Dextranomer Hyaluronic Acid Copolymer Effects on Gastroesophageal Junction
Bibliographic record
Abstract
OBJECTIVE: The outcomes of fundoplication for gastroesophageal reflux disease are suboptimal in many children, and alternatives are clearly needed. Dextranomer hyaluronic acid (DxHA) copolymer, an agent with proven efficacy in vesicoureteral reflux, was studied with respect to its effects on the gastroesophageal junction (GEJ). METHODS: Twelve New Zealand white rabbits underwent measurement of lower esophageal sphincter pressure followed by laparotomy and injection into the muscular layer of the GEJ (controls, 1.0 mL saline; low-dose DxHA [0.5 mL]; high-dose DxHA [1.0 mL]). After a 12-week survival period, the animals underwent manometry, sacrifice, and necropsy. Organs were examined histologically by pathologists blinded to the injection delivered. RESULTS: All animals survived. Weight gain was equal in the 3 groups. There was no significant difference in mean lower esophageal sphincter pressure from baseline in any group (control 2.3 mmHg [95% confidence interval, CI -3.3 to 7.9]; low-dose group 3.2 mmHg [95% CI -0.8 to 7.2]; high-dose group -4.0 mmHg [95% CI -18.95 to 10.95]). Histologically, DxHA injection produced an intramural implant, with a foreign body giant cell reaction, and fibroblastic infiltration with collagen deposition. High-dose injection did not consistently result in a qualitative increase in the magnitude of the reaction. There was no mucosal injury or luminal stenosis. CONCLUSIONS: In this first study evaluating the effects of DxHA injection at the GEJ, a histologic bulking effect was observed without obvious functional complications. The agent may have a role in the treatment of gastroesophageal reflux disease.
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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 | 0.000 | 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 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".