Year: 2025
Type: article
Abstract: A range of techniques are being developed with the goal of leverage physiologic data to detect large vessel occlusion (LVO) in the prehospital setting. The output of most every technique is a continuous (or ordinal) variable, but a threshold is applied to yield a simplified binary outcome (i.e., high-likelihood LVO vs low-likelihood LVO). The mathematically optimal threshold is typically selected to balance sensitivity and specificity. Though intuitive, this approach may not appropriately account for the relative significance of false negatives and false positives. Most importantly, relying on a single threshold is an unnecessary oversimplification, and this one-size-fits-all approach to prehospital LVO detection does not optimally account for the diversity of prehospital systems of care. Here, we use a recently reported technique, optical blood flow imaging, to demonstrate how thresholds can be easily titrated in favor of sensitivity or specificity and thereby provide options that may better serve any given micro-environment.
Institutions: University of Pennsylvania, Temple University, Brown University
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,170
OpenAlex ID: W4409535942