tPA use for Stroke in the Registry of the Canadian Stroke Network
Bibliographic record
Abstract
BACKGROUND: Thrombolytic therapy with recombinant tissue plasminogen activator (tPA) has been shown to be cost-effective and safe. Thrombolysis for stroke with tPA is now a standard of care in North America. However, it is only used on a small percentage of patients. METHODS: The Registry of the Canadian Stroke Network was a consent-based stroke registry from 21 hospital sites across Canada. Using the thrombolysis data in phase 1 and 2 of the Registry, we sought to describe the use of stroke thrombolysis and its outcomes. RESULTS: A total of 4107 patients were diagnosed with ischemic stroke in phase 1 and 2 of the Registry, of which 8.9% were treated with tPA. In consented tPA patients, the method of tPA administration was 85.8% i.v. only, 9.0% ia only, and 5.2% i.v./i.a. combined. Patients had a median onset-to-treatment time of 167 minutes [IQR 140-188]. One quarter (25.5%) of eligible candidates (time from onset <150 minutes) were treated with tPA. Protocol violations occurred in 27.7% (67/242) of patients with 14.9% (10/67) mortality. Overall, in-hospital mortality was 11.6%. Lower Canadian Neurological Scale score and higher glucose level were predictive of mortality The symptomatic intracerebral hemorrhage (ICH) rate (phase 2 only) was 4.3%. The mean Stroke Impact Scale-16 score at six months was 73.2, approximately equivalent to a modified Rankin scale score of 2. CONCLUSIONS: At selected hospitals in Canada, thrombolysis use is higher than previously reported rates. Thrombolysis continues to be safe and effective in Canada.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".