Endoscopic recanalization using rendez-vous technique for complete upper esophageal obstruction: a case report
Bibliographic record
Abstract
Abstract: Esophageal obstruction is a rare late adverse effect after head and neck cancer radiotherapy and chemotherapy treatment. The approach to complete esophageal obstruction is not well established in cases where malignant recurrence has been ruled out. We hereby present the case of a patient that presented with total dysphagia and multiple aspiration episodes. A minimally invasive endoscopic management was proposed for this complete esophageal obstruction. The endoscopic rendez-vous technique for esophageal recanalization requires an antegrade access through the mouth and a retrograde access through a feeding gastrostomy. Two interventional endoscopists locate and measure the length of the stenosis under fluoroscopic control. Once the axis of the two endoscopes is aligned, recanalization is achieved using a needle knife incision followed by balloon dilatation over a guide wire. Nasogastric (NG) tube insertion is performed at the end of the procedure to prevent premature recurrence of the stenosis. Subsequent dilatations were necessary after this procedure to obtain a satisfactory functional result. Post-operative speech therapy follow-up was also required. The endoscopic rendez-vous technique is hence a reliable and safe therapeutic option for short stenosis with transillumination. A multidisciplinary approach and long-term follow-up are mandatory in order to maximize the functional benefit for these complex patients.
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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) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".