Sensorineural Hearing Loss and Celiac Disease: A Coincidental Finding
Bibliographic record
Abstract
BACKGROUND: Celiac disease (CD) can be associated with a variety of extraintestinal manifestations, including neurological diseases. A new neurological correlation has been found between CD and sensorineural hearing loss (SNHL). OBJECTIVE: To verify the association between SNHL and CD, and to establish whether the neurological hearing impairment in CD is related to nonorgan-specific and antineuronal antibodies, as well as the presence of autoimmune disorders. METHODS: A sample of 59 consecutive biopsy- and serologically proven CD patients were studied. Among CD patients, 11 were newly diagnosed and 48 were on a gluten-free diet. Hearing function was assessed by audiometric analysis in all CD patients as well as in 59 age- and sex-matched controls. Patients were tested for a panel of immune markers including nonorgan-specific autoantibodies and antineuronal antibodies. RESULTS: SNHL was detected in five CD patients (8.5%) and in two controls (3.4%). In one patient, the SNHL was bilateral, whereas the remaining four had a monolateral impairment. The prevalence of SNHL was not significantly different between CD patients and controls. At least one of the antibodies tested for was positive in two of the five CD patients with SNHL and in 12 of the 54 CD patients without SNHL. Antineuronal antibodies to central nervous system antigens were consistently negative in the five CD patients with SNHL. Only one of the five CD patients with SNHL had Hashimoto thyroiditis. CONCLUSIONS: SNHL and CD occur coincidentally. Hearing function should be assessed only in CD patients with clinical signs of hearing deficiency.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".