Effects of Behçet's Disease on Hearing Thresholds and Transient Evoked Otoacoustic Emissions
Bibliographic record
Abstract
OBJECTIVES: The aim of this prospective study was to investigate hearing loss in patients with Behçet disease (BD). METHODS: The study group consisted of 20 patients (8 males, 12 females) with BD and 40 ears. The control group consisted of 20 healthy patients without BD (8 males, 12 females) and 40 ears. All subjects were evaluated by an otolaryngologic examination, pure-tone and high-frequency audiometry, and transient evoked otoacoustic emissions (TEOAEs). RESULTS: Sensorineural hearing loss (SNHL) was present in 25% of the ears on pure-tone audiometry and 60% of the ears on high-frequency audiometry in the study group. In the study group, at pure-tone and high-frequency audiometry, hearing thresholds were significantly higher than in the control group. For TEOAE values, in the BD group, each of the 1.0 to 4.0 kHz percent and amplitude values was significantly lower than in the control group. It was found that as age increased, hearing thresholds increased and TEOAEs decreased. As the disease duration got longer, hearing thresholds continued to increase and otoacoustic emissions at 3.0 kHz decreased. In males, hearing thresholds increased more whereas emissions decreased more than in females. CONCLUSION: Since SNHL is not infrequent in BD patients, patients may be evaluated regularly by pure-tone and high-frequency audiometry and TEOAEs. It may be possible to detect cochlear pathologies earlier than audiometric tests by TEOAEs.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".