The role of anti-reflux surgery in refractory peptic strictures—case series
Bibliographic record
Abstract
Background: Current treatment algorithms for peptic stricture disease advocate pharmacological acid suppression and serial endoscopic dilations. For patients with refractory strictures, esophageal stents are recommended. The role of surgery is now overlooked in preference to these endoscopic therapies. This study assesses the outcomes of a series of patients with strictures refractory to endoscopic therapy treated with laparoscopic anti-reflux surgery. Case Description: All patients referred to a single centre with refractory peptic strictures between 2014 and 2022 were retrospectively identified and included. All subsequently underwent a laparoscopic fundoplication at St Thomas’ Hospital. Basic demographics, pre-operative stent use, the number of pre and post-operative dilations, surgical and clinical outcomes were collected. Seven patients underwent surgery in this time-period. Four patients of the patients had undergone pre-operative stenting prior to surgery. All three patients treated without stents (median follow-up 7 months) achieved complete symptom resolution. In the stented group, symptom resolution was achieved in 50% (2 of the 4 patients). There were significantly higher numbers of post-operative dilations in the group which were stented prior to surgery (14.0 vs. 0.67, P=0.004). Conclusions: In the management of esophageal peptic stricture disease, the role of laparoscopic fundoplication has been overlooked with the advancement of medical and endoscopic therapies. This study has demonstrated that laparoscopic fundoplication is a safe procedure and has a role alongside these therapies, particularly in refractory 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".