An Evaluation of Procedural Training in Canadian Respirology Fellowship Programs: Program Directors’ and Fellows’ Perspectives
Bibliographic record
Abstract
BACKGROUND: In recent years, there has been a rapid growth in diagnostic and therapeutic procedures performed by respirologists. OBJECTIVES: To assess the number and type of procedures performed in Canadian respirology training programs, for comparison with the American College of Chest Physicians minimum competency guidelines, and to assess fellow satisfaction with procedural training during their fellowships. METHODS: Internet-based surveys of Canadian respirology fellows and respirology fellowship program directors were conducted. RESULTS: Response rates for program director and respirology fellow surveys were 71% (10 of 14) and 62% (41 of 66), respectively. Thirty-eight per cent of respirology fellows reported the presence of an interventional pulmonologist at their institution. Flexible bronchoscopy was the only procedure reported by a large majority of respirology fellows (79.5%) to meet American College of Chest Physicians recommendations (100 procedures). As reported by respirology fellows, recommended numbers of procedures were met by 59.5% of fellows for tube thoracostomy, 21% for transbronchial needle aspiration and 5.4% for closed pleural biopsy. Respirology fellows in programs with an interventional pulmonologist were more likely to have completed some form of additional interventional bronchoscopy training (80% versus 32%; P=0.003), had increased exposure to and expressed improved satisfaction with training in advanced diagnostic and therapeutic procedures, but did not increase their likelihood of achieving recommended numbers for any procedures. CONCLUSIONS: Canadian respirology fellows perform lower numbers of basic respiratory procedures, other than flexible bronchoscopy, than that suggested by the American College of Chest Physicians guidelines. Exposure and training in advanced diagnostic and therapeutic procedures is minimal. A concerted effort to improve procedural training is required to improve these results.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".