Statin Therapy Does Not Affect the Radiographic and Clinical Profile of Patients with TIA and Minor Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Acute statin therapy improves neurologic outcome and diminishes infarct growth in animal models of stroke. Clinical studies suggest that premorbid and early statin use is associated with improved outcome after major stroke. We studied the association between statin therapy and radiographic and clinical outcomes in patients with high-risk TIA and minor stroke. MATERIALS AND METHODS: Patients with high-risk TIA and minor stroke (NIHSS ≤3) were prospectively enrolled within 24 hours of symptom onset. Patients were followed clinically for 3 months, and a subset had a repeat MR imaging at 90 days. RESULTS: Of 418 patients, 23% were prescribed statins before their stroke. Statins were continued in 20% and initiated in 42%. Patients on prior statin therapy were older and more hypertensive, treated with aspirin, and more likely to have symptomatic carotid disease compared with those not on statin. Adjusting for these differences, prior statin treatment was not associated with DWI positivity (adjusted OR = 1.3; 95% CI, 0.77-2.1; P = .32) or smaller median baseline infarct volume, 1.1 mL (interquartile range = 4) versus 1 mL (interquartile range = 2.5; P = .56). Early or continued treatment with statins did not improve the risk of clinical deterioration (adjusted OR = 0.66; 95% CI, 0.27-1.6; P = .35) or poor functional outcome at 3 months (adjusted OR = 0.66; 95% CI, 0.35-1.24; P = .19). CONCLUSIONS: Prestroke or early-stroke statin therapy was not associated with a reduction in the number of DWI lesions, infarct volume, or improved clinical or functional outcome at 3 months. The effect of acute statin treatment in patients with ischemic stroke/TIA remains unclear and needs further investigation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".