MR perfusion lesions after TIA or minor stroke are associated with new infarction at 7 days
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationship between acute perfusion-weighted imaging (PWI) lesions occurring within the first hours after a TIA or a minor brain infarction (BI) and the incidence of new BI detected on a systematic MRI at 1 week. METHODS: Consecutive patients who experienced a TIA or BI with a neurologic deficit that lasted <24 hours, did not receive any revascularization therapy (thrombolysis/thrombectomy), and underwent DWI/PWI at baseline and fluid-attenuated inversion recovery (FLAIR)/DWI 1 week after symptom onset were enrolled. Investigators blinded to clinical information independently assessed the presence of acute ischemic lesions on baseline DWI/PWI and follow-up DWI and FLAIR. Baseline and follow-up MRIs were then compared to determine the occurrence and location of new infarctions. RESULTS: Sixty-four patients met the inclusion criteria. Median (IQR) ABCD2 score was 4 (3-5). Median delay from onset to baseline and follow-up MRI was 5 (2-10) hours and 6 (5-7) days, respectively. MRI revealed an acute ischemic lesion on DWI and/or PWI in 38 patients. Nine patients (14%) had a new infarction on follow-up MRI. Each had a PWI and 4 had a DWI lesion on baseline MRI. All new BIs except one were asymptomatic and in the same location as the acute PWI lesion. CONCLUSIONS: Our results showed that 30% of the acute focal PWI lesions detected after a TIA are associated with a new BI at 1 week. Those new BIs may result from the progression of the initial ischemic injury.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".