Cognition mediates the relationship between white matter hyperintensity and motor function in patients with cerebral small vessel disease: a cross-sectional study
Bibliographic record
Abstract
Background: White matter hyperintensity (WMH) is a common neuroimaging marker of cerebral small vessel disease (SVD) and a critical independent predictor of motor dysfunction, which increases the risk of disability, morbidity, and mortality. However, the mechanism underlying the relationship between WMH and motor function has not yet been fully clarified. It was hypothesized that cognitive impairment mediates the relationship between WMH and motor dysfunction in patients with SVD, which were considered predictor and outcome variables, respectively. Methods: A total of 221 patients with SVD were enrolled in this study, and their magnetic resonance imaging (MRI), neuropsychological, and motor function data were collected. The MRI data were visually assessed to determine the WMH burden using the Fazekas scale. Cognition was evaluated using the Montreal Cognitive Assessment (MoCA). Motor function was assessed using the Tinetti Gait and Balance Scale and the Short Physical Performance Battery (SPPB). Finally, a bootstrap analysis was performed to determine whether cognition mediated the relationship between WMH and motor function. Results: Of all the patients, 30.3% had mild WMH, 37.6% had moderate WMH, and 32.1% had severe WMH. Patients' cognition and motor function decreased as the WMH burden increased (P<0.01). The MoCA scores were associated with the Tinetti scale (r=0.545, P<0.01) and SPPB scores (r=0.365, P<0.01). Finally, multi-categorical mediation models confirmed our research hypothesis; the coefficients for the indirect effects had 95% confidence intervals (CIs) that excluded zero, indicating statistically significant mediation effects. Conclusions: WMH is associated with motor dysfunction, and this association is mediated by cognition in patients with SVD. This finding highlights the importance of early interventions targeting cognitive function to reduce the risk of motor dysfunction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".