Abstract WMP96: The Iscore Predicts Clinical Response To Thrombolysis: Results From VISTA
Bibliographic record
Abstract
Background: The iScore is a validated tool developed to estimate the risk of death and functional outcomes early after an acute ischemic stroke. It includes demographics, stroke severity and subtype, comorbidities, pre-stroke status, and glucose on admission. Objective: To determine the ability of the iScore to predict the clinical response after iv thrombolysis (tPA) in the Virtual International Stroke Trials Archive (VISTA). Methods: We applied the iScore (www.sorcan.ca/iscore) to patients with an acute ischemic stroke within the VISTA collaboration. We explored the association between the iScore (as continuous and binary [<200 and ≥200] measures) and the outcomes of interest. Outcome Measures: The primary outcome was death or disability at 90 days defined as a modified Rankin scale (mRS) 4-to-6. Secondary outcomes included death at 90 days and favorable outcome (mRS 0-2). Results: Among 7140 patients with an acute ischemic stroke, 2732 (38.5%) received tPA and 712 (10%) had an iScore ≥200. Patients with higher iScore had worse clinical outcomes (p<0.0001 for all outcomes; c-statistics 0.777 for mRS0-6 and 0.748 for death at 90 days). Overall, an iScore ≥200 was associated with nine fold higher risk of death or disability at 90 days (OR 9.41, 95%CI 7.00-12.6). Similar trends were observed for secondary outcomes (Figure). tPA administration in stroke patients with an iScore≥200 was associated with a lower risk of death or disability at 90 days (OR 0.48; 95%CI 0.32-0.72). There was a direct interaction between the iScore and tPA for both death or disability and death alone at 90 days (p-value for the interaction <0.001). Conclusion: The iScore is a useful tool that can be used to estimate clinical outcomes after tPA. Although outcomes were poorer for the high-risk group (iScore≥200), the benefits of tPA in this group were greater than for low-risk patients. Figure
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".