Postoperative but not intraoperative transfusions are associated with respiratory failure after pneumonectomy
Bibliographic record
Abstract
OBJECTIVES: Transfusion of blood products has been associated with increased risk of post-pneumonectomy respiratory failure. It is unclear whether intraoperative or postoperative transfusions confer a higher risk of respiratory failure. Our objective was to assess the role of transfusions in developing post-pneumonectomy respiratory failure. METHODS: We performed a retrospective cohort study using prospectively collected data on consecutive pneumonectomies between 2005 and 2015. Patient records were reviewed for intraoperative/postoperative exposures. Univariable and multivariable analyses were performed. RESULTS: Of the 251 pneumonectomies performed during the study period, 24 (9.6%) patients suffered respiratory failure. Ninety-day mortality was 5.6% (n = 14) and was more likely in patients with respiratory failure (7/24 vs 7/227, P < 0.001). Intraoperative and postoperative transfusions occurred in 42.2% (n = 106) and 44.6% (n = 112) of patients, respectively and were predominantly red blood cells. On univariable analysis, both intraoperative (P = 0.03) and postoperative transfusion (P = 0.004) were associated with a higher risk of respiratory failure. The multivariable model significantly predicted respiratory failure with an area under curve (AUC) = 0.88 (P = 0.001). On multivariable analysis, the only independent predictors of respiratory failure were postoperative transfusions [adjusted odds ratio (aOR) 6.54, 95% confidence interval (CI) 1.74-24.59; P = 0.005] and lower preoperative forced expiratory volume (adjusted OR 0.96, 95% CI 0.93-0.99; P = 0.03). Estimated blood loss was not significantly different (P = 0.91) between those with (median 800 ml, interquartile range 300-2000 ml) and without respiratory failure (median 800 ml, interquartile range 300-2000 ml). CONCLUSIONS: Respiratory failure occurred in 9.6% of patients post-pneumonectomy and confers a higher risk of 90-day mortality. Postoperative (but not intraoperative) transfusion was the strongest independent predictor associated with respiratory failure. Intraoperative transfusion may be in reaction to active/unpredictable blood loss and may not be easily modifiable. However, postoperative transfusion may be modifiable and potentially avoidable. Transfusion thresholds should be assessed in light of potential cost-benefit trade-offs.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".