Incident Infarcts in Patients With Stroke and Cerebral Small Vessel Disease
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Factors associated with cerebral small vessel disease (SVD) progression, including incident infarcts, are unclear. We aimed to determine the frequency of incident infarcts over 1 year after minor stroke and their relation to baseline SVD burden, vascular risks, and recurrent stroke and cognitive outcomes. METHODS: We recruited patients with lacunar or nondisabling cortical stroke. After diagnostic imaging, we repeated structural MRI at 3-6 monthly intervals for 12 months, visually assessing incident infarcts on diffusion-weighted imaging or FLAIR. We used logistic regression to determine associations of baseline vascular risks, SVD score, and index stroke subtype with subsequent incident infarcts. We assessed cognitive and functional outcomes at 1 year using Montreal Cognitive Assessment (MoCA) and modified Rankin scale (mRS), adjusting for baseline age, mRS, MoCA, premorbid intelligence, and SVD score. RESULTS: We recruited 229 participants, mean age 65.9 (SD 11.1). Over half of all participants, 131 of 229 (57.2%) had had an index lacunar stroke. From baseline to 1-year MRI, we detected 117 incident infarcts in n = 57/229 (24.8%) participants. Incident infarcts were mainly of the small subcortical (86/117 [73.5%] in n = 38/57 [66.7%]) vs cortical infarct subtype (n = 19/57 [33.3%]). N = 39/57 participants had incident infarcts at 1 visit; 18 of 57 at 2 or more visits; and 19 of 57 participants had multiple infarcts at a single visit. Only 7 of 117 incident infarcts corresponded temporally to clinical stroke syndromes. The baseline SVD score was the strongest predictor of incident infarcts (adjusted odds ratio [OR] 1.87, 95% CI 1.39-2.58), while mean arterial pressure was not associated. All participants with incident infarcts were prescribed an antiplatelet or anticoagulant. Lower 1-year MoCA was associated with lower baseline MoCA (β 0.47, 95% CI 0.33-0.61), lower premorbid intelligence, and older age. Higher 1-year mRS was associated with higher baseline mRS only (OR 5.57 [3.52-9.10]). Neither outcome was associated with incident infarcts. DISCUSSION: In the year after stroke in a population enriched for lacunar stroke, incident infarcts occurred in one-quarter and were associated with worse baseline SVD. Most incident infarcts detected on imaging did not correspond to clinical stroke/transient ischemic attack. Worse 1-year cognition and function were not associated with incident infarcts.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".