Pre-hospital LVO detection: One size does not fit all

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.

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Publication Details

Journal
Journal of Stroke and Cerebrovascular Diseases
Published
2025-04-17
DOI
https://doi.org/10.1016/j.jstrokecerebrovasdis.2025.108323
Citations
1
Primary Topic
Cardiovascular Syncope and Autonomic Disorders
Type
article
Field-Weighted Citation Impact
2.01

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article

Pre-hospital LVO detection: One size does not fit all

Soren D. Konecky, Grayson L. Baird, Michael T. Mullen, Ryan McTaggart et al.
1 citations
Journal of Stroke and Cerebrovascular Diseases
Cardiovascular Syncope and Autonomic Disorders
2.01
article

Pre-hospital LVO detection: One size does not fit all

Soren D. Konecky, Grayson L. Baird, Michael T. Mullen, Ryan McTaggart, Christopher G. Favilla, Tyler McCardell
article en
1 citations

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.

Journal of Stroke and Cerebrovascular DiseasesVol. 34(7)
Brown University (US), OpenAI (United States) (US), University of Pennsylvania (US), Temple University (US)
National Institutes of Health
Gender equality
Openalex Percentile: Top 17%
Cardiovascular Syncope and Autonomic Disorders
2.01
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Pre-hospital LVO detection: One size does not fit all — Soren D. Konecky, Grayson L. Baird, et al. · Journal of Stroke and Cerebrovascular Diseases (2025) | TGRS Research Map | TGRS