Pupillary light reflex measured with quantitative pupillometry has low sensitivity and high specificity for predicting neuroworsening after traumatic brain injury.

BACKGROUND: Triage and neurological assessment of the 1.7 million traumatic brain injuries occurring annually is often done by nurse practitioners and physician assistants in the emergency department. Subjective assessments, such as the neurological examination that includes evaluation of the pupillary light reflex (PLR), can contain bias. Quantitative pupillometry (QP) standardizes and objectifies the PLR examination. Additional data are needed to determine whether QP can predict neurological changes in a traumatic brain injury (TBI) patient. PURPOSE: This study examines the effectiveness of QP in predicting neurological decline within 24 hours of admission following acute TBI. METHODOLOGY: This prospective, observational, clinical trial used pragmatic sampling to assess PLR in TBI patients using QP within 24 hours of ED admission. Chi-square analysis was used to determine change in patient status, through Glasgow Coma Scale (GCS), at baseline and within 24 hours of admission, to the QP. RESULTS: There were 95 participants included in the analysis; of whom 35 experienced neuroworsening, defined by change in GCS of >2 within the first 24 hours of admission. There was a significant association between an abnormal Neurological Pupil index (NPi), defined as NPi of <3, and neuroworsening (p < .0001). The sensitivity (51.43%) and specificity (91.67%) of abnormal NPi in predicting neuroworsening were varied. CONCLUSION: There is a strong association between abnormal NPi and neuroworsening in the sample of TBI patients with high specificity and moderate sensitivity. IMPLICATIONS: NPi may be an early indicator of neurological changes within 24 hours of ED admission in patients with TBI.

Outcomes From a Nursing-Driven Acute Stroke Care Protocol for Telehealth Encounters.

INTRODUCTION: Nursing care is widely recognized to be a vital element in stroke care delivery. However, no publications examining clinical education and optimal workflow practices as predictors of acute ischemic stroke care metrics exist. This study aimed to explore the impact of a nurse-led workflow to improve patient care that included telestroke encounters in the emergency department. METHODS: A nonrandomized prospective pre- and postintervention unit-level feasibility study design was used to explore how implementing nurse-driven acute stroke care affects the efficiency and quality of telestroke encounters in the emergency department. Nurses and providers in the emergency department received education/training, and then the Nursing-Driven Acute Ischemic Stroke Care protocol was implemented. RESULTS: There were 180 acute ischemic stroke encounters (40.3%) in the control phase and 267 (59.7%) in the postintervention phase with similar demographic characteristics. Comparing the control with intervention times directly affected by the nurse-driven protocol, there was a significant reduction in median door-to-provider times (5 [interquartile range 12] vs 2 [interquartile range 9] minutes, P < .001) and in median door-to-computed tomography scan times (9 [interquartile range 18] vs 5 [interquartile range 11] minutes, P < .001); however, the metrics potentially affected by extraneous variables outside of the nurse-driven protocol demonstrated longer median door-to-ready times (21 [interquartile range 24] vs 25 [interquartile range 25] minutes, P < .001). Door-to-specialist and door-to-needle times were not significantly different. DISCUSSION: In this sample, implementation of the nurse-driven acute stroke care protocol is associated with improved nurse-sensitive stroke time metrics but did not translate to faster delivery of thrombolytic agents for acute ischemic stroke, emphasizing the importance of well-outlined workflows and standardized stroke code protocols at every point in acute ischemic stroke care.