Balloon dilation of the eustachian tube using endovascular balloon under local anesthesia—a case series and systematic literature review
Bibliographic record
Abstract
Objective To report a novel technique in Balloon Dilation of Eustachian Tube (BDET) using an endovascular balloon (EVB), in a prospective cohort. The results are compared with reported outcomes using standard balloons. Methods Demographic information and clinical parameters were collected prospectively fora series of patients with obstructive eustachian tube dysfunction (OETD). Balloon dilation Eustachian tuboplasty was performed under local anesthesia in a tertiary referral center, using the EVB. Systematic literature review was used for comparison, using Medline via “PubMed”, “Embase”, and “Web of Science”. Results Eight OETD candidates (12 ears) were enrolled; 5 males and 3 females. Average age was 48 (range −23 to 63) years. The most common presenting symptom was aural fullness (9/12), followed by ear pressure (7/12), hearing loss (5/12) and tinnitus (4/12). Otoscopically, tympanic membrane retraction was evident in 10/12 ears, the majority of which was class II—Sade classification. Pre-operative tympanogram was type B and C in 7 and 5 ears, respectively. All BDETs were performed without complications. Post-operative tympanometry was A in 8/12 ears. Post-operatively, Eustachian Tube Dysfunction Questionnaire-7 results reduced to within normal limits (average score ≤3) in 11/12 ears (p = 0.0014). The systematic literature review included 6 papers (193 patients, 262 ETs) with comparable results, most also with little adverse effects. Conclusion BDET using an EVB is a safe and effective option for OETD. It is well tolerated under local anesthesia in properly selected individuals. The reduced procedural cost may be an important factor in certain healthcare jurisdictions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".