Association between white matter integrity and lower limb motor impairment after stroke: A systematic review
Bibliographic record
Abstract
BACKGROUND: There is no clear consensus on the anatomical substrates required for recovery from lower limb (LL) impairment after stroke. Knowledge of biomarkers, such as white matter integrity (WMI), could fill this knowledge gap. OBJECTIVES: To analyze the associations between WMI of the corticospinal tract (CST) and corticoreticulospinal pathway (CRP) and LL motor impairment after stroke, in terms of synergistic control and muscle strength. It also explores whether any associations depend on time post-stroke. METHODS: In April 2023, PubMed, Web of Science, and Scopus databases were systematically searched for studies associating WMI of the CST and CRP and LL motor impairment after stroke. Risk of bias was assessed using the Newcastle-Ottawa Quality Assessment Scales. RESULTS: Nineteen studies were included, 15 about the association between CST and motor impairment, and 4 concerning CST and CRP. Associations were consistently found between higher WMI of the CST and greater muscle strength, but not with synergistic control. There were no clear associations between WMI of the CRP and muscle strength, and associations could not be analyzed for synergistic control. The results could not determine whether the associations are time dependent. CONCLUSIONS: The results of this review supported using WMI of the CST to understand LL muscle strength after stroke. However, the same cannot be said for LL synergistic control due to the small number of studies. There was no clear evidence of an association between WMI of the CRP and LL muscle strength or synergistic control due to mixed results or a lack of studies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.001 |
| 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".