Dynamic Evolution of Diffusion-Weighted Imaging Lesions in Patients With Minor Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Diffusion-weighted imaging (DWI) lesion volume on magnetic resonance imaging is increasingly being used as a surrogate outcome measure in clinical trials. We aimed to characterize the evolution of DWI lesion volumes within 30 days of symptom onset after minor stroke. METHODS: Minor stroke patients with DWI lesions on magnetic resonance imaging within 48 hours of symptom onset were prospectively followed with magnetic resonance imaging brain scan at 7 and 30 days. Change in the lesion volume was defined as the difference between day 30 Fluid-Attenuated Inversion Recovery and baseline DWI lesion volumes. RESULTS: Three patterns of infarct evolution were observed: reduction (72 [63%]), no change (26 [23%]), and growth (16 [14%]). Patients with infarct reduction at 30 days had larger baseline DWI lesion volumes (2.5 [0.9-8.5] mL) than those with stable infarcts (0.5 [0.3-0.9] mL; P=0.01). Complete DWI reversal at day 30, was seen in only 6 (5.3%) patients. CONCLUSIONS: The most common pattern of infarct evolution in patients with minor stroke is a reduction in volume, but complete resolution is uncommon.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".