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The Impact of Tilburg Frailty on Poststroke Fatigue in First-Ever Stroke Patients: A Cross-Sectional Study With
Chuan-Bang Chen1, Xiao-Xue Wang2, Shao-Rui Bao3
1Department of Rehabilitation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Background:
Poststroke fatigue (PSF) and frailty share substantial overlap in their manifestations, yet previous research has yielded conflicting results due to the use of heterogeneous frailty assessment tools.
Objective:
To evaluate the independent impact of frailty on PSF using a unified measurement system (Tilburg Frailty Indicator, TFI) while controlling for modified Rankin Scale (mRS), National Institutes of Health Stroke Scale (NIHSS), anxiety, depression, and other confounding factors.
Methods:
A single-center cross-sectional study was conducted with 320 first-ever stroke patients. Frailty was assessed using the TFI, fatigue with the Fatigue Severity Scale (FSS), and psychological symptoms with the Hospital Anxiety and Depression Scale (HADS). Both linear regression and logistic regression models were employed, with quantile regression for robustness testing.
Results:
TFI total score demonstrated a strong positive correlation with FSS scores (ρ = 0.85, p < 0.001). Here, frailty (independent variable) was captured by TFI and poststroke fatigue (dependent variable) by FSS. In multivariable regression analysis, TFI (β = 0.42, 95% CI: 0.35-0.49), HADS-A (β = 0.28, 95% CI: 0.21-0.35), and NIHSS (β = 0.18, 95% CI: 0.11-0.25) emerged as significant predictors of PSF (all p < 0.001). The combined model explained 74.2% of variance in fatigue scores.
Conclusion:
The use of the unified frailty assessment tool (TFI) resolves previous conflicting findings and confirms that frailty is a strong independent predictor of PSF. Routine frailty assessment using the TFI should be incorporated into poststroke care to identify patients at high risk for fatigue and guide targeted interventions.
