Objective:

The goal of this study is to validate the feasibility of utilizing a stopcock position sensor (SPS) and annotation hub for continuous data acquisition (CDA) to accurately determine the position of an external ventricular drain (EVD) stopcock transducer, a critical factor affecting the accuracy of ICP measurement.

Background:

Environmental and contextual factors can significantly impact physiological data, including ICP. For instance, ICP readings are unreliable when the stopcock is in the open-to-drain position. In patients with acute acquired brain injury, this data is typically recorded manually. Automating the capture of contextual data will enhance data quality for post hoc analysis, including machine learning.

Design/Methods:

The SPS was designed to collect contextual data and generates time-synchronized annotations linked to physiological data. This prospective, non-randomized observational trial will evaluate the effectiveness of the SPS to accurately measure when a transducer is open to drain versus monitoring ICP. Eligible subjects were monitored for up to 24 hours. 

Results:

Phase 1 and 2 prototypes of the SPS were completed between January 2022 and April 2023. From April 2023 to October 2023, the SPS was deployed on the EVD stopcocks of 12 patients in the Neuroscience Intensive Care Unit. These patients were admitted for various neurological disorders, including for subarachnoid hemorrhage (5), intraventricular hemorrhage (2), mass lesion (4), and congenital hydrocephalus (1). All patients completed the trial without any adverse event or complication, providing linked reading to ICP data.

Conclusions:

Our specific aim of this study is that using annotated CDA data in a neurocritical setting, will enhance the clinical utility of ICP monitoring by increasing the accuracy and reliability of ICP readings. Subsequent phases of this study aim to further validate these initial findings. The next version of the annotation hub will collect environmental data in addition to contextual data.