Prognosis of Lacunar Stroke Patients in Association with Leukoaraiosis
Bibliographic record
Abstract
P152 Background: Leukoaraiosis (LA) is a frequent finding on CT scans of patients with vascular risk factors and cerebrovascular disease, particularly in those with lacunar stroke. Both conditions appear to be linked by a common pathophysiological mechanism, namely small vessel disease. Objective: To characterize the relationship between lacunar stroke and LA, and to correlate with the risk of recurrent lacunar stroke. Patients & Methods: Baseline CT scans of NASCET participants with stroke as the index event were assessed for the presence and severity of LA by two readers independently unaware of clinical data. Results: Four groups based on the type of index stroke and on the presence of LA were formed: a) no lacunar stroke & no LA (n=437), 2) non lacunar stroke & LA (n=153), c) lacunar stroke & no LA (n=365), d) lacunar stroke & LA (n=76). Baseline characteristics different among the groups were: age >65 years (53, 76, 56, 63% respectively p<0.001), hyperlipidemia (30, 20, 37, 29% respectively p=0.002), smoking (42, 28, 41, 45, 42% respectively p=0.02) and degree of carotid stenosis 50–99% (52, 44, 45, 34% respectively p=0.01). Patients with LA were 2.9 times more likely to have multiple lacunes on CT (p=0.001). The risk of lacunar stroke at 5 years increased across the four groups (5, 8, 10 and 11% respectively p=0.02), after adjusting for all baseline characteristics. Conclusions: The presence of leukoaraiosis in lacunar stroke patients is associated with higher number of lacunar infarcts and strongly predicts the likelihood of developing a subsequent lacunar stroke. Our findings support the hypothesis that both conditions are caused by the same pathological entity in this patient population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".