Procedure volume and mortality after surgical lung biopsy in interstitial lung disease
Bibliographic record
Abstract
Surgical volume–outcome relationships are well established but have not been studied in patients with interstitial lung disease (ILD) undergoing surgical lung biopsy (SLB). Our study objective was to determine if hospital SLB volume is associated with post-operative mortality in patients with ILD. A cohort study using administrative, population-based data from Ontario, Canada was performed in adults with ILD who underwent a SLB between 2001 and 2014. The association between yearly hospital SLB volume and 30-day post-operative mortality was assessed using multilevel logistic regression modelling. 3057 surgical lung biopsies for ILD were performed during the study period with a median (interquartile range) yearly hospital volume of 73 (34–143) procedures. 30-day mortality was 7.1%, 20.2% and 1.9% in overall, nonelective and elective patients, respectively. Higher yearly hospital SLB volume was associated with lower odds of 30-day post-operative mortality after adjusting for patient characteristics (OR 0.84, 95% CI 0.73–0.97; p=0.02), with the association appearing stronger for nonelective versus elective procedures (OR 0.84, 95% CI 0.69–1.02; p=0.08 versus OR 0.94, 95% CI 0.74–1.18; p=0.57). Higher yearly hospital SLB volume was associated with lower post-operative mortality in patients with ILD, with the association appearing to be mainly driven by nonelective cases. SLB mortality was significantly higher for nonelective cases.
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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".