Abstract WP70: Do Stroke Patients benefit from Thrombolysis despite Contraindications or Warnings?
Bibliographic record
Abstract
Background&Purpose: Intravenous thrombolysis with alteplase is approved for acute ischemic stroke but its use is limited by numerous contraindications and warnings arising from trial selection criteria and/or expert opinions. We examined outcomes from alteplase-treated versus untreated patients from neuroprotectant trials held within a trials archive called VISTA, according to presence or absence of specified contraindications and warnings. Subjects&Methods: We analysed 90 day modified Rankin scale across the whole distribution of scores using the Cochran-Mantel-Haenszel (CMH) test, with adjustment for age and baseline NIHSS, followed by proportional odds logistic regression analysis to estimate the odds ratios for preferred outcome. We gathered data from 9613 ischemic stroke patients, of whom 4793 patients (49.6%; 1281 thrombolysed, 3512 non-thrombolysed) had at least one known contraindication, and 6231 (64.8%; 1946 thrombolysed, 4285 non-thrombolysed) had at least one known contraindication or warning for treatment with alteplase. Results: A broad trend of more favourable 3-month outcome associated with alteplase treatment in various subgroups of patients with contraindications or warnings was evident; eg in patients aged >80 (n=1805; OR 1.40; 95% CI 1.14-1.70; p <0.001), with combined history of prior stroke and diabetes (n=672; OR 1.50; 1.03-2.18; p=0.03), on prior single antiplatelet agent (n=1626; OR 1.42; 1.19-1.70; p 180 mg/dl (n=879; OR 1.50; 1.15-1.97; p=0.002) or with major early computed tomographic changes (n=176; OR 2.46; 1.28-4.72; p=0.01). Results were inconclusive after mild stroke, NIHSS<6 (n=381; OR 0.97; 0.50-1.87; p=0.76). Conclusions: This retrospective analysis of various contraindications and warnings provides reassurance about benefits and risks of intravenous alteplase treatment in common clinical situations.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".