Imaging markers of small vessel disease and brain frailty, and outcomes in acute stroke
Bibliographic record
Abstract
OBJECTIVE: To assess the association of baseline imaging markers of cerebral small vessel disease (SVD) and brain frailty with clinical outcome after acute stroke in the Efficacy of Nitric Oxide in Stroke (ENOS) trial. METHODS: ENOS randomized 4,011 patients with acute stroke (<48 hours of onset) to transdermal glyceryl trinitrate (GTN) or no GTN for 7 days. The primary outcome was functional outcome (modified Rankin Scale [mRS] score) at day 90. Cognition was assessed via telephone at day 90. Stroke syndrome was classified with the Oxfordshire Community Stroke Project classification. Brain imaging was adjudicated masked to clinical information and treatment and assessed SVD (leukoaraiosis, old lacunar infarcts/lacunes, atrophy) and brain frailty (leukoaraiosis, atrophy, old vascular lesions/infarcts). Analyses used ordinal logistic regression adjusted for prognostic variables. RESULTS: In all participants and those with lacunar syndrome (LACS; 1,397, 34.8%), baseline CT imaging features of SVD and brain frailty were common and independently associated with unfavorable shifts in mRS score at day 90 (all participants: SVD score odds ratio [OR] 1.15, 95% confidence interval [CI] 1.07-1.24; brain frailty score OR 1.25, 95% CI 1.17-1.34; those with LACS: SVD score OR 1.30, 95% CI 1.15-1.47, brain frailty score OR 1.28, 95% CI 1.14-1.44). Brain frailty was associated with worse cognitive scores at 90 days in all participants and in those with LACS. CONCLUSIONS: Baseline imaging features of SVD and brain frailty were common in lacunar stroke and all stroke, predicted worse prognosis after all acute stroke with a stronger effect in lacunar stroke, and may aid future clinical decision-making. IDENTIFIER: ISRCTN99414122.
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
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".