Hearing loss and history of otolaryngological conditions in adults with microdeletion 22q11.2
Bibliographic record
Abstract
Previous studies have shown that the 22q11.2 microdeletion, associated with 22q11.2 deletion syndrome (22q11.2DS), conveys an increased risk of chronic otitis media, and hearing loss at young age. This study reports on hearing loss and history of otolaryngological conditions in adults with 22q11.2DS. We conducted a retrospective study of 60 adults with 22q11.2DS (41.7% male) at median age 25 (range 16-74) years who had visited an otolaryngologist and audiologist for routine assessment at a 22q11.2 expert center. Demographic, genetic, audiometric, and otolaryngological data were systematically extracted from the medical files. Regression analysis was used to evaluate the effect of age, sex, full-scale intelligence quotient, and history of chronic otitis media on the severity of hearing loss. Hearing loss, mostly high-frequency sensorineural, was found in 78.3% of adults. Higher age and history of chronic otitis media were associated with more severe hearing loss. Otolaryngological conditions with possible treatment implications included chronic otitis media (56.7%), globus pharyngeus (18.3%), balance problems (16.7%), and obstructive sleep apnea (8.3%). The results suggest that in 22q11.2DS, high-frequency hearing loss appears to be common from a young adult age, and often unrecognized. Therefore, we recommend periodic audiometric screening in all adults, including high-frequency ranges.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".