Clinical Relevance of ‘Cap’ and ‘Track’ Development after Recent Small Subcortical Infarct
Bibliographic record
Abstract
Objective: After a recent small subcortical infarct (RSSI), some patients develop perilesional or remote hyperintensities (‘caps/tracks’) to the index infarct on T2/FLAIR MRI. However, their clinical relevance remains unclear. We investigated the clinicoradiological correlates of ‘caps/tracks’, and their impact on long-term outcomes following RSSI. Methods: We identified participants with lacunar stroke and MRI-confirmed RSSI from 3 prospective studies. At baseline, we collected risk factors, RSSI characteristics, small vessel disease (SVD) features, and microstructural integrity on diffusion imaging. Over 1-year, we repeated MRI and recorded ‘caps/tracks’ blinded to other data. We evaluated predictors of ‘caps/tracks’, and their association with 1-year functional (modified Rankin Scale score ≥2), mobility (Timed Up-and-Go), cognitive outcomes (Montreal Cognitive Assessment [MoCA] score <26), and recurrent cerebrovascular events (stroke/transient ischemic attack/incident infarct) using multivariable regression. Results: Among 185 participants, 93 (50.3%) developed ‘caps/tracks’ first detected at median 198 days after stroke. ‘Caps/tracks’ were independently predicted by baseline factors: larger RSSI, RSSI located in white matter, higher SVD score, and higher mean diffusivity in normal-appearing white matter (odds ratio [OR] [95% confidence interval {CI}], 1.15 [1.07–1.25], 6.01 [2.80–13.57], 1.77 [1.31–2.44], 1.42 [1.01–2.03]). At 1 year, ‘cap/track’ formation was associated with worse functional outcome (OR: 3.17, 95% CI: 1.28–8.22), slower gait speed (β: 0.13, 95% CI: 0.01–0.25), and recurrent cerebrovascular events (hazard ratio [HR]: 2.05, 95% CI: 1.05–4.02), but not with cognitive impairment. Interpretation: ‘Caps/tracks’ after RSSI are associated with worse clinical outcomes, and may reflect vulnerability to progressive SVD-related injury. Reducing ‘caps/tracks’ may offer early efficacy markers in trials aiming to improve outcome after lacunar stroke. ANN NEUROL 2025;97:942–955.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".