Post-stroke cognitive impairment and fatigue in patients with white matter hyperintensities. A prospective cohort study
Bibliographic record
Abstract
Background: Cognitive impairment, depression, and fatigue are often neglected symptoms post-stroke. This study aimed to identify how white matter hyperintensity (WMH), a marker for cerebral small vessel disease (CSVD), is associated with post-stroke cognitive impairment, fatigue, and depression. Methods: This prospective cohort study included participants admitted with stroke or transient ischemic attack. Participants were classified into two groups based on WMH on magnetic resonance imaging (MRI) using the Fazekas scale (0-1: no CSVD, 2-3: CSVD). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), Symbol Digit Modalities Test (SDMT), and Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) in the acute stroke phase (≤14 days) and three months post-stroke. Fatigue and depression were evaluated with the Fatigue Severity Scale (FSS) and the Beck Depression Inventory-II (BDI-II). Results: = 0.011) independently of age. There was no association between the Fazekas score and MoCA or BDI-II. Conclusion: These findings highlight the association between WMH, lower processing speed on the SDMT test in the acute stroke phase, and higher fatigue post-stroke. We propose that the WMH burden should be considered in all patients admitted with stroke or transient ischemic attack to identify those at increased risk of post-stroke cognitive impairment and fatigue.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".