National practice variation in pneumonectomy perioperative care among Canadian thoracic surgeons†
Bibliographic record
Abstract
OBJECTIVES: Our objective was to assess perioperative pneumonectomy practices among Canadian thoracic surgeons as part of a quality-improvement initiative to determine practice variability and identify areas for study/improvement. METHODS: After several rounds of survey development and piloting, a 29-item survey was distributed using the Dillman method to all practicing members of the Canadian Association of Thoracic Surgeons. RESULTS: The response rate was 87% (62 of 71). Median number of pneumonectomies performed annually was 3.5 (interquartile range 2.75-5.00). Routine preoperative workup was variable, but the most consistently reported tests were diffusing capacity of the lungs for carbon monoxide (87%, n = 54) and spirometry (85%, n = 53). Reported routine use of epidurals (84%, n = 52) was more prevalent than paravertebral blocks (18%, n = 11). Many (69%, n = 43) reported intraoperative restriction <2 l. Postoperatively, 84% (n = 52) reported daily fluid restriction <2 l. Regarding intraoperative protective ventilation strategies, respondents appeared more focused on minimizing peak airway pressures (55%, n = 34) rather than tidal volumes (18%, n = 11). Twenty-four percent (n = 15) reported using intraoperative steroids in attempts to decrease postoperative complications. Thirty-two percent (n = 20) do not routinely insert chest tubes, whereas the most common practice (44%, n = 27) was to insert chest tubes attached to conventional drainage systems without suction. Eighty-two percent (n = 52) reported willingness to participate in multicentre studies regarding perioperative pneumonectomy practices. CONCLUSIONS: Our findings suggest significant variability in reported preoperative, intraoperative and postoperative care practices for pneumonectomy across Canada. This survey has a high response rate, representing the Canadian experience, and highlights several areas for study and quality-improvement initiatives. Many respondents report willingness to participate in multicentre initiatives.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".