Does prophylactic bronchoalveolar lavage during surgery reduce post-operative pulmonary complications?
Bibliographic record
Abstract
Reducing post-operative complications from lung surgery is critical. We explored if intra-operative bronchioalveolar lavage would reduce post-operative respiratory complications such atelectasis, pneumonia, and mucous plugging. BAL is well-researched as a diagnostic tool but its use as a protective procedure is not well studied. We conducted a retrospective cohort study of 291 patients who underwent routine BAL intraoperatively during lung surgery in the last 3 years as well as a comparison group of 215 patients who did not receive intra-operative BAL. This group of 506 patients fit the inclusion criteria of having undergone lung resection. Exclusion criteria were as follows: lack of one-lung ventilation, concurrent other surgery. All the surgeries took place at Health Sciences Centre in Winnipeg. 34.9% (n = 75) of patients in control group and 37.1% (n = 108) of the cases had some type of post-operative complication as classified by the Ottawa TM&M. Narrowing down to only respiratory complications (pulmonary and pleural), 20.5% (n = 44) of controls and 25.5% (n = 73) of cases had complications. When looking at only pulmonary complications, 7.4% (n = 16) of the controls and 9.6% (n = 28) of the cases had pulmonary complications. We saw that patients who received BAL prophylactically had a similar incidence of pulmonary complications compared to the control group (9.6% and 7.4% respectively). However, multivariable analysis shows that current smokers benefited greatly from prophylactic BAL where there was a reduction in pulmonary complications.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".