QUALITY OF CARE FOR ISCHEMIC STROKE IN QUEBECu2019S COMPREHENSIVE STROKE CENTERS BEFORE AND AFTER INITIATION OF A PROVINCIAL ACTION PLAN
Bibliographic record
Abstract
INTRODUCTION. In Quu00e9bec (Canada), an action plan to reorganize stroke care, to introduce thrombectomy and to promote best practices with a tool kit was initiated following a province-wide field evaluation in 2013-2014. We compare quality of care in comprehensive stroke centers before and after implementation of this initiative.METHODS. An evaluation of ischemic stroke treatment was conducted during two periods. Information from medical charts was entered into a centralized, secure website (REDCap). Results were compared for patients directly admitted to one of the four comprehensive stroke centers and treated with thrombolysis or thrombectomy from October 2016 to March 2017, versus those directly admitted to the same centers during the equivalent period in 2013-2014.RESULTS. Patient median age (75 versus 76 years) and sex distribution (47% versus 46% female) were unchanged. Median door-to-scan time improved from 32 (25th to 75th percentile: 15-73) to 17(11-25) minutes. Number of patients treated with thrombolysis increased from 70 to 152. In 2016-2017, 57 patients had thrombectomy after thrombolysis; 24 had thrombectomy alone. For thrombolysis, median scan-to-needle time decreased from 41(22-60) to 21(12-37) minutes, while door-to-needle time decreased from 62(49-88) to 41(32-55) minutes. Proportion treated with thrombolysis u226460 minutes increased from 47% to 80%. Proportion with standardized screening for dysphagia increased from 32% to 73%. In 2016-2017, 91% of patients were admitted to a stroke unit compared with 75%, previously.CONCLUSIONS. Quebecu2019s provincial action plan and reorganization of care was associated with more ischemic stroke patients being optimally treated in comprehensive stroke centers.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".