Additional Predictors of Stroke and Transient Ischaemic Attack in BEFAST Positive Patients in Out-of-hours Emergency Primary Care

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2024 Sep 20

PMID 39302942

Authors

Florien S van Royen

Geert-Jan Geersing

Daphne C Erkelens

Mathe Delissen

Jorn V F Rutten

Dorien L Zwart

Maarten van Smeden

Frans H Rutten

Sander van Doorn

Affiliations

Soon will be listed here.

Abstract

Introduction: In patients suspected of stroke or transient ischemic attack (TIA), rapid triaging is imperative to improve clinical outcomes. For this purpose, balance-eye-face-arm-speech-time (BEFAST) items are used in out-of-hours primary care (OHS-PC). We explored the risk of stroke and TIA among BEFAST positive patients calling to the OHS-PC, and assessed whether additional predictors could improve risk stratification.

Methods: This is a cross-sectional study of retrospectively gathered routine care data from telephone triage tape-recordings of patients calling the OHS-PC with neurological deficit symptoms, classified as BEFAST positive. Four models-with the predictors age, sex, a history of cardiovascular or cerebrovascular disease, and cardiovascular risk factors-were fitted using logistic regression to predict the outcome stroke or TIA. Likelihood ratio testing was used to select the best model, which was subsequently internally validated.

Results: The risk of stroke or TIA diagnosis was 52% among 1,289 BEFAST positive patients, median age 72 years, 56% female sex. Of patients with the outcome stroke/TIA, 24% received a low urgency allocation, while 92% had signs or symptoms when calling. Only the addition of age and sex improved predicting stroke or TIA (internally validated c-statistic 0.72, 95%CI 0.69-0.75). The predicted risk of stroke or TIA remained below 20% in those aged below 40. Females aged 70 or over and males aged 55 or over, had a predicted risk above 50%.

Discussion: Urgency allocation appears to be suboptimal in BEFAST positive patients calling the OHS-PC. Risk stratification could be improved in this setting by adding age and sex.

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