Early Pupillometry Assessment in Traumatic Brain Injury Patients: A Retrospective Study

Early Pupil Abnormality Frequency Predicts Poor Outcomes and Enhances International Mission for Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) Model Prognostication in Traumatic Brain Injury

IMPORTANCE

In patients with traumatic brain injury (TBI), baseline pupillary assessment is routine; however, the occurrence rate and clinical significance of pupil abnormalities over the early course of hospitalization remain poorly characterized.

OBJECTIVES

To determine whether the occurrence and frequency of pupil abnormalities within the first 72 hours of ICU admission are associated with unfavorable discharge outcomes and to assess whether incorporating this frequency improves the performance of an established prognostic model.

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective observational study of adults admitted with a primary diagnosis of TBI to a single tertiary care ICU between 2018 and 2022. Inclusion criteria included at least three quantitative pupillometry assessments within the first 72 hours.

MAIN OUTCOMES AND MEASURES

Quantitative pupillometry was used to calculate the Neurological Pupil index (NPi) at each assessment. Abnormalities were defined as NPi less than 3 in either eye, NPi asymmetry greater than or equal to 0.7, or pupil size asymmetry greater than or equal to 1 mm. The primary outcome was unfavorable discharge disposition (death, hospice, or long-term care). Multivariable logistic regression was used to evaluate the association between pupil abnormality frequency and outcomes, and model performance was compared using goodness-of-fit tests with and without pupil frequency added to the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) model.

RESULTS

Among 131 patients (median age, 59 yr; 30% women), 35% had an unfavorable discharge disposition. Pupil abnormalities occurred in 60% of mild, 61% of moderate, and 88% of severe TBI patients. For each 1% increase in the frequency of pupil abnormalities over 72 hours, the odds of unfavorable discharge increased by 3% (odds ratio, 1.03; 95% CI, 1.01-1.05). Adding pupil abnormality frequency to the IMPACT model improved its goodness-of-fit (χ2 = 5.24; p = 0.02).

CONCLUSIONS AND RELEVANCE

Pupil abnormalities are common across TBI severities, particularly in severe cases. A higher frequency of abnormal pupil measurements within the first 72 hours is associated with unfavorable outcomes and significantly enhances the predictive performance of established TBI prognostic models. Serial quantitative pupillometry may offer clinically valuable, dynamic prognostic information in the acute care setting.

Prognostic role of quantitative pupillometry in traumatic brain injury: a scoping review

BACKGROUND

Traumatic brain injury (TBI) is a major cause of global mortality and disability, leading to primary and secondary brain injuries that can result in severe neurological, cognitive, and psychological impairments. Accurate and early prognosis of TBI outcomes is critical, particularly in assessing the risk of neurological decline, intracranial pressure (ICP) changes, and mortality.

OBJECTIVE

This systematic review aims to evaluate the prognostic value of quantitative pupillometry, particularly the Neurological Pupil Index (NPi), in predicting long-term outcomes in TBI patients.

METHODS

A systematic review was conducted following PRISMA guidelines, with the protocol registered on PROSPERO (CRD42023489079). Databases including PubMed, Scopus, and Embase were searched. Studies were included based on predefined inclusion criteria, focusing on the prognostic accuracy of automated pupillometry in TBI patients. Risk of bias was assessed using the Joanna Briggs Institute (JBI) tool, and evidence quality was evaluated using the Best-Evidence Synthesis approach.

RESULTS

Thirteen studies met the inclusion criteria, with sample sizes ranging from 36 to 2258 participants. The studies demonstrated a consistent association between lower NPi values and increased mortality, poorer functional outcomes, elevated ICP, and the need for emergency interventions. Despite variability in study design and sample sizes, strong evidence supported the use of NPi as a reliable prognostic tool in TBI management.

CONCLUSION

Automated infrared pupillometry, particularly through NPi measurement, offers important prognostic value in TBI patients. Incorporating NPi into routine clinical practice could improve the accuracy of prognosis and enhance patient management. Future research should focus on standardizing measurement protocols and validating these findings in larger, more diverse cohorts.

Machine Learning Approaches to Prognostication in Traumatic Brain Injury

PURPOSE OF REVIEW

This review investigates the use of machine learning (ML) in prognosticating outcomes for traumatic brain injury (TBI). It underscores the benefits of ML models in processing and integrating complex, multimodal data-including clinical, imaging, and physiological inputs-to identify intricate non-linear relationships that traditional methods might overlook.

RECENT FINDINGS

ML algorithms of clinical features, neuroimaging, and metrics from the autonomic nervous system enhance the early detection of clinical deterioration and improve outcome prediction. Challenges persist, including issues of data variability, model interpretability, and overfitting. However, advancements in model standardization and validation are key to enhancing their clinical applicability. ML-based, multimodal approaches offer transformative potential for personalized treatment planning and patient management. Future directions include integrating digital twins and real-time continuous data analysis, reinforcing the idea that comprehensive data amalgamation is essential for precise, adaptive prognostication and decision-making in neurocritical care, ultimately leading to better patient outcomes.

TILTomorrow today: dynamic factors predicting changes in intracranial pressure treatment intensity after traumatic brain injury

Practices for controlling intracranial pressure (ICP) in traumatic brain injury (TBI) patients admitted to the intensive care unit (ICU) vary considerably between centres. To help understand the rational basis for such variance in care, this study aims to identify the patient-level predictors of changes in ICP management. We extracted all heterogeneous data (2008 pre-ICU and ICU variables) collected from a prospective cohort (n = 844, 51 ICUs) of ICP-monitored TBI patients in the Collaborative European NeuroTrauma Effectiveness Research in TBI study. We developed the TILTomorrow modelling strategy, which leverages recurrent neural networks to map a token-embedded time series representation of all variables (including missing values) to an ordinal, dynamic prediction of the following day's five-category therapy intensity level (TIL(Basic)) score. With 20 repeats of fivefold cross-validation, we trained TILTomorrow on different variable sets and applied the TimeSHAP (temporal extension of SHapley Additive exPlanations) algorithm to estimate variable contributions towards predictions of next-day changes in TIL(Basic). Based on Somers' Dxy, the full range of variables explained 68% (95% CI 65-72%) of the ordinal variation in next-day changes in TIL(Basic) on day one and up to 51% (95% CI 45-56%) thereafter, when changes in TIL(Basic) became less frequent. Up to 81% (95% CI 78-85%) of this explanation could be derived from non-treatment variables (i.e., markers of pathophysiology and injury severity), but the prior trajectory of ICU management significantly improved prediction of future de-escalations in ICP-targeted treatment. Whilst there was no significant difference in the predictive discriminability (i.e., area under receiver operating characteristic curve) between next-day escalations (0.80 [95% CI 0.77-0.84]) and de-escalations (0.79 [95% CI 0.76-0.82]) in TIL(Basic) after day two, we found specific predictor effects to be more robust with de-escalations. The most important predictors of day-to-day changes in ICP management included preceding treatments, age, space-occupying lesions, ICP, metabolic derangements, and neurological function. Serial protein biomarkers were also important and may serve a useful role in the clinical armamentarium for assessing therapeutic needs. Approximately half of the ordinal variation in day-to-day changes in TIL(Basic) after day two remained unexplained, underscoring the significant contribution of unmeasured factors or clinicians' personal preferences in ICP treatment. At the same time, specific dynamic markers of pathophysiology associated strongly with changes in treatment intensity and, upon mechanistic investigation, may improve the timing and personalised targeting of future care.

Pupil Abnormality Frequency in the First 72 Hours Improves IMPACT score in Traumatic Brain Injury

Importance

In patients with traumatic brain injury (TBI), baseline pupillary assessment is common. However, the incidence and frequency of pupil abnormalities within the first several days remain poorly characterized.

Objectives

Our aim was to test the association between pupil abnormality frequency over the first 72 hours of admission and clinical outcomes.

Design

We conducted a retrospective observational study of patients with a primary diagnosis of TBI with at least three quantitative pupillometry measurements within 72 hours at a single-center ICU from 2018 to 2022.

Outcomes and Measures

Neurological Pupil index (NPi), a quantitative composite metric for pupil reactivity, was obtained at each clinical neurologic assessment over 72 hours. Pupil measurements were defined as abnormal if they had a NPi of <3 in either eye, NPi asymmetry ≥0.7, or pupil size asymmetry ≥1mm. We tested the association of increased frequency of pupil abnormalities over 72 hours and unfavorable discharge disposition (death, hospice, or long-term care) using multivariable logistic regression, adjusting for confounders. We then compared whether the IMPACT model was improved by the frequency of pupil abnormalities using goodness-of-fit.

Results

Of 131 patients, median age was 59 years, and 30% were women. Thirty-five percent had unfavorable discharge disposition. Pupil abnormalities occurred in 62%, 61%, and 88% of mild, moderate, and severe TBI patients, respectively. Odds ratio of unfavorable discharge for every 1% increase in pupil abnormality frequency was 1.03 (95% Cl, 1.01-1.05), equivalent to one additional abnormal pupil measurement within a 72-hour period. The adjusted IMPACT TBI model's goodness-of-fit improved with pupil abnormality frequency ( X 2 =5.67, p =0.02).

Conclusions and Relevance

Pupil abnormalities occur commonly in TBI and have the highest frequency in severe TBI. Increased pupil abnormality frequency is associated with unfavorable discharge disposition and improves performance of prognostic TBI models.

Key Points

The goal of this study was to test the association between pupil abnormality frequency over the first 72 hours of admission and unfavorable discharge disposition and whether it improved the IMPACT model. In this retrospective observational study of 131 TBI patients at a single-center, we found that an increased frequency of pupil abnormalities across 72-hours significantly correlated with unfavorable discharge in patients and improved the IMPACT model's goodness-of-fit. These findings highlight the potential of long-term pupillary metrics and their role as not only a prognostic indicator in patients but also a tool that improves the performance of prognostic TBI models.

Nursing insights on the effectiveness of automated pupillometry in two distinct pediatric intensive care units

PURPOSE

Automated pupillometry (AP) facilitates objective pupillary assessment. In this study, we aimed at assessing nursing perspective about the utility of AP in neurocritically ill children to understand acceptance and usage barriers to guide development of a standardized use protocol.

METHODS

We conducted a web-based, cross-sectional, anonymous, Google™ survey of nurses at two independent pediatric ICUs which have been using AP over last four years. The survey included questions related to user-friendliness, barriers, acceptance, frequency of use, and method of documenting AP findings.

RESULTS

A total of 31 nurses responded to the survey. A total of 25 nurses (80.6%) used the automated pupillometer and 19 (61.3%) nurses preferred to use the automated pupillometer on critically ill intubated patients. Respondents rated the pupillometer a median [IQR] frequency of use of 7/10 [4-9] and a mean user-friendliness of 8/10 [7-10]. Barriers to pupillometer use included pupillometer unavailability, technical issues, lack of perceived clinical significance, and infection control.

CONCLUSION

Nurses have widely adopted the use of automated pupillometer in the PICU especially for critically ill intubated patients and rate it favorably for user-friendliness. Barriers against its use include limited resources, infection concerns, technical issues, and a lack of perceived clinical significance and training. Implementation of standardized PICU protocol for AP usage in critically ill children, may enhance the acceptance, increase usage and aid in objective assessments.

PRACTICE IMPLICATIONS

These findings can be used to create a standardized protocol on implementing automated pupillometry in the PICU for critically ill children.

Prediction of neurocritical care intensity through automated infrared pupillometry and transcranial doppler in blunt traumatic brain injury: the NOPE study

PURPOSE

This pilot study aimed to determine the capacity of automated infrared pupillometry (AIP) alone and in combination with transcranial doppler (TCD) on admission to rule out need for intense neuroAQ2 critical care (INCC) in severe traumatic brain injury (TBI).

METHODS

In this observational pilot study clinicians performed AIP and TCD measurements on admission in blunt TBI patients with a Glasgow Coma Score (GCS) < 9 and/or motor score < 6. A Neurological Pupil index (NPi) < 3, Pulsatility Index (PI) > 1,4 or diastolic blood flow velocity (dV) of < 20 cm/s were used to rule out the need for INCC (exceeding the tier 0 Seattle Consensus Conference). The primary outcome was the negative likelihood ratio (nLR) of NPi < 3 alone or in combination with TCD to detect need for INCC.

RESULTS

A total of 69 TBI patients were included from May 2019 to September 2020. Of those, 52/69 (75%) median age was 45 [28-67], median prehospital GCS of 7 [5-8], median Injury Severity Scale of 13.0 [6.5-25.5], median Marshall Score of 4 [3-5], the median Glasgow Outcome Scale at discharge was 3 [1-5]. NPi < 3 was an independent predictor of INCC. NPi demonstrated a nLR of 0,6 (95%CI 0.4-0.9; AUROC, 0.65, 95% CI 0.51-0.79), a combination of NPi and TCD showed a nLR of 0.6 (95% CI 0.4-1.0; AUROC 0.67 95% CI 0.52-0.83) to predict INCC.

CONCLUSION

This pilot study suggests a possible useful contribution of NPi to determine the need for INCC in severe blunt TBI patients on admission.

Analysis of pupillary responses in pediatric patients with vitamin D deficiency

PURPOSE

To evaluate the effects of vitamin D deficiency on pupillary responses in the pediatric population.

METHODS

The study was conducted using data from the right eyes of 52 children with vitamin D deficiency and 52 healthy children. Measurements were taken under static and dynamic conditions with automatic pupillometry. Static measurements were performed at scotopic, mesopic, and photopic light intensities. The mean pupil dilation speed was calculated by observing the changes in pupil dilation over time according to dynamic measurements. Differences between patient and control groups were analyzed for the static and dynamic measurements and the mean pupil dilation speed.

RESULTS

While the two groups were similar in terms of scotopic, mesopic, the first dynamic measurements, and the pupil dilation speed data (p > 0.05), a significant difference was found in the photopic conditions (p = 0.001). The mean pupil diameter of the patient group was 4.46 ± 0.928 mm and 3.95 ± 0.556 mm in the control group under photopic conditions.

CONCLUSIONS

Pediatric patients with vitamin D deficiency have significantly larger pupil diameters in photopic conditions than healthy children. These results suggest that there is an autonomic dysfunction in vitamin D deficiency in the pediatric population, especially pointing to the parasympathetic system.

Automated Pupillometry Is Able to Discriminate Patients with Acute Stroke from Healthy Subjects: An Observational, Cross-Sectional Study

BACKGROUND

Automated pupillometry (AP) is a handheld, non-invasive tool that is able to assess pupillary light reflex dynamics and is useful for the detection of intracranial hypertension. Limited evidence is available on acute ischemic stroke (AIS) patients. The primary objective was to evaluate the ability of AP to discriminate AIS patients from healthy subjects (HS). Secondly, we aimed to compute a predictive score for AIS diagnosis based on clinical, demographic, and AP variables.

METHODS

We included 200 consecutive patients admitted to a comprehensive stroke center who underwent AP assessment through NPi-200 (NeurOptics®) within 72 h of stroke onset and 200 HS. The mean values of AP parameters and the absolute differences between the AP parameters of the two eyes were considered in the analyses. Predictors of stroke diagnosis were identified through univariate and multivariate logistic regressions; we then computed a nomogram based on each variable's β coefficient. Finally, we developed a web app capable of displaying the probability of stroke diagnosis based on the predictive algorithm.

RESULTS

A high percentage of pupil constriction (CH, p < 0.001), a low constriction velocity (CV, p = 0.002), and high differences between these two parameters (p = 0.036 and p = 0.004, respectively) were independent predictors of AIS. The highest contribution in the predictive score was provided by CH, the Neurological Pupil Index, CV, and CV absolute difference, disclosing the important role of AP in the discrimination of stroke patients.

CONCLUSIONS

The results of our study suggest that AP parameters, and in particular, those concerning pupillary constriction, may be useful for the early diagnosis of AIS.

Autonomic nervous system dysfunction in pediatric sport-related concussion: a systematic review

Objective

To identify, appraise and synthesize the evidence of autonomic nervous system (ANS) dysfunction following sport-related concussion in pediatric populations.

Methods

A literature search was conducted using MEDLINE (Ovid), SportDiscus (EBSCO), CINAHL (EBSCO), EMBASE (Ovid) and PsycINFO (Ovid). Studies were selected and appraised using the Joanna Briggs Institute (JBI) critical appraisal tools. Data was extracted from the included studies and qualitatively synthesized.

Results

Eleven studies were included in the synthesis. There was variability in the methods used to measure ANS function between studies, and sample populations and time to assessment following concussion varied considerably. There was also variability in the direction of change of ANS function between some studies.

Conclusion

This systematic review identifies that concussion is associated with dysregulation of ANS function in pediatric athletes. We identified some weaknesses in the extant literature which may be due to existing logistical and financial barriers to implementing valid ANS measurements in clinical and sports settings.

The Neurological Pupil index for outcome prognostication in people with acute brain injury (ORANGE): a prospective, observational, multicentre cohort study

BACKGROUND

Improving the prognostication of acute brain injury is a key element of critical care. Standard assessment includes pupillary light reactivity testing with a hand-held light source, but findings are interpreted subjectively; automated pupillometry might be more precise and reproducible. We aimed to assess the association of the Neurological Pupil index (NPi)-a quantitative measure of pupillary reactivity computed by automated pupillometry-with outcomes of patients with severe non-anoxic acute brain injury.

METHODS

ORANGE is a multicentre, prospective, observational cohort study at 13 hospitals in eight countries in Europe and North America. Patients admitted to the intensive care unit after traumatic brain injury, aneurysmal subarachnoid haemorrhage, or intracerebral haemorrhage were eligible for the study. Patients underwent automated infrared pupillometry assessment every 4 h during the first 7 days after admission to compute NPi, with values ranging from 0 to 5 (with abnormal NPi being <3). The co-primary outcomes of the study were neurological outcome (assessed with the extended Glasgow Outcome Scale [GOSE]) and mortality at 6 months. We used logistic regression to model the association between NPi and poor neurological outcome (GOSE ≤4) at 6 months and Cox regression to model the relation of NPi with 6-month mortality. This study is registered with ClinicalTrials.gov, NCT04490005.

FINDINGS

Between Nov 1, 2020, and May 3, 2022, 514 patients (224 with traumatic brain injury, 139 with aneurysmal subarachnoid haemorrhage, and 151 with intracerebral haemorrhage) were enrolled. The median age of patients was 61 years (IQR 46-71), and the median Glasgow Coma Scale score on admission was 8 (5-11). 40 071 NPi measurements were taken (median 40 per patient [20-50]). The 6-month outcome was assessed in 497 (97%) patients, of whom 160 (32%) patients died, and 241 (47%) patients had at least one recording of abnormal NPi, which was associated with poor neurological outcome (for each 10% increase in the frequency of abnormal NPi, adjusted odds ratio 1·42 [95% CI 1·27-1·64]; p<0·0001) and in-hospital mortality (adjusted hazard ratio 5·58 [95% CI 3·92-7·95]; p<0·0001).

INTERPRETATION

NPi has clinically and statistically significant prognostic value for neurological outcome and mortality after acute brain injury. Simple, automatic, repeat automated pupillometry assessment could improve the continuous monitoring of disease progression and the dynamics of outcome prediction at the bedside.

FUNDING

NeurOptics.

Neurological Pupillary Index (NPi) Measurement Using Pupillometry and Outcomes in Critically Ill Children

Aim/objective Neurological Pupil Index (NPi), measured by automated pupillometry (AP), allows the objective assessment of pupillary light reflex (PLR). NPi ranges from 0 (non-reactive) to 5 (normal). In this study, we aimed to compare neurologic and functional outcomes in children admitted for neurologic injury with normal (≥3) versus abnormal (<3) NPi measured during their pediatric intensive care unit (PICU) stay. Materials and methods We conducted a retrospective chart review of children between one month and 18 years admitted to our PICU with a diagnosis of neurologic injury between January 2019 and June 2022. We collected demographic, clinical, pupillometer, and outcome data, including mortality, Pediatric Cerebral Performance Category (PCPC), Pediatric Overall Performance Category (POPC), and Functional Status Score (FSS) at admission, at discharge, and at the three to six-month follow-up. We defined abnormal pupil response as any NPi <3 at any point during the PICU stay. Using the student's t-test and chi-square test, we compared the short-term and long-term outcomes of children with abnormal NPi (<3) versus those with normal NPi (≥3). Results There were 49 children who met the inclusion criteria and who had pupillometry data available for analysis. The mean (SD) Glasgow Coma Scale (GCS) in the study cohort was 5.6 (4.3), and 61% had low (<3) NPi during ICU stay. Mortality was significantly higher among patients with an abnormal NPi as compared to those with normal NPi. Children with abnormal NPi exhibited significant worsening of neurologic and functional status (ΔPCPC, ΔPOPC, and ΔFSS) from admission to discharge (mean (SD): 3.55(1.5), 3.45(1.43), 16.75(7.85), p<0.001) as compared to those with normal NPi (mean (SD): 1.45(0.93), 1.73(0.90), 3.55(2.07), p>0.05). The significant difference in neurologic and functional status persisted at the three to six-month follow-up between the two groups - children with abnormal NPi (mean (SD): 2.0(1.41), 2.08(1.38), 6.92(6.83), p<0.01) and children with normal NPi (mean (SD): 0.82(1.01), 0.94(1.03), 1.53(1.70), p>0.05). Conclusion In our retrospective cohort study, children admitted to the PICU for a neuro injury and with abnormal NPi (< 3) have higher mortality, and worse short-term and long-term neurologic and functional outcomes as compared to those with normal NPi (≥ 3) measured during the PICU course. AP provides an objective assessment of PLR and has potential applications for neuro-prognostication. More research needs to be done to elucidate the prognostic value of NPi in pediatrics.

Combat Sports as a Model for Measuring the Effects of Repeated Head Impacts on Autonomic Brain Function: A Brief Report of Pilot Data

Automated pupil light reflex (PLR) is a valid indicator of dysfunctional autonomic brain function following traumatic brain injury. PLR's use in identifying disturbed autonomic brain function following repeated head impacts without outwardly visible symptoms has not yet been examined. As a combat sport featuring repeated 'sub-concussive' head impacts, mixed martial arts (MMA) sparring may provide a model to understand such changes. The aim of this pilot study was to explore which, if any, PLR variables are affected by MMA sparring. A cohort of n = 7 MMA athletes (age = 24 ± 3 years; mass = 76.5 ± 9 kg; stature = 176.4 ± 8.5 cm) took part in their regular sparring sessions (eight rounds × 3 min: 1 min recovery). PLR of both eyes was measured immediately pre- and post-sparring using a Neuroptic NPi-200. Bayesian paired samples t-tests (BF₁₀ ≥ 3) revealed decreased maximum pupil size (BF₁₀ = 3), decreased minimum pupil size (BF₁₀ = 4) and reduced PLR latency (BF₁₀ = 3) post-sparring. Anisocoria was present prior to sparring and increased post-sparring, with both eyes having different minimum and maximum pupil sizes (BF₁₀ = 3-4) and constriction velocities post-sparring (BF₁₀ = 3). These pilot data suggest repeated head impacts may cause disturbances to autonomic brain function in the absence of outwardly visible symptoms. These results provide direction for cohort-controlled studies to formally investigate the potential changes observed.

Pupillary Light Response Deficits in 4-Week-Old Piglets and Adolescent Children after Low-Velocity Head Rotations and Sports-Related Concussions

Neurological disorders and traumatic brain injury (TBI) are among the leading causes of death and disability. The pupillary light reflex (PLR) is an emerging diagnostic tool for concussion in humans. We compared PLR obtained with a commercially available pupillometer in the 4 week old piglet model of the adolescent brain subject to rapid nonimpact head rotation (RNR), and in human adolescents with and without sports-related concussion (SRC). The 95% PLR reference ranges (RR, for maximum and minimum pupil diameter, latency, and average and peak constriction velocities) were established in healthy piglets (N = 13), and response reliability was validated in nine additional healthy piglets. PLR assessments were obtained in female piglets allocated to anesthetized sham (N = 10), single (sRNR, N = 13), and repeated (rRNR, N = 14) sagittal low-velocity RNR at pre-injury, as well as days 1, 4, and 7 post injury, and evaluated against RRs. In parallel, we established human PLR RRs in healthy adolescents (both sexes, N = 167) and compared healthy PLR to values obtained <28 days from a SRC (N = 177). In piglets, maximum and minimum diameter deficits were greater in rRNR than sRNR. Alterations peaked on day 1 post sRNR and rRNR, and remained altered at day 4 and 7. In SRC adolescents, the proportion of adolescents within the RR was significantly lower for maximum pupil diameter only (85.8%). We show that PLR deficits may persist in humans and piglets after low-velocity head rotations. Differences in timing of assessment after injury, developmental response to injury, and the number and magnitude of impacts may contribute to the differences observed between species. We conclude that PLR is a feasible, quantifiable involuntary physiological metric of neurological dysfunction in pigs, as well as humans. Healthy PLR porcine and human reference ranges established can be used for neurofunctional assessments after TBI or hypoxic exposures (e.g., stroke, apnea, or cardiac arrest).

Evaluating the Reliability of Neurological Pupillary Index as a Prognostic Measurement of Neurological Function in Critical Care Patients

Background

Neurological pupil index (NPi) is a novel method of assessing pupillary size and reactivity using pupillometry to reduce human subjectivity. This paper aims to evaluate the use of NPi as a potential prognostic tool in a broad population of neurocritical care patients by observing the correlation between NPi, modified Rankin Scale (mRS), and Glasgow Coma Scale (GCS).

Methods

Our data was collected from 194 patients in the neurosurgical intensive care unit (ICU) at Arrowhead Regional Medical Center (ARMC), as determined by the power calculation. We utilized the Kolmogorov-Smirnova and Shapiro-Wilk normality tests with Lilliefors significance correction. Pearson product-moment correlation was performed between average final NPi and final GCS. Multi-variate linear regression and analysis of variance (ANOVA) were used to evaluate the association and predictive capabilities of NPi on GCS and discharge mRS. Finally, we evaluated whether age, ethnicity, sex, length of stay (LOS), or discharge location were significantly associated with NPi. 

Results

We observed a significant correlation between final GCS and NPi (r=0.609, p<0.001). Our regression analysis revealed that NPi significantly predicted GCS and mRS scores; however, no associations were found between age, ethnicity, sex, LOS, or discharge location. Limitations of our study include a single institutional study with a lack of disease subtyping and the inability to quantify the predictive ability of NPi.

Conclusion

The analysis revealed a strong correlation between final GCS and average final NPi. NPi was also able to significantly predict GCS and mRS scores. The correlation between NPi and established methods to determine neurological function, such as mRS and GCS, suggests that NPi can be a good prognostication tool for neurological diseases.