Interventional cardiology fellowship training in canada
Bibliographic record
Abstract
BACKGROUND: Several institutions in Canada offer fellowship training in interventional cardiology (IC). However, no national mechanism exists to ensure uniformity of training or assessment of final competency. METHODS: A cross-sectional survey was carried out for physicians completing IC training from 2007 to 2009. The survey used a semistructured questionnaire to determine compliance with training components recommended by Accreditation Council for Graduate Medical Education (ACGME) and American College of Cardiology (ACC). RESULTS: Sixty-six (78%) of 85 trainees from 15 programs participated in the study. All programs were affiliated with a university and associated with accredited programs in adult cardiology. Annual procedural volume of >1,500 and faculty volume of >250 were reported for 67% and 70% of programs. Annual trainee percutaneous coronary intervention volume of 250-350 was reported by 29%, 350-450 by 47%, and >450 by 24% of respondents. All respondents reported regular participation in case management rounds, and 54% reported formal instruction of structured curriculum; 91% reported participation in research, and 38% reported mandatory attendance in outpatient clinic. All respondents reported annual and 61% reported ≥2 performance evaluations per year; 45% of respondents reported formal trainee assessment of program and faculty. CONCLUSION: Canadian IC training meets ACGME/ACC recommendations for procedural volume and academic activity. However, participation in outpatient clinics and compliance with administrative requirement of faculty and program assessment by trainee was suboptimal. Formal accreditation is highly desirable to standardize program content and administration for optimal IC training.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".