Abstract 151: Enlarged Perivascular Spaces in Lacunar Stroke Patients. The Secondary Prevention of Small Subcortical Stroked (SPS3) trial.
Bibliographic record
Abstract
Introduction: Enlarge perivascular spaces (EPVS) are a common finding on MRI with little known about their aetiology or clinical significance. Associations of EPVS with white matter hyperintensities (WMH) and cognitive impairment have been reported. We assessed the prevalence of EPVS in the basal ganglia (BG) and centrum semiovale (CS) and associations with vascular risk factors, MRI abnormalities, and cognitive impairment in a large cohort of MRI documented lacunar stroke patients. Methods: All SPS3 participants enrolled in North America (N=1632) were included in the cohort. MRIs were obtained at the time of index stroke. We graded severity of EPVS on T2 in each of the right and left BG and CS as: <10, 11-20, or 20+. We assessed relationships between maximum (max) BG and CS scores and patient demographics, number of subcortical infarcts, WMH, and cognitive impairment using chi-square tests and ANOVA. Logistic regression was used to identify independent associations between max score in the BG or CS (<10 vs. 11+ points) and these factors. Results: Of the 1632 MRIs, 1172 had T2-imaging available. EPVS was symmetrical in right and left sides of BG and of CS so max score in each area were used for analyses. In 42% of BG and 69% of CS, the max number of unilateral EPVS was ≥11. Patients with more EPVS in the BG were older (mean 59 vs. 63 vs. 70 years, p < 0.001), had hypertension (75% vs. 84% vs. 86% p < 0.001), and lower eGFR (mean 83 vs. 80 vs. 74 ml/min/1.73m 2 , p = 0.006). More EPVS in the BG were associated with WMH severity as measured by Age Related White Matter Changes total score (median 3 vs. 6 vs. 8, p < 0.001). Patients with more EPVS in the BG more often had multiple infarcts (11% vs. 19% vs. 29%, p<0.001). All findings were similar in the CS. Age (OR 1.9 per each 10 years, 95% CI 1.7-2.1), history of hypertension (OR 1.7, 95% CI 1.2-2.3) and multiple infarcts (OR 2.4, 95% CI 1.7-3.4) were independently associated with a maximum unilateral EPVS score of 2+ in the BG. Mild cognitive impairment was not associated with EPVS in BG (p=0.3) or CS (p=0.5). Conclusions: In this well-defined large cohort of lacunar stroke patients, BG EPVS were associated with age, hypertension and multiple infarcts. These findings suggest that BG EPVS share similar risk factors with lacunar stroke and may be a marker for small vessel disease. Unexpectedly, EPVS were not associated with cognitive impairment.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".