Bacterial contamination and greenhouse gas emissions
Bibliographic record
Abstract
BACKGROUND: Reusing anaesthesia infusion-set components may reduce the climate impact from plastic waste and discarded medications. Infusion-set contents can be shielded from patient contact by single use of an infusion line fitted with dual antireflux valves, preventing retrograde entry of microorganisms, and eliminating the risk for patient-to-patient cross-contamination. However, infusion-set contamination from compromised aseptic handling could affect quality of care. INTERVENTIONS: To determine the prevalence of infusion-set bacterial contamination and compare the climate effects, we randomised operating rooms scheduled for total intravenous anaesthesia to handle procedures by infusion-set reuse or single-use. Both methods used dual single-use antireflux valves. OUTCOMES: The primary outcome was infusion-set bacterial contamination assessed by aerobic culture of infusion-set fluid collected after each procedure. The secondary outcome was CO 2 emissions (CO 2 -eq) estimated by life cycle assessment of component and medication use. To assess feasibility of detecting an inter-method difference in bacterial contamination, an interim analysis was planned after including at least 150 procedures per group. RESULTS: After allocating 54 operating rooms per method, 189 and 159 procedures of reuse and single use were included. Reuse permitted a median of three procedures per infusion set (range 1 to 8). Positive cultures occurred in two procedures per method [mean (95% CI)]; prevalence 1.15% (0.03 to 2.27); relative risk of reuse versus single use 0.84 (0.12 to 5.93), P = 0.861. As prespecified, inclusion was stopped due to futility. The median (95% CI) per-procedure climate emissions were 0.43 (0.41 to 0.47) and 1.39 (1.37 to 1.40) kg CO 2 -eq for reuse and single-use respectively; difference -0.96 (-0.99 to -0.93), P < 0.0005. The main sources for climate emissions were production of infusion-set components and waste handling. CONCLUSIONS: We conclude that the prevalence of bacterial contamination was low for both methods. A much larger study would be needed to detect an inter-method difference. Reuse of infusion-set components allowed significantly reduced intravenous anaesthesia climate emissions.
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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 | 0.000 |
| 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 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".