Abstract TMP75: Atrial Fibrillation In Ischemic Stroke: Predicting Response To Thrombolysis And Clinical Outcomes
Bibliographic record
Abstract
Background: Atrial fibrillation (AF) increases the risk of stroke and is associated with poorer stroke outcomes. Few tools are available to evaluate clinical outcomes and response to thrombolysis in stroke patients with AF. Methods: We applied the iScore ( www.sorcan.ca/iscore ), a validated risk score, to consecutive patients with an acute ischemic stroke participating in the RCSN. The main outcome was the proportion of patients with a favorable outcome (defined as a modified Rankin scale 0-2) at discharge after thrombolysis. Secondary outcomes included death at 30-days and at 1-year stratified by terciles of the iScore. Results: Among 12,686 patients with an acute ischemic stroke, 2,185 (17.2%) had AF. Among patients in the highest iScore tercile, those with AF had higher mortality at 30 days (34.7% vs.28.2%; p<.001) and at 1-year (53.6% vs.45.0%; p3) at discharge (RR 1.26, 95%CI 1.18-1.33; Figure 1) and an increased risk of intracranial hemorrhage (any type) (16.5% vs. 13.1%; RR 1.42, 95%CI 1.05-1.91) after thrombolysis. In the Poisson regression analysis, the benefit of tPA declined more rapidly at lower iScore values among AF patients than for others (p-value for interaction <0.001; Figure 2). Conclusion: The iScore predicted a differential response after tPA between patients with and without AF. Stroke patients with AF have higher mortality, greater risk of ICH, and reduced response to thrombolysis compared with non-AF patients for a given high iScore. Figure 1 Figure 2
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".