A Simple Method to Maintain Continuous Oral Suction During Upper Endoscopy
Bibliographic record
Abstract
During upper endoscopic procedures, maintenance of oral suction usually requires a nurse to manually hold the suction tube in place, often for a prolonged period of time. In order to provide assistance to the endoscopist with biopsies or hemostasis, the suction tube is often removed, placed under the pillow or falls on the floor, causing patient discomfort due to accumulation of saliva in the oropharynx. To minimize patient distress and allow continuous hands-free suction of saliva, we have developed a modified suction tube attachment method, using the redundancy of the bite block elastic strap. This simple technique allows fixation of the suction tube within the bite block strap, thereby ensuring continuous aspiration of saliva without the need for nurse-held stabilization. The attachment of the suction tube to the bite block is sufficiently mobile to allow repositioning of the apparatus, if required. Any excess tubing can be placed behind the patient's pillow, to avoid traction of the suction tube. Patient comfort and procedural efficiency may be enhanced by using this simple method for suctioning during various diagnstic or theraputic upper endoscopic procedures, including EUS and ERCP.Figure: Attachment of the elastic strap to the bite block.Figure: Suction tube inserted into bite block with overlapping of strap.Figure: Hands-free suction tube secured to bite block.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".