Balloon eustachian tuboplasty for patients with chronic eustachian tube dysfunction: a novel method for Iranian samples
Bibliographic record
Abstract
Background and Aim: Balloon eustachian tuboplasty (BET) is a recently developed and approved method for management of chronic eustachian tube dysfunction (ETD). In the present study we aimed to evaluate the safety and efficacy of this method in Iranian samples. Methods: In this prospective case-series study, we included 15 adult patients with chronic ETD who were resistant to previous medical managements and/or ventilation tube use. All patients underwent baseline audiometry (pure tone audiometry and tympanometry), Valsalva maneuver, EDT questionnaire-7 (ETDQ-7), and physical examination. Three to six months after the BET procedure, all patients underwent four evaluation methods again. Results: We found a significant improvement in the mean ETDQ-7 scores comparing pre- and post-test scores (p < 0.0001). There was also a statistically significant decrease in the average air-bone gap from 40.55 at baseline to 27.22 after treatment (p < 0.001). In the Valsalva test, 17 out of 18 study ears (92.3%) had a positive result after the surgery. Under tympanographic evaluation, 9 ears (50%) reported a conversion from type B to type A after treatment, 2 ears (11%) had a conversion from type B to C, and 7 ears (39%) showed no any change and stayed in type B after BET. Conclusion: As a novel method in Iran, BET can be an alternative safe treatment option for chronic ETD. Keywords: Balloon eustachian tuboplasty; eustachian tube dysfunction; Iranian
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".