A Novel External Ventricular Drain Sensor to Improve Acquired Brain Injury Monitoring.

INTRODUCTION: The insufficiency of current methods to capture the context and environment of neurocritical care can negatively impact patient outcomes. Insertion of an external ventricular drain (EVD) into the ventricles to monitor intracranial pressure (ICP) is a common lifesaving procedure for acquired brain injury patients. Yet, nursing interventions that significantly affect the measured ICP value, such as changing the EVD stopcock position, are poorly documented. Environmental factors like light and noise levels are not monitored as standard of care despite worse outcomes in patients affiliated with sensory sensitivities. Capturing these missing data is an essential first step toward quantifying their effects. MATERIALS AND METHODS: Our entry point was the development of a stopcock position sensor (SPS) that attaches to the EVD stopcock and time-synchronously annotates the recorded ICP data with its position. A two-phase, prospective, nonrandomized observational study was conducted to evaluate the efficacy of the SPS. Phase I assessed the SPS using an ex vivo simulation of ICP management. Phase II involved human subjects with the SPS attached to the EVD stopcock while patients were managed per standard of care. RESULTS: The SPS accurately annotated the ICP data and identified that the EVD drained the cerebrospinal fluid for 94.52% of total patient monitoring time (16.98 h). For only 3.54% of the time, the stopcock directed the cerebrospinal fluid into the pressure transducer for accurate ICP measurement. For the remaining 1.94% of the time, the stopcock was positioned off: No cerebrospinal fluid drainage and no ICP monitoring. CONCLUSIONS: We successfully captured an important aspect of the ICP monitoring context, the EVD stopcock position, and time-synchronized it with the recorded physiology. Our system enables future investigations into the impact that a broad contextual data environment has on physiological measurements and acquired brain injury patient outcomes. In the future, we aim to capture additional contextual data sources and expand the scope to battlefield environments.

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.