Abstract
Background
During the helicopter transportation of patients suspected of large vessel occlusion
(LVO), an accurate and rapid decision-making process is required.
Aims
We attempted to create an algorithm for the pre-hospital diagnosis of the presence
of LVO in patients suspected of stroke using data from patients transported urgently
by helicopter.
Methods
One hundred and sixty-five patients transported by helicopter were divided into two
subgroups: a training dataset and a validation dataset. We extracted clinical information
obtained on site, the unadjusted score of the National Institutes of Health Stroke
Scale, and previously reported pre-hospital scales as an LVO screen. On the basis
of the analyses of these factors, an algorithm was devised to predict the presence
of LVO and its predictive accuracy was evaluated using the validation dataset.
Results
Ischemic stroke with LVO was diagnosed in 36 out of 121 cases (29.8%) in the training
dataset and in 10 out of 44 cases (22.7%) in the validation dataset. Combining five
factors (conjugate deviation, upper limb paresis, atrial fibrillation, Japan Coma
Scale ≥ 200, and systolic blood pressure ≥ 180), an algorithm was created to classify
cases into six groups with different likelihoods of LVO presence. The algorithm predicted
correctly 6 out of 10 cases in the validation dataset. Furthermore, it definitively
ruled out 17 out of 34 cases in the validation dataset.
Conclusions
Using the newly created algorithm, emergency staff could easily and accurately distinguish
patients suitable for urgent endovascular thrombectomy from patients with non-LVO
or stroke mimics.
Key Words
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Article Info
Publication History
Published online: October 31, 2020
Accepted:
October 15,
2020
Received in revised form:
October 13,
2020
Received:
August 17,
2020
Identification
DOI: https://doi.org/10.1016/j.jstrokecerebrovasdis.2020.105416
Copyright
© 2020 Elsevier Inc. All rights reserved.
