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. 2021 Sep;23(3):443-448.
doi: 10.5853/jos.2021.01312. Epub 2021 Sep 30.

A Bayesian Framework to Optimize Performance of Pre-Hospital Stroke Triage Scales

Mayank Goyal  1   2   3 , Johanna M Ospel  4 , Beom Joon Kim  5 , Nima Kashani  1 , Martijne H C Duvekot  6   7 , Bob Roozenbeek  6 , Aravind Ganesh  2   3
Affiliations

A Bayesian Framework to Optimize Performance of Pre-Hospital Stroke Triage Scales

Mayank Goyal et al. J Stroke. 2021 Sep.
No abstract available

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Figures

Figure 1.
Figure 1.
The occurrence of vessel occlusions in patients with ischemic stroke presenting with different degrees of stroke severity per the National Institutes of Health Stroke Scale (NIHSS) score. (A) The proportion of patients with and without large vessel occlusion (LVO), in each NIHSS score category, among all patients undergoing computed tomography or magnetic resonance angiography. These graphs are based on re-analyses of data reported from the Bernese Stroke Database [11]. (B) The estimated number of patients with ischemic stroke in the USA, seeking emergency medical attention each year, who are likely to have LVO for a given NIHSS score. These estimates were obtained by applying published data from the Bernese Stroke Database to stroke statistics from the American Heart Association [4]. In (B), the corresponding NIHSS score for different cut-offs on the Los Angeles Motor Scale (LAMS) are also shown, as roughly estimated from work by the Field Administration of Stroke Therapy–Magnesium (FAST-MAG) investigators on the distribution of vessel occlusions for different scores on the LAMS and NIHSS..
Figure 2.
Figure 2.
Pre- and post-test probability of large vessel occlusion (LVO) when using the Los Angeles Motor Scale (LAMS) with its typical cut-off of LAMS ≥4. Of course, the National Institutes of Health Stroke Scale (NIHSS) is not typically determined in the pre-hospital setting, but we show it here as a quantification of the manifest stroke severity observed by the pre-hospital team. We also show what the post-test probabilities would be with hypothetical pre-hospital technologies that achieve a slightly better positive likelihood ratio (+LR) of 3.00 (vs. 2.17 for LAMS) and a much better +LR of 19.00, including at the mildest end of the severity spectrum, to which current scales are likely insensitive. Such technologies would be especially valuable if ongoing trials of endovascular therapy (EVT) in low-NIHSS populations are positive.
See this image and copyright information in PMC

References

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