Repurposing medical devices as “button” esophagostomy tubes for extended nutritional support
Bibliographic record
Abstract
BACKGROUND: Esophagostomy tubes (E-tubes) are widely utilized for extended nutritional support in dogs and cats. Problems associated with their use include the unwieldy excess (10-20 cm) of external tubing, constant need for neck wraps and necessity for skin sutures, suture tract infection, and tube loss if sutures fail. OBJECTIVES: To evaluate 2 different, low profile (LP) "button" products intended for use in people as enteral (jejunostomy [J] and gastrojejunostomy [G-J]) feeding tubes for suitability as LP E-tubes in dogs and cats. ANIMALS: A young giant breed dog that required extended (>6 months) nutritional and fluid support during recovery from severe neurological illness with protracted adipsia, anorexia, and dysphagia. METHODS: Prospective evaluation of 2 commercially available LP feeding devices after placement of a standard E-tube. An LP J-tube and an LP G-J tube were assessed in consecutive 4-week trials, for tube retention, patient comfort, stoma health, and functionality. RESULTS: Both products performed extremely and equally well as LP E-tubes in this clinical patient, enhancing patient freedom and comfort by eliminating external tubing, skin sutures, and bandaging. The dual port G-J tube allows medication delivery (eg, sucralfate) to the entire esophagus, but for safety alone (ie, to avoid aspiration), the single port J-tube appears the best device for client-owned patients. CONCLUSIONS AND CLINICAL IMPORTANCE: The LP enteral feeding tubes from the human medical field can be successfully used as LP E-tubes in dogs and cats, offering superior patient comfort, with no obvious detriment to the patient and main drawback of higher cost.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".