Determinants of Routine Quantitative Pupillometry in Neurocritical Care

Determinants of Routine Quantitative Pupillometry in Neurocritical Care | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Determinants of Routine Quantitative Pupillometry in Neurocritical Care Shripal Gunna, Dorina Harper, Thomas Lawson, Sarah Livesay, Chelsea McVay, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6226822/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Dec, 2025 Read the published version in Global Implementation Research and Applications → Version 1 posted 9 You are reading this latest preprint version Abstract Background/Introduction : Manual pupillary light reflex (PLR) assessment is inconsistent, outdated, and unreliable. Even with evidence of the superiority of QP (Quantitative Pupillometry) assessments, use of manual assessment remains commonplace. Aim : This study aims to quantify the use of QP in the NCCU (Neurocritical Care Unit) and examine clinical determinants of routine QP use. It also identifies clinician beliefs and perceptions of acceptability, appropriateness, feasibility, and fidelity of QP use. Methods : This multi-site, period prevalence observational implementation study took place at 2 academic NCCUs. Both sites recorded frequency of QP use and acuity measures of patients receiving QP use over a 2-week period. A REDCap® survey was distributed to NCCU clinicians assessing their perceptions on QP. Results : Site A had higher prevalence of QP utilization than Site B. Multinomial logistic regression modeling indicated patient diagnosis, age, mechanical ventilation, and continuous EEG were factors associated with QP use at Site B, however no association was evident at Site A. Survey results were in support of QP at both sites. Discussion : QP is a useful tool for pupillary assessment, with years of research and the support of clinicians to its utilization. Utilization varied at Sites A and B, even though both were in support of QP overall. Conclusion : This study established baseline estimates of routine use, as well as factors influencing the frequency of QP assessments. Additional research is needed to definitively determine optimal assessment frequency, role that clinical factors may play, as well as impact of QP on patient outcomes. Background Neurological disorders and injuries are some of the leading causes of disabilities and death globally (Feigin et al., 2020 ; Kang et al., 2022 ; Lundquist et al., 2024 ). The pupillary light reflex (PLR) response is a rapid assessment used to make emergent life and death decisions about the need for high-risk invasive therapies, costly diagnostic testing, or withdrawal of care (Romagnosi et al., 2020 ; Tran et al., 2022 ). Despite its pivotal role in the care and management of patients in the Neurocritical Care Unit (NCCU), current practice for manual PLR assessment is inconsistent, outdated, highly subjective and repeatedly proven to be unreliable among nurses, physicians, advanced practice providers, and emergency responders (Ali et al., 2024 ; Bashir et al., 2025 ; Godau et al., 2021 ; Trent et al., 2023 ). Even with substantial and consistent evidence confirming the superiority of QP for serial assessments in the critical care setting, implementation of this best practice remains fragmented and inconsistent among clinical teams (Jiang et al., 2024 ; Kamal, Kim, et al., 2024 ). The PLR exam is a standard component of serial neurological assessments in the NCCU setting, and decades of research indicates its usefulness as a prognostic tool (Barra et al., 2023; Figueroa et al., 2024 ; Ghauri et al., 2022 ). The pupilloconstrictor response is a parasympathetic reflex caused by stimulation of the 3rd cranial nerve (oculomotor). The 3rd cranial nerve is adjacent to the medial temporal lobe and the midbrain third nucleus; therefore, damage to these areas of the brain controlling consciousness can disrupt cranial nerve pathways, resulting in a decreased PLR response (Figueroa et al., 2024 ; Kamal, Nairon, et al., 2024 ). Though the importance of PLR assessments may seem obvious, there are significant limitations to manual pupillary exams that rely upon subjective assessment (Nyholm et al., 2022 ). Substantial evidence demonstrates superiority of QP assessments, specifically with its high reliability and accuracy of assessments (Godau et al., 2021 ; Kamal, Nairon, et al., 2024 ; Oddo et al., 2023 ). Moreover, even if human assessments were reliable, the assessment of PLR reaction speed (brisk, sluggish, and fixed) is inadequate to determine whether the pupil is functioning in a normal manner (Doyle et al., 2024 ; Nyancho et al., 2021 ; Privitera et al., 2022 ). A brisk pupil can react abnormally, and a sluggish pupil can react normally. Though there are well studied benefits to QP, pupillometry does have barriers in its implementation which ultimately can limit its adoption at different institutions (Bower et al., 2021 ; Vrettou et al., 2024 ). Furthermore, anecdotal observations indicate fragmented and inconsistent use of this practice between critical care units, ultimately leading to a gap in the literature of estimates of routine use of QP(Sridhar et al., 2023 ). Aim of Study This study aims to quantify the use of QP in NCCU and examine clinical determinants of routine QP use. It also seeks to identify clinician beliefs and perceptions of acceptability, appropriateness, feasibility, and fidelity of QP use for patients. Methods Research Design This study utilized a multi-site, period prevalence observational implementation science design. The study took place in the NCCU of two separate academic medical centers: Site A, which is in the Southwestern United States, and Site B, which is in the Midwestern United States. Site A is an 849-bed medical center, with a 24-bed NCCU. This site is designated as a comprehensive stroke center by the American Stroke Association, a Magnet designated facility by the American Nurses Credentialing Center, and the unit has received Beacon recognition by the American Association of Critical Care Nurses. The site has a designated policy on QP use, as well as a handheld pupillometer available in each patient room. Site B is a 1,456-bed academic medical center, with a 24 bed NCCU. Site B is also an accredited comprehensive stroke center by The Joint Commission, has ANCC Magnet designation, and is a Beacon Award unit. The site does not have a specific policy on QP use, but it may be ordered by providers with specific timing and frequency of assessments or used at the nurses’ discretion. Handheld pupillometers are available at a ratio of approximately 1 pupillometer per 1.75 rooms. Each site had the study reviewed and approved by their respective Institutional Review Boards (IRBs) prior to data collection. To address Aim 1 and quantify routine use of QP at each site, both sites recorded frequency of QP use daily during the same 2-week period to establish period prevalence. To examine clinical determinants of routine use, daily clinical data on patients meeting inclusion criteria were also recorded. Sample and Setting The Inclusion criteria were: Adult patients (> 18 years of age) admitted to Neurocritical care service. The exclusion criteria were patients not on Neurocritical care service, those on comfort measure status in the 24 hours prior to data collection, and any patient enrolled in a separate device or drug research study that may influence routine QP assessments. Clinical data that were recorded daily included: daily patient acuity measures (mechanical ventilation, vasoactive medications, invasive cerebral monitoring, EEG monitoring, administration of mannitol/hypertonic saline, and need for neurosurgical intervention), documentation of pupil examination, and patient demographic data (diagnosis, age, gender, race and ethnicity). Data was recorded in REDCap, then exported and stored on a password protected network drive for cleaning and analysis. Aim 2 was guided by the Consolidated Framework for Implementation Research (CFIR) to evaluate determinants of routine use of QP among healthcare clinicians. The CFIR is a determinant framework composed of five domains that influence implementation of evidence-based practices into routine care settings. Domains include the characteristics of innovation, the outer setting, inner setting, characteristics of individuals, and the process of implementation. Within each domain, specific constructs serve as determinants or factors influencing routine implementation. A quantitative survey that included these CFIR domains was created to evaluate clinician perceptions of factors that may influence their routine use of QP(Chitiyo et al., 2023 ). The survey also included quantitative questions from the Acceptability of Intervention Measure (AIM), the Intervention Appropriateness Measure (IAM), and Feasibility of Implementation Measure (FIM) (Weiner et al., 2017 ). The quantitative survey was created in REDCap and distributed via an emailed survey link to clinicians who routinely care for patients in each of the respective NCCUs of the study. Inclusion criteria for clinicians were any employed healthcare provider on the Neurocritical care service at each site, including attending physicians, neurology/neurosurgery trainees, advanced practice providers, registered nurses, and pharmacists who are employed to work primarily in the NCCU. The survey was sent after the daily prevalence period and was open for clinicians to complete for 3 weeks. Data were analyzed using SPSS at each study site. Period prevalence was calculated as the proportion of patients at each site receiving QP relative to the proportion of patients eligible to receive QP daily during a 14-day period. Descriptive statistics, including means, frequencies, and standard deviations were calculated with clinical data to describe characteristics of the study sample. Bivariate Chi-square statistics were calculated to determine the proportion of patients receiving QP based on demographic and clinical characteristics. Logistic regression models were used to identify clinical determinants of routine use at each site. To evaluate clinician responses to survey items on perceptions of use, descriptive statistics were calculated to report means and frequencies of aggregate responses by site. Ethical Considerations This study was approved by the institutional review board of the University of Texas Southwestern Medical Center before data collection began (IRB Number: STU-2024-0115). The study was reviewed under the exempt category as PHI was not collected from subjects in this study. When filling out the survey, subjects were provided with an information sheet detailing the study’s purpose and procedures, as well as their right to refusal to participate in the study. Results Period Prevalence of QP Use During the 2-week prevalence period, Site A recorded 270 observations among 75 patients. The daily prevalence of QP use at Site A ranged from 88%-100% among eligible patients. Site B recorded 236 observations from 71 patients, with a daily prevalence ranging from 9%-50%. Clinical Determinants of QP Use As shown in Table 1 , univariate analysis at Site A for each of the clinical acuity measures observed and QP use were: mechanical ventilation (X 2 = 0.525; p = 0.469), vasoactive medications (X 2 = 2.603; p = 0.107), continuous EEG monitoring (X 2 = 0.038; p = 0.845), hypertonic saline administration (X 2 = 0.358; p = 0.550), and diagnosis (X 2 = 6.342; p = 0.386). After abstracting diagnoses of patients in the NCCU, a multivariate analysis provided the following chi square value and p value (X 2 = 6.3424; p = 0.3860). For Site B, there was a strong relationship between QP use and ventilation (ꭓ=42.54; p < 0.001), vasoactive medications (ꭓ=8.36; p < 0.001), continuous EEG (X 2 = 33.84; p < 0.001), hypertonic saline administration (X 2 = 27.60; p < 0.001). Additionally, patients with ICH and TBI had higher proportion of QP use (X 2= 55.297, p < 0.001). Multinomial logistic regression modeling indicated patient diagnosis, age, mechanical ventilation, and continuous EEG were factors most predictive of QP assessments (X 2= 167.14, p < 0.001) Table 1 Site A and B Clinical Determinants of QP Use (Chi Square and P-Value) Chi Square (X 2 , ꭓ) P-Value SITE (A or B) Site A Site B Site A Site B Mechanical Ventilation X 2 = 0.525 ꭓ = 42.54 P = 0.469 p < 0.001 Vasoactive Medication X 2 = 2.603 ꭓ = 8.36 P = 0.107 p < 0.001 Continuous EEG Monitoring X 2 = 0.038 ꭓ = 33.84 P = 0.845 p < 0.001 Hypertonic Saline Administration X 2 = 0.358 ꭓ = 27.60 P = 0.550 p < 0.001 Diagnosis X 2 = 6.342 ꭓ = 55.30 P = 0.386 p < 0.001 Clinician Perspectives on Routine QP Use At Site A, n = 68 clinicians completed the survey on perspectives and determinants of routine QP use, while n = 11 completed the survey for Site B. Survey respondents at both sites were similar with regards to years of QP use and years of experience (Table 2 ). Most respondents at both sites were clinical nurses (n = 42, 61.8%; n = 5; 45% for Site A, B, respectively). Across both sites, there was also adequate representation from other members of the healthcare team that included attending physicians, residents/fellows, advance practice providers, and clinical pharmacists. When looking at reported determinants of routine QP use according to CFIR domains, respondents at both sites equally welcomed QP use when caring for their patients (mean 4.7), found the practice appealing (mean 4.5), and useful for routine clinical care (mean 4.6) (Table 3 ). Respondents also reported strong advantages of QP use over manual pupil assessments (mean 4.7, 4.6 for Site A, B, respectively), a solid understanding of QP values and what they mean when caring for patients (mean 4.6 at both sites), and the perspective that QP use is well supported by published research studies (4.2, 4.0 for Site A, B, respectively). While respondents at both sites reported QP is suitable for use in all patients in the NCCU (mean 4.4, 4.3,) respondents at Site A felt QP use is also feasible for all ICU patients (mean 4.2), which differed from Site B (mean 3.4). Site A respondents reported lower scores overall for feasibility of routine QP use (mean 3.2–3.6) when compared to Site B (mean 4.2). Site A also reported frequent QP assessment being more burdensome for staff (mean 3.2) when compared to Site B (mean 2.6). Scores for overall difficulty of starting QP use were similar between sites, while ongoing maintenance of QP was reported as being more difficult for Site B (Table 3 ). Table 2 Demographics/Characteristics of Clinicians Role Site A N (%) Site B N (%) Nurse Leader (CNO, Director, Manager) 4 (5.9%) 0 (0%) Advanced Practice Provider (PA, CNS, NP, APRN) 5 (7.4%) 2 (18.2%) Nurse Educator 1 (1.5%) 0 (0%) Clinical/Bedside Nurse 42 (61.8%) 5 (45.5%) Academic Faculty 2 (2.9%) 0 (0%) Attending Physician 8 (11.8%) 2 (18.2%) Fellow Physician 5 (7.4%) 1 (9.21%) Other 1 (1.5%) 1 (9.1%) Education Level N (%) Associate's degree 1 (1.5%) 1 (9.1%) BSN 44 (64.7%) 2 (18.2%) MSN or Other Masters Level 6 (8.8%) 3 (27.3%) DNP, PharmD, MD, or Other Practice Doctorate 17 (25%) 5 (45.5%) Mean Length of QP Use in Years 4.8 (3.12) 5.70 (2.75) Mean Age (Years) 36.4 (11.88) 35.70 (7.15) Table 3 Site A Survey Results (Mean answer (Standard Deviation)) Type The questions below are on a Likert Scale: 1 (Strongly Disagree), 2(Disagree), 3 (Neutral), 4 (Agree), 5(Strongly Agree). Site A Results Site B Results CFIR QP assessment is well supported by published studies. 4.2 (0.76) 4 CFIR QP offers a strong advantage over manual pupil assessments. 4.7 (0.51) 4.6 CFIR I understand QP values and what they mean when caring for my patient. 4.6 (0.57) 4.6 CFIR QP is useful in routine clinical practice. 4.6 (0.66) 4.6 CFIR QP is used in other Neurocritical Care Programs in the region. 3.8 (0.92) 4.1 CFIR QP should be limited to the most acute patients in the NCCU. 2.3 (1.24) 2.7 CFIR QP should always be used instead of manual pupil. 3.5 (1.27) 3.0 CFIR I always perform QP for pupillary assessment in eligible patient. 4.2 (0.99) 3.8 CFIR My unit has a policy on QP use. 3.9 (0.92) 3.2 CFIR When performing pupillary assessments, I follow the frequency and indications listed in the policy. 3.9 (0.90) 3.7 AA QP is appealing to me. 4.5 (0.61) 4.5 AA I welcome QP use in my patients. 4.7 (0.56) 4.7 AA QP is suitable for use in all patients in the NCCU. 4.4 (0.84) 4.3 AA QP is suitable for use in all patients in all ICUs. 4.2 (0.99) 3.4 F Frequent (q 1–2 hour) QP assessment in the NCCU seems possible. 3.6 (1.10) 4.2 F Frequent (q 1–2 hour) QP assessment seems easy to me. 3.5 (1.10) 4.2 F Frequent (q 1–2 hour) QP assessment is a burden for nursing staff. 3.2 (1.12) 2.6 The questions below are on a scale from 1 (Not Difficult at All) to 10 (Extremely Difficult). Mean (SD) Mean 18 How difficult was it to start QP use in your NCCU? 2.9 (2.05) 2.5 19 How difficult was it to maintain QP use in your NCCU? 3.0 (2.01) 2.6 20 How difficult was it to hardwire regular QP use in your NCCU? 3.4 (2.25) 3.3 21 Overall, how difficult was starting QP use in your NCCU? 3.0 (1.93) 3.2 22 Overall, how difficult was maintaining QP use in your NCCU? 2.7 (1.71) 3.2 23 Overall, how difficult was completing QP use in your NCCU (i.e. recording meaningful outcomes, hardwiring change in practice)? 2.9 (1.89) 3.2 CFIR: CFIR Domains AA: Acceptability & Appropriateness F: Feasibility E: Ease of Use Limitations At Site A, we found limitations in piloting this study in the fact that most patients in the NCCU receive pupillometry. Though staff surveys indicate Site A has a strong inclination to pupillometry, other facilities without existing protocols may experience different daily prevalence than in this NCCU. This idea of further assessing ICUs without protocols in place can make for areas of further study. Another limitation in this study is that staff were not questioned regarding the quality or quantity of education they received in pupillometry specifically. Differing training amongst NCCU’s can result in varying utilization of pupillometry, which can contradict the overall universal acceptance of QP. Discussion This study is the first, to our knowledge, to document variation in routine QP use within NCCUs. Although both sites in this study were large academic medical centers, there were large differences in prevalence of routine QP assessments. Pupil assessments remain a standard component of serial neurological examinations for patients suffering from neurological conditions. The emergence of QP technology has better standardized these pupillary assessments, as multiple studies have confirmed the accuracy of these assessments over manual evaluations (Godau et al., 2021 ; Jiang et al., 2024 ; Nyholm et al., 2022 ). Despite this evidence, our study findings demonstrate it is not routinely used by healthcare clinicians among all patients in NCCUs. The primary aim of this study was also to evaluate if there were clinical factors associated with routine QP use among NCCU healthcare clinicians. Because QP was widely used at site A, clinical factors of the patient, including measures of acuity and patient diagnosis, did not significantly influence use of QP for pupillary assessments. This can be explained by the fact that the organization’s QP assessment protocol states the exam is to be performed on all NCCU patients, regardless of these clinical factors. In contrast, site B had larger variability in routine QP use. As such, patients with higher acuity had a higher proportion of QP use, suggesting QP assessments were done more often on these patients. Similarly, patients with certain diagnosis types, namely ICH and TBI, had QP assessments performed more often. A common practice on this unit is generally to perform QP assessments on patients with higher neurological acuity, which would explain these study findings. As established in previous studies, accurate assessment of the PLR is crucial in patients across multiple diagnosis types in NCCUs (Gupta et al., 2023 ; Hsu & Kuo, 2023 ). However, there are no definitive recommendations or accreditation requirements that QP be used routinely for specific diagnoses or conditions, which could also explain the variation in routine use among the two sites in this study. In addition to evaluating the role that clinical factors had on routine QP use, this study also evaluated how clinician perceptions influenced QP use. Overwhelmingly, clinicians at both sites were familiar with the evidence to support QP use for pupillary assessments, and felt the practice was acceptable and appropriate for patients with neurological injury. Clinicians also viewed adoption and utilization of QP favorably at both study sites. Clinician scores differed between sites with respect to burden and feasibility of routine QP use, with Site A reporting QP use as slightly more burdensome and not as consistently feasible when compared with Site B. Site A also had much higher routine use prevalence, suggesting QP assessments were done regularly which could explain the slightly additional reported burden, when compared to Site B that used QP less frequently on all patients. This finding highlights an important area for future consideration: weighing the benefit of high frequency QP assessments with clinician workload and feasibility. Currently there are no studies that definitively demonstrate the benefit of higher QP assessment frequency with improved patient outcomes, and optimal frequency of QP assessments remain uncertain. The use of an internal hospital or unit policy on frequency of QP assessments may influence prevalence of routine use. In our study, site A had an existing policy that included recommended frequency of QP assessments, while site B did not have a specific policy on QP use. It is likely that this influenced the higher prevalence rates observed in Site A when compared to site B, as well as the role that clinical factors played in determining the need for QP assessments. Further research is needed to better evaluate the role that patient clinical factors may play on QP use, as well as how unit policies, resources, and education may influence decisions for QP assessments. Among units with high QP use, dissemination of implementation strategies used to promote routine use would be beneficial to support widespread implementation efforts across hospitals and health systems. Conclusion Quantitative pupillometer is a useful tool for pupillary assessment, with years of research and the support of clinicians to its utilization. This study established baseline estimates of routine use, as well as factors that may influence frequency of QP assessments. Additional research is needed to definitively determine optimal frequency of assessments, as well as impact of these assessments on patient outcomes. Implications Sites that consistently have high prevalence of routine QP use are encouraged to disseminate implementation strategies used to inform optimal approaches for widespread use across healthcare settings. Declarations Author Contribution D.O. and M.M. contributed to the study design. S.G., D.H., T.L., M.D., D.O., and M.M. collected the data. D.O. and M.M. conducted the data analysis. D.O. and M.M. supervised the study. S.G., D.H., T.L., S.L., C.M., S.Y., M.D., D.O., and M.M. wrote the manuscript. S.G., D.H., T.L., S.L., C.M., S.Y., M.D., D.O., and M.M. critically revised the manuscript for important intellectual content. Acknowledgement The study team would like to acknowledge Maria Goralski and Brittany Doyle who played instrumental roles in data collection. References Ali, A. M. S., Gul, W., Sen, J., Hewitt, S. J., Olubajo, F., & McMahon, C. (2024). Evaluating the utility of quantitative pupillometry in a neuro-critical care setting for the monitoring of intracranial pressure: A prospective cohort study. Clinical Neurology And Neurosurgery , 239 , 108215. https://doi.org/10.1016/j.clineuro.2024.108215 Barra, M. E., Zink, E. K., Bleck, T. P., Caceres, E., Farrokh, S., Foreman, B., Cediel, E. G., Hemphill, J. C., Nagayama, M., Olson, D. M., & Suarez, J. I. & Curing Coma Campaign, i. c. m. (2023). Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Hospital Course, Confounders, and Medications. Neurocritical Care , 39 (3), 586–592. https://doi.org/10.1007/s12028-023-01803-4 Bashir, M. M. I., Olson, D. M., Miller, N. T., Bunt, S. C., & Cullum, C. M. (2025). Quantitative pupillometry as a potential biomarker in early concussion assessment. Journal Of Clinical Neuroscience : Official Journal Of The Neurosurgical Society Of Australasia , 132 , 111003. https://doi.org/10.1016/j.jocn.2024.111003 Bower, M. M., Sweidan, A. J., Xu, J. C., Stern-Neze, S., Yu, W., & Groysman, L. I. (2021). Quantitative Pupillometry in the Intensive Care Unit. Journal Of Intensive Care Medicine , 36 (4), 383–391. https://doi.org/10.1177/0885066619881124 Chitiyo, C., Verhey, R., Mboweni, S. N., Healey, A., Chibanda, D., Araya, R., & Wagenaar, B. H. (2023). Applying the Consolidated Framework for Implementation Research to Optimize Implementation Strategies for the Friendship Bench Psychological Intervention in Zimbabwe. Global Implementation Research and Applications , 3 (3), 245–258. https://doi.org/10.1007/s43477-023-00093-4 Doyle, B. R., Aiyagari, V., Yokobori, S., Kuramatsu, J. B., Barnes, A., Puccio, A., Nairon, E. B., Marshall, J. L., & Olson, D. M. (2024). Anisocoria After Direct Light Stimulus is Associated with Poor Outcomes Following Acute Brain Injury. Neurocritical Care . https://doi.org/10.1007/s12028-024-02030-1 Feigin, V. L., Vos, T., Nichols, E., Owolabi, M. O., Carroll, W. M., Dichgans, M., Deuschl, G., Parmar, P., Brainin, M., & Murray, C. (2020). The global burden of neurological disorders: translating evidence into policy. Lancet Neurology , 19 (3), 255–265. https://doi.org/10.1016/S1474-4422(19)30411-9 Figueroa, S. A., Olson, D. M., Kamal, A., & Aiyagari, V. (2024). Quantitative Pupillometry: Clinical Applications for the Internist. American Journal Of Medicine , 137 (9), 825–831. https://doi.org/10.1016/j.amjmed.2024.04.043 Ghauri, M. S., Ueno, A., Mohammed, S., Miulli, D. E., & Siddiqi, J. (2022). Evaluating the Reliability of Neurological Pupillary Index as a Prognostic Measurement of Neurological Function in Critical Care Patients. Cureus , 14 (9), e28901. https://doi.org/10.7759/cureus.28901 Godau, J., Bierwirth, C., Rosche, J., & Bosel, J. (2021). Quantitative Infrared Pupillometry in Nonconvulsive Status Epilepticus. Neurocritical Care , 35 (1), 113–120. https://doi.org/10.1007/s12028-020-01149-1 Gupta, A., Bansal, R., Sharma, A., & Kapil, A. (2023). Pupillary Signs. In A. Gupta, R. Bansal, A. Sharma, & A. Kapil (Eds.), Ophthalmic Signs in Practice of Medicine (pp. 475–492). Springer Nature Singapore. https://doi.org/10.1007/978-981-99-7923-3_16 Hsu, C. H., & Kuo, L. T. (2023). Application of Pupillometry in Neurocritical Patients. J Pers Med , 13 (7). https://doi.org/10.3390/jpm13071100 Jiang, B. S. J., Huff, E., Hanna, A., Gourabathini, H., & Bhalala, U. (2024). Nursing insights on the effectiveness of automated pupillometry in two distinct pediatric intensive care units. Journal Of Pediatric Nursing , 78 , e398–e403. https://doi.org/10.1016/j.pedn.2024.07.032 Kamal, A., Kim, Y., Salter, A., Gunna, S., Nairon, E. B., & Olson, D. M. (2024). There Is Significant Within-Subject Variation in the Time from Light Stimulus to Maximum Pupil Constriction Among Healthy Controls. J Clin Med , 13 (23). https://doi.org/10.3390/jcm13237451 Kamal, A., Nairon, E. B., Bashmakov, A., Aoun, S. G., & Olson, D. M. (2024). Time to maximum pupil constriction is variable in neurocritical care patients. Journal Of Clinical Monitoring And Computing . https://doi.org/10.1007/s10877-024-01234-2 Kang, S., Eum, S., Chang, Y., Koyanagi, A., Jacob, L., Smith, L., Shin, J. I., & Song, T. J. (2022). Burden of neurological diseases in Asia from 1990 to 2019: a systematic analysis using the Global Burden of Disease Study data. British Medical Journal Open , 12 (9), e059548. https://doi.org/10.1136/bmjopen-2021-059548 Lundquist, C. B., Lillelund, S., Hansen, G. M., Knudsen, V. D., Pommerich, U. M., Pallesen, H., & Brunner, I. C. (2024). Implementation of Standardized Outcome Measures for Motor Function in a Neurorehabilitation Hospital. Global Implementation Research and Applications , 4 (2), 179–191. https://doi.org/10.1007/s43477-023-00103-5 Nyancho, D., Atem, F. D., Venkatachalam, A. M., Barnes, A., Hill, M., Traylor, J. I., Stutzman, S. E., Bedros, N., Aiyagari, V., & Aoun, S. G. (2021). Anisocoria Correlates With Injury Severity and Outcomes After Blunt Traumatic Brain Injury. Journal Of Neuroscience Nursing , 53 (6), 251–255. https://doi.org/10.1097/jnn.0000000000000613 Nyholm, B., Obling, L., Hassager, C., Grand, J., Moller, J., Othman, M., Kondziella, D., & Kjaergaard, J. (2022). 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. PLoS One , 17 (7), e0272303. https://doi.org/10.1371/journal.pone.0272303 Oddo, M., Taccone, F. S., Petrosino, M., Badenes, R., Blandino-Ortiz, A., Bouzat, P., Caricato, A., Chesnut, R. M., Feyling, A. C., Ben-Hamouda, N., Hemphill, J. C., Koehn, J., Rasulo, F., Suarez, J. I., Elli, F., Vargiolu, A., Rebora, P., Galimberti, S., & Citerio, G. (2023). & investigators, O. s. The Neurological Pupil index for outcome prognostication in people with acute brain injury (ORANGE): a prospective, observational, multicentre cohort study. Lancet Neurol , 22 (10), 925–933. https://doi.org/10.1016/S1474-4422(23)00271-5 Privitera, C. M., Neerukonda, S. V., Aiyagari, V., Yokobori, S., Puccio, A. M., Schneider, N. J., Stutzman, S. E., & Olson, D. M. (2022). A differential of the left eye and right eye neurological pupil index is associated with discharge modified Rankin scores in neurologically injured patients. Bmc Neurology , 22 (1), 273. https://doi.org/10.1186/s12883-022-02801-3 Romagnosi, F., Bongiovanni, F., & Oddo, M. (2020). Eyeing up the injured brain: automated pupillometry and optic nerve sheath diameter. Current Opinion In Critical Care , 26 (2), 115–121. https://doi.org/10.1097/MCC.0000000000000710 Sridhar, A., Olesegun, O., & Drahota, A. (2023). Identifying Methods to Select and Tailor Implementation Strategies to Context-Specific Determinants in Child Mental Health Settings: A Scoping Review. Global Implementation Research and Applications , 3 (2), 212–229. https://doi.org/10.1007/s43477-023-00086-3 Tran, D. K., Poole, C., Tobias, E., Moores, L., Espinoza, M., & Chen, J. W. (2022). 7-Year Experience with Automated Pupillometry and Direct Integration With the Hospital Electronic Medical Record. World Neurosurg , 160 , e344–e352. https://doi.org/10.1016/j.wneu.2022.01.022 Trent, T., Vashisht, A., Novakovic, S., Kanter, G., Nairon, E., Lark, A., Tucker, A., Reddy, V., McCreary, M., Stutzman, S. E., & Olson, D. M. (2023). Pupillary light reflex measured with quantitative pupillometry has low sensitivity and high specificity for predicting neuroworsening after traumatic brain injury. J Am Assoc Nurse Pract , 35 (2), 130–134. https://doi.org/10.1097/JXX.0000000000000822 Vrettou, C. S., Fragkou, P. C., Mallios, I., Barba, C., Giannopoulos, C., Gavrielatou, E., & Dimopoulou, I. (2024). The Role of Automated Infrared Pupillometry in Traumatic Brain Injury: A Narrative Review. J Clin Med , 13 (2). https://doi.org/10.3390/jcm13020614 Weiner, B. J., Lewis, C. C., Stanick, C., Powell, B. J., Dorsey, C. N., Clary, A. S., Boynton, M. H., & Halko, H. (2017). Psychometric assessment of three newly developed implementation outcome measures. Implement Sci , 12 (1), 108. https://doi.org/10.1186/s13012-017-0635-3 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Dec, 2025 Read the published version in Global Implementation Research and Applications → Version 1 posted Editorial decision: Revision requested 15 Aug, 2025 Reviews received at journal 07 Jul, 2025 Reviewers agreed at journal 03 Jul, 2025 Reviews received at journal 13 Jun, 2025 Reviewers agreed at journal 08 Jun, 2025 Reviewers invited by journal 26 Mar, 2025 Editor assigned by journal 15 Mar, 2025 Submission checks completed at journal 15 Mar, 2025 First submitted to journal 14 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Kang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Lundquist et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The pupillary light reflex (PLR) response is a rapid assessment used to make emergent life and death decisions about the need for high-risk invasive therapies, costly diagnostic testing, or withdrawal of care (Romagnosi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tran et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Despite its pivotal role in the care and management of patients in the Neurocritical Care Unit (NCCU), current practice for manual PLR assessment is inconsistent, outdated, highly subjective and repeatedly proven to be unreliable among nurses, physicians, advanced practice providers, and emergency responders (Ali et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Bashir et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Godau et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Trent et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Even with substantial and consistent evidence confirming the superiority of QP for serial assessments in the critical care setting, implementation of this best practice remains fragmented and inconsistent among clinical teams (Jiang et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kamal, Kim, et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe PLR exam is a standard component of serial neurological assessments in the NCCU setting, and decades of research indicates its usefulness as a prognostic tool (Barra et al., 2023; Figueroa et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ghauri et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The pupilloconstrictor response is a parasympathetic reflex caused by stimulation of the 3rd cranial nerve (oculomotor). The 3rd cranial nerve is adjacent to the medial temporal lobe and the midbrain third nucleus; therefore, damage to these areas of the brain controlling consciousness can disrupt cranial nerve pathways, resulting in a decreased PLR response (Figueroa et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kamal, Nairon, et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Though the importance of PLR assessments may seem obvious, there are significant limitations to manual pupillary exams that rely upon subjective assessment (Nyholm et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Substantial evidence demonstrates superiority of QP assessments, specifically with its high reliability and accuracy of assessments (Godau et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kamal, Nairon, et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Oddo et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, even if human assessments were reliable, the assessment of PLR reaction speed (brisk, sluggish, and fixed) is inadequate to determine whether the pupil is functioning in a normal manner (Doyle et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Nyancho et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Privitera et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A brisk pupil can react abnormally, and a sluggish pupil can react normally. Though there are well studied benefits to QP, pupillometry does have barriers in its implementation which ultimately can limit its adoption at different institutions (Bower et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Vrettou et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Furthermore, anecdotal observations indicate fragmented and inconsistent use of this practice between critical care units, ultimately leading to a gap in the literature of estimates of routine use of QP(Sridhar et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eAim of Study\u003c/h3\u003e\n\u003cp\u003eThis study aims to quantify the use of QP in NCCU and examine clinical determinants of routine QP use. It also seeks to identify clinician beliefs and perceptions of acceptability, appropriateness, feasibility, and fidelity of QP use for patients.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e\n\n \n\n"},{"header":"Methods","content":"\u003ch2\u003eResearch Design\u003c/h2\u003e\u003cp\u003eThis study utilized a multi-site, period prevalence observational implementation science design. The study took place in the NCCU of two separate academic medical centers: Site A, which is in the Southwestern United States, and Site B, which is in the Midwestern United States. Site A is an 849-bed medical center, with a 24-bed NCCU. This site is designated as a comprehensive stroke center by the American Stroke Association, a Magnet designated facility by the American Nurses Credentialing Center, and the unit has received Beacon recognition by the American Association of Critical Care Nurses. The site has a designated policy on QP use, as well as a handheld pupillometer available in each patient room. Site B is a 1,456-bed academic medical center, with a 24 bed NCCU. Site B is also an accredited comprehensive stroke center by The Joint Commission, has ANCC Magnet designation, and is a Beacon Award unit. The site does not have a specific policy on QP use, but it may be ordered by providers with specific timing and frequency of assessments or used at the nurses’ discretion. Handheld pupillometers are available at a ratio of approximately 1 pupillometer per 1.75 rooms. Each site had the study reviewed and approved by their respective Institutional Review Boards (IRBs) prior to data collection.\u003c/p\u003e\u003cp\u003eTo address Aim 1 and quantify routine use of QP at each site, both sites recorded frequency of QP use daily during the same 2-week period to establish period prevalence. To examine clinical determinants of routine use, daily clinical data on patients meeting inclusion criteria were also recorded.\u003c/p\u003e\u003ch3\u003eSample and Setting\u003c/h3\u003e\u003cp\u003eThe Inclusion criteria were: Adult patients (\u0026gt; 18 years of age) admitted to Neurocritical care service. The exclusion criteria were patients not on Neurocritical care service, those on comfort measure status in the 24 hours prior to data collection, and any patient enrolled in a separate device or drug research study that may influence routine QP assessments. Clinical data that were recorded daily included: daily patient acuity measures (mechanical ventilation, vasoactive medications, invasive cerebral monitoring, EEG monitoring, administration of mannitol/hypertonic saline, and need for neurosurgical intervention), documentation of pupil examination, and patient demographic data (diagnosis, age, gender, race and ethnicity). Data was recorded in REDCap, then exported and stored on a password protected network drive for cleaning and analysis.\u003c/p\u003e\u003cp\u003e Aim 2 was guided by the Consolidated Framework for Implementation Research (CFIR) to evaluate determinants of routine use of QP among healthcare clinicians. The CFIR is a determinant framework composed of five domains that influence implementation of evidence-based practices into routine care settings. Domains include the characteristics of innovation, the outer setting, inner setting, characteristics of individuals, and the process of implementation. Within each domain, specific constructs serve as determinants or factors influencing routine implementation. A quantitative survey that included these CFIR domains was created to evaluate clinician perceptions of factors that may influence their routine use of QP(Chitiyo et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The survey also included quantitative questions from the Acceptability of Intervention Measure (AIM), the Intervention Appropriateness Measure (IAM), and Feasibility of Implementation Measure (FIM) (Weiner et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The quantitative survey was created in REDCap and distributed via an emailed survey link to clinicians who routinely care for patients in each of the respective NCCUs of the study. Inclusion criteria for clinicians were any employed healthcare provider on the Neurocritical care service at each site, including attending physicians, neurology/neurosurgery trainees, advanced practice providers, registered nurses, and pharmacists who are employed to work primarily in the NCCU. The survey was sent after the daily prevalence period and was open for clinicians to complete for 3 weeks.\u003c/p\u003e\u003cp\u003eData were analyzed using SPSS at each study site. Period prevalence was calculated as the proportion of patients at each site receiving QP relative to the proportion of patients eligible to receive QP daily during a 14-day period. Descriptive statistics, including means, frequencies, and standard deviations were calculated with clinical data to describe characteristics of the study sample. Bivariate Chi-square statistics were calculated to determine the proportion of patients receiving QP based on demographic and clinical characteristics. Logistic regression models were used to identify clinical determinants of routine use at each site. To evaluate clinician responses to survey items on perceptions of use, descriptive statistics were calculated to report means and frequencies of aggregate responses by site.\u003c/p\u003e\u003ch3\u003eEthical Considerations\u003c/h3\u003e\u003cp\u003e This study was approved by the institutional review board of the University of Texas Southwestern Medical Center before data collection began (IRB Number: STU-2024-0115). The study was reviewed under the exempt category as PHI was not collected from subjects in this study. When filling out the survey, subjects were provided with an information sheet detailing the study’s purpose and procedures, as well as their right to refusal to participate in the study.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePeriod Prevalence of QP Use\u003c/h2\u003e \u003cp\u003eDuring the 2-week prevalence period, Site A recorded 270 observations among 75 patients. The daily prevalence of QP use at Site A ranged from 88%-100% among eligible patients. Site B recorded 236 observations from 71 patients, with a daily prevalence ranging from 9%-50%.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical Determinants of QP Use\u003c/h3\u003e\n\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, univariate analysis at Site A for each of the clinical acuity measures observed and QP use were: mechanical ventilation (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.525; p\u0026thinsp;=\u0026thinsp;0.469), vasoactive medications (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;2.603; p\u0026thinsp;=\u0026thinsp;0.107), continuous EEG monitoring (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.038; p\u0026thinsp;=\u0026thinsp;0.845), hypertonic saline administration (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.358; p\u0026thinsp;=\u0026thinsp;0.550), and diagnosis (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;6.342; p\u0026thinsp;=\u0026thinsp;0.386). After abstracting diagnoses of patients in the NCCU, a multivariate analysis provided the following chi square value and p value (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;6.3424; p\u0026thinsp;=\u0026thinsp;0.3860). For Site B, there was a strong relationship between QP use and ventilation (ꭓ=42.54; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), vasoactive medications (ꭓ=8.36; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), continuous EEG (X\u003cem\u003e2\u003c/em\u003e\u0026thinsp;=\u0026thinsp;33.84; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hypertonic saline administration (X\u003cem\u003e2\u003c/em\u003e\u0026thinsp;=\u0026thinsp;27.60; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, patients with ICH and TBI had higher proportion of QP use (X\u003csup\u003e2=\u003c/sup\u003e55.297, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Multinomial logistic regression modeling indicated patient diagnosis, age, mechanical ventilation, and continuous EEG were factors most predictive of QP assessments (X\u003csup\u003e2=\u003c/sup\u003e167.14, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSite A and B Clinical Determinants of QP Use (Chi Square and P-Value)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eChi Square (X\u003csup\u003e2\u003c/sup\u003e, ꭓ)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSITE (A or B)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSite A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSite B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSite A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSite B\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical Ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eꭓ = 42.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasoactive Medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;2.603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eꭓ = 8.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContinuous EEG Monitoring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eꭓ = 33.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertonic Saline Administration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eꭓ = 27.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;6.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eꭓ = 55.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eClinician Perspectives on Routine QP Use\u003c/h3\u003e\n\u003cp\u003eAt Site A, n\u0026thinsp;=\u0026thinsp;68 clinicians completed the survey on perspectives and determinants of routine QP use, while n\u0026thinsp;=\u0026thinsp;11 completed the survey for Site B. Survey respondents at both sites were similar with regards to years of QP use and years of experience (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Most respondents at both sites were clinical nurses (n\u0026thinsp;=\u0026thinsp;42, 61.8%; n\u0026thinsp;=\u0026thinsp;5; 45% for Site A, B, respectively). Across both sites, there was also adequate representation from other members of the healthcare team that included attending physicians, residents/fellows, advance practice providers, and clinical pharmacists.\u003c/p\u003e \u003cp\u003eWhen looking at reported determinants of routine QP use according to CFIR domains, respondents at both sites equally welcomed QP use when caring for their patients (mean 4.7), found the practice appealing (mean 4.5), and useful for routine clinical care (mean 4.6) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Respondents also reported strong advantages of QP use over manual pupil assessments (mean 4.7, 4.6 for Site A, B, respectively), a solid understanding of QP values and what they mean when caring for patients (mean 4.6 at both sites), and the perspective that QP use is well supported by published research studies (4.2, 4.0 for Site A, B, respectively). While respondents at both sites reported QP is suitable for use in all patients in the NCCU (mean 4.4, 4.3,) respondents at Site A felt QP use is also feasible for all ICU patients (mean 4.2), which differed from Site B (mean 3.4). Site A respondents reported lower scores overall for feasibility of routine QP use (mean 3.2\u0026ndash;3.6) when compared to Site B (mean 4.2). Site A also reported frequent QP assessment being more burdensome for staff (mean 3.2) when compared to Site B (mean 2.6). Scores for overall difficulty of starting QP use were similar between sites, while ongoing maintenance of QP was reported as being more difficult for Site B (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics/Characteristics of Clinicians\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRole\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSite A N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSite B N (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNurse Leader (CNO, Director, Manager)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdvanced Practice Provider (PA, CNS, NP, APRN)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNurse Educator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical/Bedside Nurse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (61.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (45.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcademic Faculty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttending Physician\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFellow Physician\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (9.21%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssociate's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBSN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (64.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSN or Other Masters Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDNP, PharmD, MD, or Other Practice Doctorate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (45.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Length of QP Use in Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.8 (3.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.70 (2.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Age (Years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.4 (11.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.70 (7.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSite A Survey Results (Mean answer (Standard Deviation))\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe questions below are on a Likert Scale:\u003c/p\u003e \u003cp\u003e1 (Strongly Disagree), 2(Disagree), 3 (Neutral), 4 (Agree), 5(Strongly Agree).\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSite A Results\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSite B Results\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQP assessment is well supported by published studies.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2 (0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQP offers a strong advantage over manual pupil assessments.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7 (0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI understand QP values and what they mean when caring for my patient.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6 (0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQP is useful in routine clinical practice.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6 (0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQP is used in other Neurocritical Care Programs in the region.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8 (0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQP should be limited to the most acute patients in the NCCU.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3 (1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQP should always be used instead of manual pupil.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 (1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI always perform QP for pupillary assessment in eligible patient.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2 (0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMy unit has a policy on QP use.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9 (0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhen performing pupillary assessments, I follow the frequency and indications listed in the policy.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9 (0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQP is appealing to me.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5 (0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI welcome QP use in my patients.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7 (0.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQP is suitable for use in all patients in the NCCU.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.4 (0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQP is suitable for use in all patients in all ICUs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2 (0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequent (q 1\u0026ndash;2 hour) QP assessment in the NCCU seems possible.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.6 (1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequent (q 1\u0026ndash;2 hour) QP assessment seems easy to me.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 (1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequent (q 1\u0026ndash;2 hour) QP assessment is a burden for nursing staff.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2 (1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eThe questions below are on a scale from 1 (Not Difficult at All) to 10 (Extremely Difficult).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHow difficult was it to start QP use in your NCCU?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9 (2.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHow difficult was it to maintain QP use in your NCCU?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.0 (2.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHow difficult was it to hardwire regular QP use in your NCCU?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.4 (2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall, how difficult was starting QP use in your NCCU?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.0 (1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall, how difficult was maintaining QP use in your NCCU?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7 (1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall, how difficult was completing QP use in your NCCU (i.e. recording meaningful outcomes, hardwiring change in practice)?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9 (1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCFIR: CFIR Domains AA: Acceptability \u0026amp; Appropriateness F: Feasibility E: Ease of Use\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eAt Site A, we found limitations in piloting this study in the fact that most patients in the NCCU receive pupillometry. Though staff surveys indicate Site A has a strong inclination to pupillometry, other facilities without existing protocols may experience different daily prevalence than in this NCCU. This idea of further assessing ICUs without protocols in place can make for areas of further study. Another limitation in this study is that staff were not questioned regarding the quality or quantity of education they received in pupillometry specifically. Differing training amongst NCCU\u0026rsquo;s can result in varying utilization of pupillometry, which can contradict the overall universal acceptance of QP.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study is the first, to our knowledge, to document variation in routine QP use within NCCUs. Although both sites in this study were large academic medical centers, there were large differences in prevalence of routine QP assessments. Pupil assessments remain a standard component of serial neurological examinations for patients suffering from neurological conditions. The emergence of QP technology has better standardized these pupillary assessments, as multiple studies have confirmed the accuracy of these assessments over manual evaluations (Godau et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jiang et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Nyholm et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Despite this evidence, our study findings demonstrate it is not routinely used by healthcare clinicians among all patients in NCCUs. The primary aim of this study was also to evaluate if there were clinical factors associated with routine QP use among NCCU healthcare clinicians. Because QP was widely used at site A, clinical factors of the patient, including measures of acuity and patient diagnosis, did not significantly influence use of QP for pupillary assessments. This can be explained by the fact that the organization\u0026rsquo;s QP assessment protocol states the exam is to be performed on all NCCU patients, regardless of these clinical factors. In contrast, site B had larger variability in routine QP use. As such, patients with higher acuity had a higher proportion of QP use, suggesting QP assessments were done more often on these patients. Similarly, patients with certain diagnosis types, namely ICH and TBI, had QP assessments performed more often. A common practice on this unit is generally to perform QP assessments on patients with higher neurological acuity, which would explain these study findings. As established in previous studies, accurate assessment of the PLR is crucial in patients across multiple diagnosis types in NCCUs (Gupta et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hsu \u0026amp; Kuo, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, there are no definitive recommendations or accreditation requirements that QP be used routinely for specific diagnoses or conditions, which could also explain the variation in routine use among the two sites in this study.\u003c/p\u003e \u003cp\u003eIn addition to evaluating the role that clinical factors had on routine QP use, this study also evaluated how clinician perceptions influenced QP use. Overwhelmingly, clinicians at both sites were familiar with the evidence to support QP use for pupillary assessments, and felt the practice was acceptable and appropriate for patients with neurological injury. Clinicians also viewed adoption and utilization of QP favorably at both study sites. Clinician scores differed between sites with respect to burden and feasibility of routine QP use, with Site A reporting QP use as slightly more burdensome and not as consistently feasible when compared with Site B. Site A also had much higher routine use prevalence, suggesting QP assessments were done regularly which could explain the slightly additional reported burden, when compared to Site B that used QP less frequently on all patients. This finding highlights an important area for future consideration: weighing the benefit of high frequency QP assessments with clinician workload and feasibility. Currently there are no studies that definitively demonstrate the benefit of higher QP assessment frequency with improved patient outcomes, and optimal frequency of QP assessments remain uncertain.\u003c/p\u003e \u003cp\u003eThe use of an internal hospital or unit policy on frequency of QP assessments may influence prevalence of routine use. In our study, site A had an existing policy that included recommended frequency of QP assessments, while site B did not have a specific policy on QP use. It is likely that this influenced the higher prevalence rates observed in Site A when compared to site B, as well as the role that clinical factors played in determining the need for QP assessments. Further research is needed to better evaluate the role that patient clinical factors may play on QP use, as well as how unit policies, resources, and education may influence decisions for QP assessments. Among units with high QP use, dissemination of implementation strategies used to promote routine use would be beneficial to support widespread implementation efforts across hospitals and health systems.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eQuantitative pupillometer is a useful tool for pupillary assessment, with years of research and the support of clinicians to its utilization. This study established baseline estimates of routine use, as well as factors that may influence frequency of QP assessments. Additional research is needed to definitively determine optimal frequency of assessments, as well as impact of these assessments on patient outcomes.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eImplications\u003c/h2\u003e \u003cp\u003eSites that consistently have high prevalence of routine QP use are encouraged to disseminate implementation strategies used to inform optimal approaches for widespread use across healthcare settings.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eD.O. and M.M. contributed to the study design. S.G., D.H., T.L., M.D., D.O., and M.M. collected the data. D.O. and M.M. conducted the data analysis. D.O. and M.M. supervised the study. S.G., D.H., T.L., S.L., C.M., S.Y., M.D., D.O., and M.M. wrote the manuscript. S.G., D.H., T.L., S.L., C.M., S.Y., M.D., D.O., and M.M. critically revised the manuscript for important intellectual content.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe study team would like to acknowledge Maria Goralski and Brittany Doyle who played instrumental roles in data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAli, A. M. S., Gul, W., Sen, J., Hewitt, S. J., Olubajo, F., \u0026amp; McMahon, C. (2024). Evaluating the utility of quantitative pupillometry in a neuro-critical care setting for the monitoring of intracranial pressure: A prospective cohort study. \u003cem\u003eClinical Neurology And Neurosurgery\u003c/em\u003e, \u003cem\u003e239\u003c/em\u003e, 108215. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.clineuro.2024.108215\u003c/span\u003e\u003cspan address=\"10.1016/j.clineuro.2024.108215\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarra, M. E., Zink, E. K., Bleck, T. P., Caceres, E., Farrokh, S., Foreman, B., Cediel, E. G., Hemphill, J. C., Nagayama, M., Olson, D. M., \u0026amp; Suarez, J. I. \u0026amp; Curing Coma Campaign, i. c. m. (2023). Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Hospital Course, Confounders, and Medications. \u003cem\u003eNeurocritical Care\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(3), 586\u0026ndash;592. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12028-023-01803-4\u003c/span\u003e\u003cspan address=\"10.1007/s12028-023-01803-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBashir, M. M. I., Olson, D. M., Miller, N. T., Bunt, S. C., \u0026amp; Cullum, C. M. (2025). Quantitative pupillometry as a potential biomarker in early concussion assessment. \u003cem\u003eJournal Of Clinical Neuroscience : Official Journal Of The Neurosurgical Society Of Australasia\u003c/em\u003e, \u003cem\u003e132\u003c/em\u003e, 111003. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jocn.2024.111003\u003c/span\u003e\u003cspan address=\"10.1016/j.jocn.2024.111003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBower, M. M., Sweidan, A. J., Xu, J. C., Stern-Neze, S., Yu, W., \u0026amp; Groysman, L. I. (2021). Quantitative Pupillometry in the Intensive Care Unit. \u003cem\u003eJournal Of Intensive Care Medicine\u003c/em\u003e, \u003cem\u003e36\u003c/em\u003e(4), 383\u0026ndash;391. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0885066619881124\u003c/span\u003e\u003cspan address=\"10.1177/0885066619881124\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChitiyo, C., Verhey, R., Mboweni, S. N., Healey, A., Chibanda, D., Araya, R., \u0026amp; Wagenaar, B. H. (2023). Applying the Consolidated Framework for Implementation Research to Optimize Implementation Strategies for the Friendship Bench Psychological Intervention in Zimbabwe. \u003cem\u003eGlobal Implementation Research and Applications\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e(3), 245\u0026ndash;258. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s43477-023-00093-4\u003c/span\u003e\u003cspan address=\"10.1007/s43477-023-00093-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoyle, B. R., Aiyagari, V., Yokobori, S., Kuramatsu, J. B., Barnes, A., Puccio, A., Nairon, E. B., Marshall, J. L., \u0026amp; Olson, D. M. (2024). Anisocoria After Direct Light Stimulus is Associated with Poor Outcomes Following Acute Brain Injury. \u003cem\u003eNeurocritical Care\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12028-024-02030-1\u003c/span\u003e\u003cspan address=\"10.1007/s12028-024-02030-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeigin, V. L., Vos, T., Nichols, E., Owolabi, M. O., Carroll, W. M., Dichgans, M., Deuschl, G., Parmar, P., Brainin, M., \u0026amp; Murray, C. (2020). The global burden of neurological disorders: translating evidence into policy. \u003cem\u003eLancet Neurology\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(3), 255\u0026ndash;265. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S1474-4422(19)30411-9\u003c/span\u003e\u003cspan address=\"10.1016/S1474-4422(19)30411-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFigueroa, S. A., Olson, D. M., Kamal, A., \u0026amp; Aiyagari, V. (2024). Quantitative Pupillometry: Clinical Applications for the Internist. \u003cem\u003eAmerican Journal Of Medicine\u003c/em\u003e, \u003cem\u003e137\u003c/em\u003e(9), 825\u0026ndash;831. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.amjmed.2024.04.043\u003c/span\u003e\u003cspan address=\"10.1016/j.amjmed.2024.04.043\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhauri, M. S., Ueno, A., Mohammed, S., Miulli, D. E., \u0026amp; Siddiqi, J. (2022). Evaluating the Reliability of Neurological Pupillary Index as a Prognostic Measurement of Neurological Function in Critical Care Patients. \u003cem\u003eCureus\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(9), e28901. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7759/cureus.28901\u003c/span\u003e\u003cspan address=\"10.7759/cureus.28901\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGodau, J., Bierwirth, C., Rosche, J., \u0026amp; Bosel, J. (2021). Quantitative Infrared Pupillometry in Nonconvulsive Status Epilepticus. \u003cem\u003eNeurocritical Care\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(1), 113\u0026ndash;120. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12028-020-01149-1\u003c/span\u003e\u003cspan address=\"10.1007/s12028-020-01149-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta, A., Bansal, R., Sharma, A., \u0026amp; Kapil, A. (2023). Pupillary Signs. In A. Gupta, R. Bansal, A. Sharma, \u0026amp; A. Kapil (Eds.), \u003cem\u003eOphthalmic Signs in Practice of Medicine\u003c/em\u003e (pp. 475\u0026ndash;492). Springer Nature Singapore. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-981-99-7923-3_16\u003c/span\u003e\u003cspan address=\"10.1007/978-981-99-7923-3_16\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsu, C. H., \u0026amp; Kuo, L. T. (2023). Application of Pupillometry in Neurocritical Patients. \u003cem\u003eJ Pers Med\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(7). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/jpm13071100\u003c/span\u003e\u003cspan address=\"10.3390/jpm13071100\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang, B. S. J., Huff, E., Hanna, A., Gourabathini, H., \u0026amp; Bhalala, U. (2024). Nursing insights on the effectiveness of automated pupillometry in two distinct pediatric intensive care units. \u003cem\u003eJournal Of Pediatric Nursing\u003c/em\u003e, \u003cem\u003e78\u003c/em\u003e, e398\u0026ndash;e403. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pedn.2024.07.032\u003c/span\u003e\u003cspan address=\"10.1016/j.pedn.2024.07.032\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamal, A., Kim, Y., Salter, A., Gunna, S., Nairon, E. B., \u0026amp; Olson, D. M. (2024). There Is Significant Within-Subject Variation in the Time from Light Stimulus to Maximum Pupil Constriction Among Healthy Controls. \u003cem\u003eJ Clin Med\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(23). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/jcm13237451\u003c/span\u003e\u003cspan address=\"10.3390/jcm13237451\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamal, A., Nairon, E. B., Bashmakov, A., Aoun, S. G., \u0026amp; Olson, D. M. (2024). Time to maximum pupil constriction is variable in neurocritical care patients. \u003cem\u003eJournal Of Clinical Monitoring And Computing\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10877-024-01234-2\u003c/span\u003e\u003cspan address=\"10.1007/s10877-024-01234-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKang, S., Eum, S., Chang, Y., Koyanagi, A., Jacob, L., Smith, L., Shin, J. I., \u0026amp; Song, T. J. (2022). Burden of neurological diseases in Asia from 1990 to 2019: a systematic analysis using the Global Burden of Disease Study data. \u003cem\u003eBritish Medical Journal Open\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(9), e059548. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmjopen-2021-059548\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2021-059548\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLundquist, C. B., Lillelund, S., Hansen, G. M., Knudsen, V. D., Pommerich, U. M., Pallesen, H., \u0026amp; Brunner, I. C. (2024). Implementation of Standardized Outcome Measures for Motor Function in a Neurorehabilitation Hospital. \u003cem\u003eGlobal Implementation Research and Applications\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(2), 179\u0026ndash;191. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s43477-023-00103-5\u003c/span\u003e\u003cspan address=\"10.1007/s43477-023-00103-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNyancho, D., Atem, F. D., Venkatachalam, A. M., Barnes, A., Hill, M., Traylor, J. I., Stutzman, S. E., Bedros, N., Aiyagari, V., \u0026amp; Aoun, S. G. (2021). Anisocoria Correlates With Injury Severity and Outcomes After Blunt Traumatic Brain Injury. \u003cem\u003eJournal Of Neuroscience Nursing\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(6), 251\u0026ndash;255. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/jnn.0000000000000613\u003c/span\u003e\u003cspan address=\"10.1097/jnn.0000000000000613\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNyholm, B., Obling, L., Hassager, C., Grand, J., Moller, J., Othman, M., Kondziella, D., \u0026amp; Kjaergaard, J. (2022). 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. \u003cem\u003ePLoS One\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(7), e0272303. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0272303\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0272303\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOddo, M., Taccone, F. S., Petrosino, M., Badenes, R., Blandino-Ortiz, A., Bouzat, P., Caricato, A., Chesnut, R. M., Feyling, A. C., Ben-Hamouda, N., Hemphill, J. C., Koehn, J., Rasulo, F., Suarez, J. I., Elli, F., Vargiolu, A., Rebora, P., Galimberti, S., \u0026amp; Citerio, G. (2023). \u0026amp; investigators, O. s. The Neurological Pupil index for outcome prognostication in people with acute brain injury (ORANGE): a prospective, observational, multicentre cohort study. \u003cem\u003eLancet Neurol\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(10), 925\u0026ndash;933. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S1474-4422(23)00271-5\u003c/span\u003e\u003cspan address=\"10.1016/S1474-4422(23)00271-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrivitera, C. M., Neerukonda, S. V., Aiyagari, V., Yokobori, S., Puccio, A. M., Schneider, N. J., Stutzman, S. E., \u0026amp; Olson, D. M. (2022). A differential of the left eye and right eye neurological pupil index is associated with discharge modified Rankin scores in neurologically injured patients. \u003cem\u003eBmc Neurology\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(1), 273. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12883-022-02801-3\u003c/span\u003e\u003cspan address=\"10.1186/s12883-022-02801-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRomagnosi, F., Bongiovanni, F., \u0026amp; Oddo, M. (2020). Eyeing up the injured brain: automated pupillometry and optic nerve sheath diameter. \u003cem\u003eCurrent Opinion In Critical Care\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(2), 115\u0026ndash;121. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/MCC.0000000000000710\u003c/span\u003e\u003cspan address=\"10.1097/MCC.0000000000000710\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSridhar, A., Olesegun, O., \u0026amp; Drahota, A. (2023). Identifying Methods to Select and Tailor Implementation Strategies to Context-Specific Determinants in Child Mental Health Settings: A Scoping Review. \u003cem\u003eGlobal Implementation Research and Applications\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e(2), 212\u0026ndash;229. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s43477-023-00086-3\u003c/span\u003e\u003cspan address=\"10.1007/s43477-023-00086-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTran, D. K., Poole, C., Tobias, E., Moores, L., Espinoza, M., \u0026amp; Chen, J. W. (2022). 7-Year Experience with Automated Pupillometry and Direct Integration With the Hospital Electronic Medical Record. \u003cem\u003eWorld Neurosurg\u003c/em\u003e, \u003cem\u003e160\u003c/em\u003e, e344\u0026ndash;e352. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.wneu.2022.01.022\u003c/span\u003e\u003cspan address=\"10.1016/j.wneu.2022.01.022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrent, T., Vashisht, A., Novakovic, S., Kanter, G., Nairon, E., Lark, A., Tucker, A., Reddy, V., McCreary, M., Stutzman, S. E., \u0026amp; Olson, D. M. (2023). Pupillary light reflex measured with quantitative pupillometry has low sensitivity and high specificity for predicting neuroworsening after traumatic brain injury. \u003cem\u003eJ Am Assoc Nurse Pract\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(2), 130\u0026ndash;134. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/JXX.0000000000000822\u003c/span\u003e\u003cspan address=\"10.1097/JXX.0000000000000822\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVrettou, C. S., Fragkou, P. C., Mallios, I., Barba, C., Giannopoulos, C., Gavrielatou, E., \u0026amp; Dimopoulou, I. (2024). The Role of Automated Infrared Pupillometry in Traumatic Brain Injury: A Narrative Review. \u003cem\u003eJ Clin Med\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(2). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/jcm13020614\u003c/span\u003e\u003cspan address=\"10.3390/jcm13020614\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeiner, B. J., Lewis, C. C., Stanick, C., Powell, B. J., Dorsey, C. N., Clary, A. S., Boynton, M. H., \u0026amp; Halko, H. (2017). Psychometric assessment of three newly developed implementation outcome measures. \u003cem\u003eImplement Sci\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), 108. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13012-017-0635-3\u003c/span\u003e\u003cspan address=\"10.1186/s13012-017-0635-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"global-implementation-research-and-applications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gira","sideBox":"Learn more about [Global Implementation Research and Applications](http://link.springer.com/journal/43477)","snPcode":"43477","submissionUrl":"https://submission.springernature.com/new-submission/43477/3","title":"Global Implementation Research and Applications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6226822/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6226822/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground/Introduction\u003c/strong\u003e: Manual pupillary light reflex (PLR) assessment is inconsistent, outdated, and unreliable. Even with evidence of the superiority of QP (Quantitative Pupillometry) assessments, use of manual assessment remains commonplace.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e: This study aims to quantify the use of QP in the NCCU (Neurocritical Care Unit) and examine clinical determinants of routine QP use. It also identifies clinician beliefs and perceptions of acceptability, appropriateness, feasibility, and fidelity of QP use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This multi-site, period prevalence observational implementation study took place at 2 academic NCCUs. Both sites recorded frequency of QP use and acuity measures of patients receiving QP use over a 2-week period. A REDCap® survey was distributed to NCCU clinicians assessing their perceptions on QP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Site A had higher prevalence of QP utilization than Site B. Multinomial logistic regression modeling indicated patient diagnosis, age, mechanical ventilation, and continuous EEG were factors associated with QP use at Site B, however no association was evident at Site A. Survey results were in support of QP at both sites.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion\u003c/strong\u003e: QP is a useful tool for pupillary assessment, with years of research and the support of clinicians to its utilization. Utilization varied at Sites A and B, even though both were in support of QP overall.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: This study established baseline estimates of routine use, as well as factors influencing the frequency of QP assessments. Additional research is needed to definitively determine optimal assessment frequency, role that clinical factors may play, as well as impact of QP on patient outcomes.\u003c/p\u003e","manuscriptTitle":"Determinants of Routine Quantitative Pupillometry in Neurocritical Care","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-14 17:34:13","doi":"10.21203/rs.3.rs-6226822/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-15T17:42:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-07T21:59:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"143355821338185073350728155069120877298","date":"2025-07-03T12:19:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-13T07:29:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"330651071073309746314834547090582176013","date":"2025-06-08T04:30:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-27T02:31:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-15T06:32:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-15T06:29:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Global Implementation Research and Applications","date":"2025-03-14T13:29:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"global-implementation-research-and-applications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gira","sideBox":"Learn more about [Global Implementation Research and Applications](http://link.springer.com/journal/43477)","snPcode":"43477","submissionUrl":"https://submission.springernature.com/new-submission/43477/3","title":"Global Implementation Research and Applications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3f0e429c-c341-4803-9dd1-23f77febd4a6","owner":[],"postedDate":"April 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T16:07:14+00:00","versionOfRecord":{"articleIdentity":"rs-6226822","link":"https://doi.org/10.1007/s43477-025-00203-4","journal":{"identity":"global-implementation-research-and-applications","isVorOnly":false,"title":"Global Implementation Research and Applications"},"publishedOn":"2025-12-24 15:57:40","publishedOnDateReadable":"December 24th, 2025"},"versionCreatedAt":"2025-04-14 17:34:13","video":"","vorDoi":"10.1007/s43477-025-00203-4","vorDoiUrl":"https://doi.org/10.1007/s43477-025-00203-4","workflowStages":[]},"version":"v1","identity":"rs-6226822","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6226822","identity":"rs-6226822","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}