The Effect of Covid-19 Pandemic on Current and Future Endoscopic Personal Protective Equipment Practices: A National Survey of 77 Endoscopists
Bibliographic record
Abstract
Abstract Introduction The COVID-19 pandemic has raised awareness about the importance of personal protective equipment (PPE). We aimed to study and compare PPE practices among Canadian endoscopists before and after the COVID-19 pandemic. Methods A 74-item questionnaire was emailed from June 2020 to September 2020 to practicing endoscopists in Canada. Survey questions collected basic demographics and differences between PPE practices pre- and post-COVID-19. PPE practices were categorized into four endoscopic procedure types including upper or lower endoscopy and diagnostic or interventional. Outcomes for specific procedures were reported as rates, with ranges shown when evaluating all procedure types together. Results A total of 77 respondents completed the survey with the majority of respondents aged 40 to 49 (44%) and identifying as Gastroenterologists (70%). Gender was evenly split (49% females versus 51% males). In the pre-pandemic era, the majority of endoscopists wore gowns (91 to 94%) and all endoscopists wore gloves (100%). However, the majority of endoscopists did not wear surgical masks (21 to 31%), face shields (13 to 34%), eye protection (13 to 21%), hair protection (11 to 13%), or N95 respirators (2 to 3%). In the post-pandemic era, more surgeons plan on wearing face shields (33 to 47%, P = 0.001 to 0.045), goggles (38.5 to 58.7%, P < 0.001), hair protection (33 to 36%, P = 0.011 to 0.024), and a trend suggests more surgeons will wear surgical masks (51 to 61%, P = 0.163 to 0.333). More endoscopists also plan on wearing N95 respirators during lower endoscopy (6 to 7%, P < 0.005). Conclusion The COVID-19 pandemic has changed the attitudes of many endoscopists regarding future PPE use in routine endoscopy. Ongoing studies are needed to inform new post-pandemic PPE consensus guidelines.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".