Altered brain glymphatic function on diffusion-tensor MRI in patients with spontaneous intracerebral hemorrhage: an exploratory study
Bibliographic record
Abstract
Objectives To investigate the function of the glymphatic system (GS) and its association with neuropsychological tests in spontaneous intracerebral hemorrhage (sICH) by diffusion tensor imaging analysis along the perivascular space (DTI-ALPS). Methods This retrospective study included 58 patients with sICH and 63 age- and sex-matched healthy controls (HCs). Partial correlation analyses were performed to examine the relationships between the DTI-ALPS index and radiological as well as clinical data. Mediation analyses were performed to explore the mediating role of the grey matter proportion (GM%) in the relationship between DTI-ALPS index and Montreal Cognitive Assessment (MoCA) score. Results Significantly lower DTI-ALPS index values were observed in sICH compared with HCs (FDR- p < 0.001). In the acute-subacute sICH group, the ALPS index was significantly correlated with hematoma volume ( r = −0.572, FDR- p = 0.031). In the chronic sICH group, the ALPS index was significantly correlated with MoCA scores ( r = 0.425, FDR- p = 0.014). In chronic sICH groups, GM% served as a significant mediator in the relationship between the DTI-ALPS index and MoCA scores (indirect effects β = 4.925, 95%CI: 0.028, 11.841). The ALPS index was identified as an independent prognostic indicator for unfavorable outcomes in sICH ( β = −9.851, p = 0.018). Conclusion Our study demonstrated that the DTI-ALPS index decreased in sICH patients, suggesting potential functional impairment of the lymphoid system. Additionally, the DTI-ALPS index served as an independent predictor of poor 90-day prognosis. In the acute-subacute stage of sICH, the DTI-ALPS index had negative correlation with hematoma volume. In the chronic sICH group, the GM% partially mediated the relationship between the GS and cognitive function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".