Abstract T P39: Serial Alberta Stroke Program Early Ct Score (aspects) Is A Superior Predictor Of Outcomes With Iv Rtpa
Bibliographic record
Abstract
Background and purpose: The Alberta stroke program early computed tomography score (ASPECTS) on baseline imaging is known predictor of outcomes for acute ischemic stroke (AIS) patients. We looked at the change in ASPECTS at the baseline CT and 24hr CT in AIS patients treated with IV rTPA to determine if it can help predict 3 month functional outcomes. Methods: Consecutive AIS patients receiving IV-tPA within 4.5 hours of symptom-onset during 2010-2013 and underwent pre-treatment and day-2 CT were included ASPECTS at the baseline CT and 24hr CT were independently scored in all anterior circulation stroke patients who underwent IV rTPA within 4.5 hours of onset. ASPECTS at baseline, 24hrs and the serial change were analyzed. Results: 210 consecutive AIS patients were included. ROC curves for ASPECTS on the initial CT scan for MRS 0-1 was AUC 0.613, 95% CI 0.536-0.690, p=0.005, while ROC curves for ASPECTS on the 24hr CT scan for MRS0-1 was AUC 0.763 95% CI 0.699 - 0.828, p <0.001. ASPECTS on the 24hr CT was statistically significantly better able to predict outcomes compared to the initial CT (z= -2.936, p = 0.001). 28 out of 210 patients had an increase in ASPECTS by >3 with a 3-fold risk of worse outcomes (OR 3.572 95%CI 1.393- 9.156, p=0.08). Conclusion: ASPECT scores on 24hr CT have better prognostic ability compared to the baseline scan. Serial ASPECT scores are a viable surrogate predictor in AIS patients treated with IV rTPA.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".