The precision by the Face Arm Speech Time (FAST) algorithm in stroke capture, sex and age differences: a stroke...

Area of Science:

• Neurology
• Public Health

Background:

• Stroke symptom presentation varies by age and sex, potentially impacting the effectiveness of the Face-Arm-Speech Time (FAST) screening tool.
• Milder stroke cases and evolving understanding of stroke symptoms necessitate re-evaluation of current diagnostic protocols.

Purpose of the Study:

• To determine the proportion of acute stroke admissions presenting with Face-Arm-Speech Time (FAST) symptoms.
• To investigate sex and age-based differences in FAST symptom presentation.
• To explore the potential benefit of incorporating additional National Institute of Health Stroke Scale (NIHSS) items into the FAST algorithm.

Main Methods:

• A registry-based study analyzed acute stroke patients admitted between November 2014 and June 2019.
• FAST symptoms were identified from National Institute of Health Stroke Scale (NIHSS) admission data.
• Descriptive statistics were used to explore sex and age differences in FAST symptom prevalence.

Main Results:

• Of 5022 patients, 59% presented with at least one FAST symptom, with no significant sex or age differences observed.
• Mild strokes (52% of cases) showed lower FAST symptom prevalence (30%).
• Incorporating sensory or visual field deficits (NIHSS items not in FAST) increased algorithm coverage from 59% to 67% but did not improve prognostic accuracy.

Conclusions:

• The Face-Arm-Speech Time (FAST) tool identifies stroke symptoms in a limited proportion of patients, especially those with mild strokes.
• While expanding the FAST criteria with additional National Institute of Health Stroke Scale (NIHSS) items can slightly increase detection rates, it does not enhance prognostic information.