Cerebral Microbleeds and Cortical Superficial Siderosis in Patients Presenting With Minor Cerebrovascular Events
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Transient focal neurological episodes occur in cerebral amyloid angiopathy (CAA) and can mimic transient ischemic attack (TIA). Risk factors and outcomes of minor ischemic stroke or TIA might differ in patients with and without cerebral microbleeds (CMBs), including CAA-consistent lobar CMB. METHODS: Baseline magnetic resonance imaging (MRI) was analyzed for CMBs and cortical superficial siderosis in 416 patients in the prospective computed tomography and MRI in the CATCH study (Triage of TIA and Minor Cerebrovascular Events to Identify High Risk Patients). Clinical symptoms, baseline characteristics, recurrence, and 90-day modified Rankin Scale were prospectively collected. MRI white-matter hyperintensity was measured using the Fazekas scale. RESULTS: CMBs were detected in 65 (15.6%) and cortical superficial siderosis in 11 patients (2.6%). Lobar CMBs were present in 49 (11.8%). In multivariable logistic regression adjusted for risk factors and age, subcortical Fazekas score was associated with lobar CMB (odds ratio, 2.07; 95% confidence interval, 1.23-3.48; P=0.006). Forty-two patients (10.1%) had lobar-only CMBs with or without cortical superficial siderosis consistent with modified Boston criteria for possible/probable CAA. The possible/probable CAA pattern was not predictive of recurrent TIA (odds ratio, 0.42; 95% confidence interval, 0.05-3.31; P=0.41), stroke (odds ratio, 1.24; 95% confidence interval, 0.26-5.99; P=0.79), or 90-day modified Rankin Scale score ≥2 (odds ratio, 1.38; 95% confidence interval, 0.62-3.07; P=0.42). CONCLUSIONS: CMBs in TIA and minor stroke are moderately common but do not predict recurrence or 90-day outcome. CAA-related transient focal neurological episodes and TIA have overlapping clinical symptoms, suggesting that MRI may be needed for differentiation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".