Comparison of 2 Automated Pupillometry Devices in Critically III Patients

Validating quantitative pupillometry thresholds for neuroprognostication after out-of-hospital cardiac arrest. A predefined substudy of the Blood Pressure and Oxygenations Targets After Cardiac Arrest (BOX)-trial

PURPOSE

Out-of-hospital cardiac arrest (OHCA) survivors face significant risks of complications and death from hypoxic-ischemic brain injury leading to withdrawal of life-sustaining treatment (WLST). Accurate multimodal neuroprognostication, including automated pupillometry, is essential to avoid inappropriate WLST. However, inconsistent study results hinder standardized threshold recommendations. We aimed to validate proposed pupillometry thresholds with no false predictions of unfavorable outcomes in comatose OHCA survivors.

METHODS

In the multi-center BOX-trial, quantitative measurements of automated pupillometry (quantitatively assessed pupillary light reflex [qPLR] and Neurological Pupil index [NPi]) were obtained at admission (0 h) and after 24, 48, and 72 h in comatose patients resuscitated from OHCA. We aimed to validate qPLR < 4% and NPi ≤ 2, predicting unfavorable neurological conditions defined as Cerebral Performance Category 3-5 at follow-up. Combined with 48-h neuron-specific enolase (NSE) > 60 μg/L, pupillometry was evaluated for multimodal neuroprognostication in comatose patients with Glasgow Motor Score (M) ≤ 3 at ≥ 72 h.

RESULTS

From March 2017 to December 2021, we consecutively enrolled 710 OHCA survivors (mean age: 63 ± 14 years; 82% males), and 266 (37%) patients had unfavorable neurological outcomes. An NPi ≤ 2 predicted outcome with 0% false-positive rate (FPR) at all time points (0-72 h), and qPLR < 4% at 24-72 h. In patients with M ≤ 3 at ≥ 72 h, pupillometry thresholds significantly increased the sensitivity of NSE, from 42% (35-51%) to 55% (47-63%) for qPLR and 50% (42-58%) for NPi, maintaining 0% (0-0%) FPR.

CONCLUSION

Quantitative pupillometry thresholds predict unfavorable neurological outcomes in comatose OHCA survivors and increase the sensitivity of NSE in a multimodal approach at ≥ 72 h.

Exploring the feasibility of pupillometry training and perceptions of potential use for intracranial pressure monitoring in Uganda: A mixed methods study

INTRODUCTION

Traumatic brain injury (TBI) accounts for the majority of Uganda's neurosurgical disease burden; however, invasive intracranial pressure (ICP) monitoring is infrequently used. Noninvasive monitoring could change the care of patients in such a setting through quick detection of elevated ICP.

PURPOSE

Given the novelty of pupillometry in Uganda, this mixed methods study assessed the feasibility of pupillometry for noninvasive ICP monitoring for patients with TBI.

METHODS

Twenty-two healthcare workers in Kampala, Uganda received education on pupillometry, practiced using the device on healthy volunteers, and completed interviews discussing pupillometry and its implementation. Interviews were assessed with qualitative analysis, while quantitative analysis evaluated learning time, measurement time, and accuracy of measurements by participants compared to a trainer's measurements.

RESULTS

Most participants (79%) reported a positive perception of pupillometry. Participants described the value of pupillometry in the care of patients during examination, monitoring, and intervention delivery. Commonly discussed concerns included pupillometry's cost, understanding, and maintenance needs. Perceived implementation challenges included device availability and contraindications for use. Participants suggested offering continued education and engaging hospital leadership as implementation strategies. During training, the average learning time was 13.5 minutes (IQR 3.5), and the measurement time was 50.6 seconds (IQR 11.8). Paired t-tests to evaluate accuracy showed no statistically significant difference in comparison measurements.

CONCLUSION

Pupillometry was considered acceptable for noninvasive ICP monitoring of patients with TBI, and pupillometer use was shown to be feasible during training. However, key concerns would need to be addressed during implementation to aid device utilization.

Noninvasive Neuromonitoring Modalities in Children Part I: Pupillometry, Near-Infrared Spectroscopy, and Transcranial Doppler Ultrasonography

BACKGROUND

Noninvasive neuromonitoring in critically ill children includes multiple modalities that all intend to improve our understanding of acute and ongoing brain injury.

METHODS

In this article, we review basic methods and devices, applications in clinical care and research, and explore potential future directions for three noninvasive neuromonitoring modalities in the pediatric intensive care unit: automated pupillometry, near-infrared spectroscopy, and transcranial Doppler ultrasonography.

RESULTS

All three technologies are noninvasive, portable, and easily repeatable to allow for serial measurements and trending of data over time. However, a paucity of high-quality data supporting the clinical utility of any of these technologies in critically ill children is currently a major limitation to their widespread application in the pediatric intensive care unit.

CONCLUSIONS

Future prospective multicenter work addressing major knowledge gaps is necessary to advance the field of pediatric noninvasive neuromonitoring.

The Role of Automated Infrared Pupillometry in Traumatic Brain Injury: A Narrative Review

Pupillometry, an integral component of neurological examination, serves to evaluate both pupil size and reactivity. The conventional manual assessment exhibits inherent limitations, thereby necessitating the development of portable automated infrared pupillometers (PAIPs). Leveraging infrared technology, these devices provide an objective assessment, proving valuable in the context of brain injury for the detection of neuro-worsening and the facilitation of patient monitoring. In cases of mild brain trauma particularly, traditional methods face constraints. Conversely, in severe brain trauma scenarios, PAIPs contribute to neuro-prognostication and non-invasive neuromonitoring. Parameters derived from PAIPs exhibit correlations with changes in intracranial pressure. It is important to acknowledge, however, that PAIPs cannot replace invasive intracranial pressure monitoring while their widespread adoption awaits robust support from clinical studies. Ongoing research endeavors delve into the role of PAIPs in managing critical neuro-worsening in brain trauma patients, underscoring the non-invasive monitoring advantages while emphasizing the imperative for further clinical validation. Future advancements in this domain encompass sophisticated pupillary assessment tools and the integration of smartphone applications, emblematic of a continually evolving landscape.

Superior reproducibility and repeatability in automated quantitative pupillometry compared to standard manual assessment, and quantitative pupillary response parameters present high reliability in critically ill cardiac patients

Background

Quantitative pupillometry is part of multimodal neuroprognostication of comatose patients after out-of-hospital cardiac arrest (OHCA). However, the reproducibility, repeatability, and reliability of quantitative pupillometry in this setting have not been investigated.

Methods

In a prospective blinded validation study, we compared manual and quantitative measurements of pupil size. Observer and device variability for all available parameters are expressed as mean difference (bias), limits of agreement (LoA), and reliability expressed as intraclass correlation coefficients (ICC) with a 95% confidence interval.

Results

Fifty-six unique quadrupled sets of measurement derived from 14 sedated and comatose patients (mean age 70±12 years) were included.

For manually measured pupil size, inter-observer bias was -0.14±0.44 mm, LoA of -1.00 to 0.71 mm, and ICC at 0.92 (0.86–0.95). For quantitative pupillometry, we found bias at 0.03±0.17 mm, LoA of -0.31 to 0.36 mm and ICCs at 0.99. Quantitative pupillometry also yielded lower bias and LoA and higher ICC for intra-observer and inter-device measurements.

Correlation between manual and automated pupillometry was better in larger pupils, and quantitative pupillometry had less variability and higher ICC, when assessing small pupils. Further, observers failed to detect 26% of the quantitatively estimated abnormal reactivity with manual assessment.

We found ICC >0.91 for all quantitative pupillary response parameters (except for latency with ICC 0.81–0.91).

Conclusion

Automated quantitative pupillometry has excellent reliability and twice the reproducibility and repeatability than manual pupillometry. This study further presents novel estimates of variability for all quantitative pupillary response parameters with excellent reliability.

Identification of abnormal pupil dilation velocity as a biomarker of cerebral injury in neurocritically ill patients

OBJECTIVE

To calculate mean dilation velocities for Glasgow coma scale-derived injury severity classifications stratified by multiple confounding variables.

METHODS

In this study, we examined 68,813 pupil readings from 3,595 patients to determine normal dilation velocity with brain injury categorized based upon a Glasgow coma scale as mild (13 - 15), moderate (9 - 12), or severe (3 - 8). The variables age, sex, race, pupil size, intensive care unit length of stay, intracranial pressure, use of narcotics, Glasgow coma scale, and diagnosis were considered as confounding and controlled for in statistical analysis. Machine learning classification algorithm-based logistic regression was employed to identify dilation velocity cutoffs for Glasgow coma scale categories.

RESULTS

The odds ratios and confidence intervals of these factors were shown to be statistically significant in their influence on dilation velocity. Classification based on the area under the curve showed that for the mild Glasgow coma scale, the dilation velocity threshold value was 1.2mm/s, with false probability rates of 0.1602 and 0.1902 and areas under the curve of 0.8380 and 0.8080 in the left and right eyes, respectively. For the moderate Glasgow coma scale, the dilation velocity was 1.1mm/s, with false probability rates of 0.1880 and 0.1940 and areas under the curve of 0.8120 and 0.8060 in the left and right eyes, respectively. Furthermore, for the severe Glasgow coma scale, the dilation velocity was 0.9mm/s, with false probability rates of 0.1980 and 0.2060 and areas under the curve of 0.8020 and 0.7940 in the left and right eyes, respectively. These values were different from the previous method of subjective description and from previously estimated normal dilation velocities.

CONCLUSION

Slower dilation velocities were observed in patients with lower Glasgow coma scores, indicating that decreasing velocities may indicate a higher degree of neuronal injury.

Automated Quantitative Pupillometry in the Critically Ill: A Systematic Review of the Literature

OBJECTIVE

A systematic literature search has been performed to identify potential confounders for outcome prediction using pupillary light reflex in adult critically ill patients, as measured by handheld automated pupillometry devices.

METHODS

Three digital databases (PubMed, EmBase, Cochrane) were systematically searched. Articles published between 1990 and 2019 in adult patients using monocular automated handheld devices were considered. Studies were classified according to the Oxford Centre for Evidence-Based Medicine classification (level 1 represents the highest and level 5 the lowest level of evidence). Case reports, original research, and systematic reviews were included and cross-referenced.

RESULTS

With the use of 202 search terms, 58 eligible articles reporting the use of handheld pupillometry in the critically ill could be identified, considering 3,246 patients. The highest level of evidence came from 10 randomized trials and 19 prospective observational studies. The level of evidence was mostly 2 to 3 and highest with studies regarding the potential confounding effects of pain, the use of opioids, and increased intracranial pressure. Additional potential confounders found are selective serotonin reuptake inhibitors, α2-adregenic receptor agonists, and NMDA antagonists.

CONCLUSIONS

The pupillary light reflex is susceptible to factors resulting from underlying comorbid conditions and effects of treatment regimens. Scenarios frequently encountered in critical care such as pain, use of opioids, and proof of increased intracranial pressure have potential confounding effects on outcome and pupillary reflexes. When treatment is guided by pupillary metrics, such confounders put patients at risk of overtreatment or undertreatment. Future research should validate and identify additional confounders, because our review suggests that even more unexplored confounders may exist.

Neuroanesthesiology Update

This review summarizes the literature published in 2020 that is relevant to the perioperative care of neurosurgical patients and patients with neurological diseases as well as critically ill patients with neurological diseases. Broad topics include general perioperative neuroscientific considerations, stroke, traumatic brain injury, monitoring, anesthetic neurotoxicity, and perioperative disorders of cognitive function.

Neurological Complications and Noninvasive Multimodal Neuromonitoring in Critically Ill Mechanically Ventilated COVID-19 Patients

Purpose: The incidence and the clinical presentation of neurological manifestations of coronavirus disease-2019 (COVID-19) remain unclear. No data regarding the use of neuromonitoring tools in this group of patients are available. Methods: This is a retrospective study of prospectively collected data. The primary aim was to assess the incidence and the type of neurological complications in critically ill COVID-19 patients and their effect on survival as well as on hospital and intensive care unit (ICU) length of stay. The secondary aim was to describe cerebral hemodynamic changes detected by noninvasive neuromonitoring modalities such as transcranial Doppler, optic nerve sheath diameter (ONSD), and automated pupillometry. Results: Ninety-four patients with COVID-19 admitted to an ICU from February 28 to June 30, 2020, were included in this study. Fifty-three patients underwent noninvasive neuromonitoring. Neurological complications were detected in 50% of patients, with delirium as the most common manifestation. Patients with neurological complications, compared to those without, had longer hospital (36.8 ± 25.1 vs. 19.4 ± 16.9 days, p < 0.001) and ICU (31.5 ± 22.6 vs. 11.5±10.1 days, p < 0.001) stay. The duration of mechanical ventilation was independently associated with the risk of developing neurological complications (odds ratio 1.100, 95% CI 1.046-1.175, p = 0.001). Patients with increased intracranial pressure measured by ONSD (19% of the overall population) had longer ICU stay. Conclusions: Neurological complications are common in critically ill patients with COVID-19 receiving invasive mechanical ventilation and are associated with prolonged ICU length of stay. Multimodal noninvasive neuromonitoring systems are useful tools for the early detection of variations in cerebrovascular parameters in COVID-19.