using 1-second-long light pulses, followed by 3 seconds of darkness, at eight light intensities (6.4 to 1200 lux) using objective pupillometry. The relative afferent pupillary defect was quantified as the ratio of the percentage change in the direct light reflexes of the left and right eyes. Its change with light intensity was described using standard exponential fits. RESULTS: The median (25th to 75th interquartile range) defect score of 54.8% cases decreased from baseline values of 1.58 (1.25 to 1.87) for right eye pathology and 0.45 (0.39 to 0.55) for left eye pathology to saturation values of 1.18 (1.05 to 1.31) and 0.98 (0.95 to 1.06), respectively, at light intensities between 56.9 and 300.5 lux. Like controls (1.01 [1.00 to 1.06]), the defect scores of the remaining 45.2% cases were constant with light intensity at 1.23 (1.18 to 1.46) and 0.87 (0.86 to 0.89) for right and left eye pathologies, respectively. CONCLUSIONS: Relative afferent pupillary defects may decrease with test light intensity in a significant proportion of patients with unilateral neuro-ophthalmic pathology. This highlights the importance of objective pupillometry with standardization light intensities for clinical assessment of afferent pupillary defects.

[Paying attention to the clinical significance of pupil abnormalities].

Pupil abnormalities may be physiological, pathological or pharmacological. It can indicate the underlying disease of the visual afferent system or visual efferent system. Examination of the pupils is therefore a part of eye examination. Insufficient knowledge and inconsistent methods in the pupillary examination by some ophthalmologists lead to mistakes or unreliable results, hampering the disease diagnosis and clinical assessment. This article emphasizes the significance of pupillary examination outcomes, advocates for standardized examination methods, and highlights the need to enhance the awareness of pupillary abnormalities, aiming to provide a guide on how to recognize and interpret the clinical implications of pupillary abnormalities, and to offer valuable insights for clinical practice.

Validation of a Smartphone Pupillometry Application in Diagnosing Severe Traumatic Brain Injury.

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.

Pupillary dilation reflex and behavioural pain scale: Study of diagnostic test.

BACKGROUND: The objective of this study was to assess the value of the pupillary dilation reflex as an assessment pain tool in critically ill patients. It is important to continue working for the well-being and security of critically ill patients. METHODS: We studied the diagnostic accuracy of the pupillary dilation reflex against the Behavioral Pain Scale. Inclusion criteria were: age greater than 18, receiving mechanical ventilation, with a basal score of the Behavioural Pain Scale of three and a Richmond Agitation and Sedation score between -1 and -4. We studied the responses to a non-painful stimulus, four calibrated stimuli, after a tracheal aspiration and with and without pain. The receiver operating curve was plotted and we calculated the area under the curve. We identified the cut-off points showing the highest sensitivity and specificity and studied diagnostic performance based on negative predictive value, positive predictive value, and accuracy. These were reported with their 95% confidence intervals. RESULTS: 183 measurements were performed. An AUC of 0.88(95% CI 0.83-0.94) was obtained. The pupillary dilation reflex of 11.5% had a sensitivity of 89.8%(95% CI 78.2-95.6) and a specificity of 78.4%(95% CI 70.6-84.5) with an accuracy of 81.4(75.2-86.4). The pupillary dilation reflex detected nociceptive pain response in 15.8% of the measurements that did not show pain according to the Behavioural Pain Scale. CONCLUSIONS: Pupillometry may be a valid alternative for identifying pain in critically ill patients.