The Safety of Early Discharge Following Transcatheter Aortic Valve Implantation Among Patients in Northern Ontario and Rural Areas Utilizing the Vancouver 3M TAVI Study Clinical Pathway
Bibliographic record
Abstract
Background: Early hospital ( < 48 hours) discharge following transcatheter aortic valve implantation (TAVI) is an increasingly adopted practice; however, data on the safety of such an approach among patients residing in North Ontario, including remote and medically underserved areas, are lacking. Methods: This retrospective study included patients who underwent TAVI in Sudbury, Ontario. The safety of early discharge after implementation of the Vancouver 3M (multidisciplinary, multimodality, but minimalist) clinical pathway was assessed. The primary endpoint was 30-day mortality. Resource utilization before vs after 3M clinical pathway implementation was also compared. Results: A total of 291 patients who underwent TAVI between 2012 and 2021 were included in the study. One in-hospital death (0.6%) occurred after the 3M clinical pathway implementation, with no mortality observed beyond hospital discharge. Eleven patients (6.7%) required rehospitalization within 30 days. The need for mechanical ventilation and surgical vascular cut-down declined from 100% and 97%, respectively, at baseline, to 6% and 2%. The number of patients receiving TAVI on a given procedural day increased from 2 to 3 patients. The median post-TAVI hospital length of stay decreased from 5 days (2-6 days) to 1 day (1-3 days) after 3M clinical pathway implementation. Conclusions: Following TAVI, early discharge of selected patients residing in Northern Ontario, including rural areas, using the Vancouver 3M clinical pathway was associated with favourable outcomes, short length of stay, and more-efficient resource utilization. These data can help improve healthcare efficiency and bridge variations in TAVI funding and accessibility in underserved locations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".