Stroke Sensitivity Calculation in Medical Emergency Calls and Factors Associated With Stroke Suspicion: A...

Sensitivity for stroke detection in emergency medical communication centers (EMCCs) varies widely. Few studies offer detailed insights into the out-of-hospital pathways of patients with stroke. This study explored the ability of EMCCs to detect strokes in medical emergency calls using an alternative method for estimating stroke sensitivity in EMCCs, thereby laying the foundation for developing artificial intelligence decision-support tools. It also identified factors associated with stroke recognition in medical emergency calls.

Overall, 1,164 patients with stroke in the catchment area of Bergen EMCC in 2018 and 2019 were included, and a data set from the EMCC was established manually and linked with data from the Norwegian Stroke Registry for analysis. Descriptive analysis and multivariable logistic regression were performed on data obtained from patients primarily assessed by the EMCC (n=838).

Stroke detection sensitivity was 76.8% in our study using the alternative method compared with 63.4% with traditional methods. Logistic regression analysis showed a positive association between stroke suspicion and ischemic strokes (odds ratio [OR]=0.317 [0.209 to 0.481]) and wake-up strokes (OR=1.716 [1.110 to 2.653]). Among Norwegian Stroke Registry symptoms, only aphasia/dysarthria was positively associated with stroke suspicion (OR=1.600 [1.087 to 2.353]), whereas leg paresis (OR=0.609 [0.390 to 0.953]) and vertigo (OR=0.376 [0.204 to 0.694]) were negatively associated.

We employed an alternative method for estimating EMCC stroke sensitivity and identified factors of particular interest for future EMCC research, relevant when developing and testing decision-support tools, such as artificial intelligence.