Classifying post-stroke fatigue: Optimal cut-off on the Fatigue Assessment Scale

Area of Science:

• Neurology
• Rehabilitation Medicine
• Psychometrics

Background:

• Post-stroke fatigue significantly impacts patient independence and quality of life.
• The Fatigue Assessment Scale (FAS) is a validated tool for screening fatigue after stroke.
• Currently, there is no established cut-off score for the FAS to classify post-stroke fatigue.

Purpose of the Study:

• To determine the optimal cut-off score for the Fatigue Assessment Scale (FAS) to accurately classify post-stroke fatigue.
• To evaluate the predictive validity of the FAS score against a defined criterion standard for fatigue.

Main Methods:

• Retrospective analysis of two independent datasets (2015 and 2007 studies).
• Evaluation of the predictive validity of FAS scores against a case definition of fatigue.
• Calculation of Area Under the Curve (AUC), sensitivity, and specificity for optimal cut-off determination.

Main Results:

• In the 2015 dataset (n=126), an optimal FAS cut-off of ≥24 yielded an AUC of 0.78, sensitivity of 0.82, and specificity of 0.66.
• Validation in the 2007 dataset (n=52) showed an AUC of 0.83, with the ≥24 cut-off providing sensitivity of 0.84 and specificity of 0.67.
• A shorter version, FAS-3, also demonstrated good validity with an AUC of 0.81 and optimal cut-off of ≥8.

Conclusions:

• A proposed cut-off score of ≥24 on the FAS is recommended for classifying post-stroke fatigue.
• This established cut-off represents a step towards standardized reporting of fatigue prevalence in stroke survivors.
• Further validation studies are warranted to confirm the utility of this cut-off.