ArticleBrain sciences2023
Personalized Biomarkers and Neuropsychological Status Can Predict Post-Stroke Fatigue.
Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Neuroimaging correlates of post-stroke fatigue: A systematic review and meta-analysis.International journal of stroke : official journal of the International Stroke Society · 2023Pooled it
- Article
- Visualizing fatigue mechanisms in non-communicable diseases: an integrative approach with multi-omics and machine learning.BMC medical informatics and decision making · 2025Article
- Duration and Efficiency of Combined versus Isolated Aerobic Training Interventions in Post-Stroke Cognition: A Systematic Review.Portuguese journal of public health · 2024Review
- Post-stroke fatigue: a review of development, prevalence, predisposing factors, measurements, and treatments.Frontiers in neurology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Post-stroke fatigue (PSF) is a common complication of stroke that has a negative impact on prognosis and recovery. We aimed to investigate the relationship between PSF and demographics, mood disorders, sleep disorders, and other clinical characteristics of patients with stroke. In this exploratory cross-sectional study, we collected data on sociodemographic characteristics, biological indicators, and imaging features and evaluated patients using neuropsychological scales. Patients were assessed using the Fatigue Severity Scale, Hamilton Depression Rating Scale, Hamilton Anxiety Scale, and Pittsburgh Sleep Quality Index. Magnetic resonance imaging scans were primarily used to evaluate infarctions and white matter lesions. The correlation between the PSF of patients with stroke and clinical indicators was obtained by logistic regression analysis and power analysis. We observed an independent association between fatigue severity and female sex (odds ratio [OR], 2.12; 95% confidence interval [CI], 1.14-3.94), depressive state (OR, 1.50; 95% CI, 1.01-1.73), and sleep disorders (OR, 1.58; 95% CI, 1.01-1.98). High levels of blood glucose, serum uric acid, and homocysteine and low levels of serum triiodothyronine were strongly associated with poor functional outcomes in patients with stroke. Further studies are needed to elucidate how specific structural lesions and anxiety symptoms are related to early PSF.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.