B.1 Safety and effectiveness of intravenous thrombolysis for acute stroke patients in the Manitoba TeleStroke Program
Bibliographic record
Abstract
Background: TeleStroke can improve access to stroke care in rural areas. We aim to evaluate the safety and effectiveness of intravenous thrombolysis in our TeleStroke system. Methods: The Manitoba TeleStroke program was rolled out across 7 sites between November 2014 and January 2019. We retrospectively analyzed prospectively collected consecutive acute stroke patients’ data in this duration. The primary outcome was safety and effectiveness measured in terms of 90-day modified Rankin score (mRs). The number of acute ischemic stroke (AIS) patients receiving thrombolysis and endovascular thrombectomy [EVT] and process metrics were also analyzed. R/RStudio version-4.3.2 was used (p<0.05). Results: Of the 1,748 TeleStroke patients (age 71 years [IQR 58-81], female 810[46.3%]), 696 were identified as AIS. Of these, 265(38.1%) received thrombolysis and 48(6.9%) EVT. Ninety-day mortality was 53(20.0%) among those receiving thrombolysis and 117(44.2%) had a favorable outcome (mRs ≤2). Of those who received intravenous thrombolysis, 9 patients (4.2%) were found to have symptomatic intracranial hemorrhage. The median last-seen-normal (LSN)-to-door was121 minutes and the median door-to-needle, 55 minutes. Conclusions: Intravenous thrombolysis was found to be effective with acceptable safety. TeleStroke improved overall access to stroke care and played an important role in identifying AIS patients eligible for thrombolysis and EVT.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".