Topography and Predictitve Value of Enlarged Perivascular Spaces in Patients with Cognitive Impairment beyond Aneurysmal Subarachnoid Hemorrhage
Bibliographic record
Abstract
Abstract Background To explore the correlation between the topography of EPVS and cognitive impairment after aSAH. Method Patients clinically diagnosed as aSAH by DSA and CT; Head magnetic resonance imaging was performed between 1 week and 1 month after onset, combined with clinical and neuroimaging variables to assess the incidence of hydrocephalus and delayed cerebral ischemia after aneurystic subarachnoid hemorrhage. Follow‐up was performed at 3 months, and the patients' prognosis and cognitive function were evaluated by mRS and the Montreal Cognitive Assesement (MoCA), respectively. The clinical characteristics of aSAH patients with EPVS <10 and EPVSV10 in basal ganglia and centrum semioval were compared, and a binary Logistic regression model was used to study the severity of EPVS and its correlation with DCI, subacute hydrocephalus, poor prognosis and cognitive impairment. Result BG‐EPVS predominance pattern (BG‐EPVS > CSO‐EPVS) was more common in the aSAH group (53.8%) than in other primary SAH patients without aneurysm(15.8%). A total of 159 patients completed 3‐month MoCA assessment, of which 63 (39.6%) were diagnosed with cognitive impairment (MoCA<22). EPVS >10 (no matter CSO or BG) was associated with unfavorable functional outcomes at 3 months. BG‐EPVS >10 linked to subacute hydrocephalus and DCI, but not with cognitive impairment after adjusting for established predictors. In contrast, CSO‐EPVS>10 predicted worse cognitive function after adjustment for established variables. Conclusion CSO‐EPVS is associated with cognitive impair beyond aSAH, but not with subacute hydrocephalus and DCI, suggesting distinct lymphatic drainage and mechanism after an attack of aSAH.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".