Ripple Effect: Safety, Cost, and Environmental Concerns of Using Sterile Water in Endoscopy
Bibliographic record
Abstract
The gastroenterology societies are committed to reducing the carbon footprint of endoscopies and hence, re-examining waste-generating practices. One such practice is the recommendation to use sterile water during endoscopy for endoscopy lens cleaning and colon irrigation. We critically reviewed all published medical literature and guidelines on the safety of the type of water used in endoscopy. We calculated the cradle-to-grave carbon footprint of a 1-L sterile water bottle and compared it to published studies on bottled drinking water. Guidelines recommending sterile water during endoscopy are based on limited evidence and mostly expert opinions. Referenced studies utilize care protocols that are not practiced. There is also considerable cross-referencing of review articles and guidelines. Two clinical studies directly comparing tap and sterile water in gastrointestinal endoscopy found tap water to be a safe and practical cost-saving alternative to sterile water. The calculated carbon footprint of bottled sterile water is 575 g CO 2 equivalent. No direct evidence supports the recommendation and widespread use of sterile water during gastrointestinal endoscopy procedures. It contributes to health-care waste and climate change and is costly. We recommend tap water be used to fill sterile water bottles until evidence shows the need for alternative practice. It would be prudent to re-evaluate guidelines and write new ones that consider harm to the environment and society in the provision of care to patients, especially when the intervention may be more harmful than the risk it aims to address.
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 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 | 0.062 | 0.287 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".