Balloon Dilation and Stent Placement for Esophageal Lesions: Indications, Methods, and Results
Bibliographic record
Abstract
Esophageal balloon dilation and expandable stent placement are safe, minimally invasive, effective treatments for esophageal strictures and fistulas. These procedures have brought the management of dysphagia due to esophageal strictures into the field of interventional radiology. Esophageal dilation is usually indicated for benign stenoses and is technically successful in more than 90% of cases. Most patients with esophageal carcinoma are not candidates for resection; thus, the main focus of treatment is palliation of malignant dysphagia and esophagorespiratory fistulas. Esophageal stent placement, which is approved only for malignant strictures, is one of the main therapeutic options in affected patients and relieves dysphagia in approximately 90% of cases. Dedicated commercially available devices continue to evolve, each with its own advantages and limitations. Stent placement is subject to technical pitfalls, and adverse events occur following esophageal procedures in a minority of cases. Although chest pain is common and self-limited, reflux esophagitis, stent migration, tracheal compression, and esophageal perforation and obstruction require specific interventions. In many cases, these complications can be recognized and treated by the interventional radiologist with minimally invasive techniques.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".