An Optimized Assessment Pathway for Remote Patients: The Vancouver Facilitated Transcatheter Aortic Valve Implantation Program
Bibliographic record
Abstract
Background: Novel pathways are needed to accommodate the increasing demand for transcatheter aortic valve implantation (TAVI) and ensure equitable access. A single Vancouver Facilitated TAVI program (VFTP) based at St. Paul's and Vancouver General Hospitals was established to streamline the assessment of remote patients with severe aortic stenosis using virtual technologies. Methods: Remote patients with severe aortic stenosis who expressed difficulties traveling to complete their pre-TAVI workup were included and received prospective follow-up. Clinical and echocardiographic parameters were reported per the Valve Academic Research Consortium 3. Results: Between December 2020 and March 2023, a total of 56 remote patients were included in the VFTP. The mean patient age was 79.7 ± 9.1 years. A total of 55 patients (98%) passed the screening for candidacy; 45 patients (80%) were found suitable for transfemoral TAVI, 5 patients (9%) were directed toward surgical aortic valve replacement; 3 (5%) underwent alternative-access TAVI; and 2 patients (4%) were assigned to a watchful waiting strategy. No inpatient mortality, stroke, or major bleeding occurred in the transfemoral TAVI group, and the median hospital stay was 1 day (interquartile range, 1-2 days; range, 1-24 days). Two patients had an access-closure failure requiring surgical intervention; 1 patient had tamponade; and 4 patients had complete heart block requiring permanent pacemaker implantation. No hospital readmission had occurred at 30 days. Conclusions: A simplified assessment pathway to assess TAVI candidacy using virtual technologies is safe and feasible. The VFTP potentially can increase access to TAVI and reduce inequity in TAVI care.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".