Oesophageal pain: A tough nut to crack the role of high resolution manometry guided segmental oesophageal myotomy
Bibliographic record
Abstract
Introduction: Oesophageal motility disorders (OMDs) are a recognized cause of pain in 25-33% of patients with non-cardiac chest pain. The understanding of these disorders based on standard multichannel oesophageal manometry has improved with high resolution oesophageal manometry (HROM). This could facilitate selection of treatment modality including identifying those suitable for surgical myotomy while preserving oesophageal function. Material and methods: This discussion is based on a 65 year old lady with a 17 year history of oesophageal pain due to Nutcracker oesophagus. Persistence of symptoms despite medical management using proton pump inhibitors, calcium channel blockers, nitrates, endoscopic pneumatic dilatation & Botulinum toxin injection prompted re-referral to our specialist unit and analysis of residual oesophageal function using HROM. This revealed a segment of nutcracker oesophagus in the mid oesophagus with significant supine reflux. Result: Surgical treatment with trans-hiatal open focused oesophageal myotomy with preservation of lower oesophageal sphincter and floppy Nissen fundoplication led to satisfactory and complete resolution of symptoms. Discussion: HROM provides a clearer classification of the functional abnormalities and their co-relation to symptoms. This allows application of the best available treatment modality including surgery to achieve symptomatic relief with preservation of residual oesophageal function. Conclusion: Limited evidence is currently available on the comparative benefits of available treatment modalities for OMDs. HROM provides greater insight into OMDs and the benefits of available treatment modalities allowing selection of optimal treatment modality and preserving oesophageal function while achieving relief of the patients distressing symptoms.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".