Related Experiment Video
Updated: Jun 15, 2026
Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
Published on: February 12, 2011
The precision by the Face Arm Speech Time (FAST) algorithm in stroke capture, sex and age differences: a stroke
Guri Hagberg1,2, Haakon Ihle-Hansen3, Tamar Abzhandadze1,4
1Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Goteborg, Sweden.
Background:
The shift towards milder strokes and studies suggesting that stroke symptoms vary by age and sex may challenge the Face-Arm-Speech Time (FAST) coverage. We aimed to study the proportion of stroke cases admitted with FAST symptoms, sex and age differences in FAST presentation and explore any additional advantage of including new item(s) from the National Institute of Health Stroke Scale (NIHSS) to the FAST algorithm.
Methods:
This registry-based study included patients admitted with acute stroke to Sahlgrenska University Hospital (November 2014 to June 2019) with NIHSS items at admission. FAST symptoms were extracted from the NIHSS at admission, and sex and age differences were explored using descriptive statistics.
Results:
Of 5022 patients, 46% were women. Median NIHSS at admission for women was (2 (8-0) and for men 2 (7-0)). In total, 2972 (59%) had at least one FAST symptom, with no sex difference (p=0.22). No sex or age differences were found in FAST coverage when stratifying for stroke severity. 52% suffered mild strokes, whereas 30% had FAST symptoms. The most frequent focal NIHSS items not included in FAST were sensory (29%) and visual field (25%) and adding these or both in modified FAST algorithms led to a slight increase in strokes captured by the algorithms (59%-67%), without providing enhanced prognostic information.
Conclusions:
60% had at least one FAST symptom at admission, only 30% in mild strokes, with no sex or age difference. Adding new items from the NIHSS to the FAST algorithm led only to a slight increase in strokes captured.
