Accepted for/Published in: JMIR Research Protocols
Date Submitted: Jul 29, 2024
Date Accepted: Apr 17, 2025
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Harnessing the Power of Technology to Transform Delirium Severity Measurement in the ICU: Protocol for a Prospective Cohort Study
ABSTRACT
Background:
Delirium, an acute brain dysfunction, is a complication in up to 50% of intensive care unit (ICU) patients. Measuring and mitigating delirium severity can reduce associated morbidity and improve long-term health outcomes post-discharge. However, the perceived complexity of the available delirium detection tools and clinical workload limits the routine assessment of delirium severity. Developing a passive digital marker for delirium severity combining routine electronic health record (EHR) and computer vision technology data could be an implementable, scalable, and sustainable approach.
Objective:
The primary objective is to develop a passive digital marker for delirium severity (PDM-DS) and examine its performance in comparison to validated delirium severity tools (aim 1 and 2). The secondary objective is to evaluate the acceptability and usability of the PDM-DS by patients, families, and clinicians (aim 3).
Methods:
A prospective, longitudinal cohort study will be conducted to develop a PDM-DS using computer vision data and routinely collected EHR data. Following informed consent, the study team will collect image data through continuous digital video recordings of adult patients (>/= 50 years) in their ICU room, routine EHR data(demographic and clinical variables), and administer delirium severity assessments (4 x daily) until ICU discharge or death. The usability and acceptability of the developed PDM-DS will be evaluated by patients, families, and direct care clinicians in a pilot randomized controlled clinical trial (aim 3). Descriptive statistics (means, standard deviations, medians, interquartile ranges, frequencies) and statistical differences between study instruments will be examined. Convolutional neural networks and machine learning will inform model development, testing, and validation. Model performance statistics including accuracy, precision, recall, and the F1 score will be reported.
Results:
Recruitment and data collection are ongoing. As of July 2024, 1,990 patients were screened (31% eligible, n=613), 306 approached (50%), and 71 participants were enrolled (23% enrollment rate). Among the 71 patients, the median age was 67 years (IQR 61-74), 65% male, and 93% Caucasian.
Conclusions:
The PDM-DS could provide real-time, actionable feedback to direct care clinicians on the brain health of ICU patients. Early mitigation of delirium severity may decrease the risk of mortality, future Alzheimer’s Disease and Related Dementia, and length of hospital stay. Clinical Trial: NCT06172491
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