Visibility of CT Early Ischemic Change Is Significantly Associated with Time from Stroke Onset to Baseline Scan beyond the First 3 Hours of Stroke Onset
Bibliographic record
Abstract
Background and Purpose Non-contrast brain computed tomography (NCCT) remains the most common imaging modality employed to select patients for thrombolytic therapy in acute ischemic stroke.The current study used the Alberta Stroke Program Early CT Score (ASPECTS) to identify early ischemic changes on brain NCCT imaging with the aim to investigate whether a relationship exists between time from symptoms onset to NCCT with the presence of early ischaemic change quantified by ASPECTS.Methods We studied 1,329 ischemic stroke patients who had NCCT within 8 hours of stroke onset.Patients were assessed to see if they had any ASPECTS lesion and if the rate of patients with a lesion increased with time using logistic regression.Results 30% patients had an ASPECTS <10 within the first 3 hours from symptom onset.Within the first 3 hours, the odds for a CT change (ASPECTS <10) per minute of time was 1.00 with 95% confidence interval (CI) (0.99 to 1.00) (P=0.266).After 3 hours, there was a significant increase in odds of ASPECTS <10 with increasing time.The odds of being ASPECTS positive increased 1% (odds ratio=1.01)per 1 minute of time with 95% CI (1.00 to 1.01) (P=0.002). ConclusionsWe have identified that prior to first 3 hours of stroke there was no effect of time on odds of CT ischemic change; after the first 3 hours of stroke the odds increased with increasing time to CT scan.The occurrence of early ischemic change may be a marker of time from stroke onset rather than severity.
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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 | 0.007 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".