Canadian national electrophysiology ablation registry report 2011–2016
Bibliographic record
Abstract
Abstract Background/purpose : Interventional cardiac electrophysiology (EP) is a rapidly evolving field in Canada; a nationwide registry was established in 2011 to conduct a periodic review of resource allocation. Methods The registry collects annual data on EP lab infrastructure, imaging, tools, human resources, procedural volumes, success rates, and wait times. Leading physicians from each EP lab were contacted electronically; participation was voluntary. Results All Canadian EP centres were identified (n = 30); 50 and 45 % of active centres participated in the last 2 instalments of the registry. A mean of 508 ± 270 standard and complex catheter ablation procedures were reported annually for 2015–2016 by all responding centres. The most frequently performed ablation targets atrial fibrillation (PVI) arrhythmia accounting for 36 % of all procedures (mean = 164 ± 85). The number of full time physicians ranges between 1 and 7 per centre, (mean = 4). The mean wait time to see an electrophysiologist for an initial non-urgent consult is 23 weeks. The wait time between an EP consult and ablation date is 17.8 weeks for simple ablation, and 30.1 weeks for AF ablation. On average centres have 2 (range: 1–4) rooms equipped for ablations; each centre uses the EP lab an average of 7 shifts per week. While diagnostic studies and radiofrequency ablations are performed in all centres, point-by-point cryoablation is available in 85 % centres; 38 % of the respondents use circular ablation techniques. Conclusions This initiative provides contemporary data on invasive electrophysiology lab practices. The EP registry provides activity benchmarks on national trends and practices.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".