Lower esophageal sphincter achalasia-like syndrome causing megaesophagus in a cat
Bibliographic record
Abstract
Case summary: Feline megaesophagus (ME) is a rare failure of esophageal motility leading to regurgitation, weight loss and sometimes death in cats. It has been identified secondarily to neurologic and neuromuscular disorders, mechanical obstruction of the esophagus (eg, vascular ring anomalies, esophageal stricture) and upper airway obstruction among others; when no cause is found, it is considered idiopathic. Videofluoroscopic swallow studies (VFSSs), especially using an unrestrained free-feeding protocol, are underutilized for comprehensive evaluation of cats with regurgitation, including identifying the etiology of ME. In this case report, a 3-month-old male intact domestic shorthair cat with a history of regurgitation since weaning and radiographic evidence of ME had VFSS features compatible with a functional obstruction of the lower esophageal sphincter (LES) consistent with LES achalasia-like syndrome. Medical management with sildenafil failed to improve clinical signs, and surgical correction of LES achalasia using a Heller myotomy and Dor fundoplication was declined. As a result of caregiver compassion fatigue from persistent regurgitation, euthanasia was elected. Relevance and novel information: Videofluoroscopic documentation of functional obstruction of the LES (ie, LES achalasia-like syndrome) can identify a novel etiology of feline ME. Free-feeding unrestrained VFSS protocols are recommended to allow physiologic assessment of swallowing disorders with no higher risk of aspiration than eating and drinking at home. Recognition of LES achalasia-like syndrome may lead to further study of directed treatments targeting the functional obstruction as has been carried out in humans and dogs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".