Sensorineural hearing loss in anti-interleukin-1 treated CAPS patients: risk factors and real-life barriers—an observational study
Bibliographic record
Abstract
OBJECTIVE: To identify modifiable risk factors associated with progression of hearing impairment from a longitudinal cohort of anti-IL-1-treated children and adults with Cryopyrin-Associated Periodic Syndromes (CAPS) and explore real-life barriers to optimal long-term management. METHODS: A single-centre, longitudinal study included consecutive paediatric and adult anti-IL-1-treated CAPS patients with sensorineural hearing loss between 2006 and 2024. Data collected encompassed demographics, disease characteristics, genotype, treatment regimens and hearing assessments using 4PTA, HF-PTA. Primary outcome was WHO grade of hearing impairment at last follow-up. Factors associated with hearing impairment and real-life barriers mandating therapy escalation were identified. RESULTS: The study included 36 patients; 20 males, 16 females, median age at CAPS disease onset and hearing loss diagnosis was 11.8 and 40 years, respectively. Most patients (83%) exhibited moderate CAPS phenotype, carrying pathogenic or likely pathogenic NLRP3 variants (78%). Hearing loss was present in 83% at baseline and 88% at last follow-up with HF-PTA-sensitivity of 100%. Patients diagnosed in adulthood, those with a late treatment start, and/or with pathogenic or likely pathogenic variants demonstrated higher WHO grades of hearing impairment. Ten patients required therapy escalation due to progressive hearing loss, eight of whom carried pathogenic mutations. Early progression was primarily driven by disease activity, while late progression was predominantly influenced by non-compliance. Over time, 86% maintained stable hearing, 8% showed improvement and 6% experienced worsening. CONCLUSION: Early diagnosis, timely intervention and a refined Treat-to-Target approach are vital for hearing in lifelong CAPS management. Precision care and continuous monitoring are key to improving long-term outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".