Association Between Tinnitus and Hearing Recovery in Sudden Sensorineural Hearing Loss: A Meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To investigate the association between tinnitus and hearing recovery prognosis in patients with sudden sensorineural hearing loss (SSHL). DATA SOURCES: PubMed, Web of Science, and Embase. MATERIALS AND METHODS: Eligible studies published between 1983 and 2025 were included. Study quality was assessed using the Newcastle-Ottawa Scale (NOS; scores ≥7 indicated high quality). Data were pooled using an inverse-variance random-effects model, with results presented through forest plots. Publication bias and sensitivity analyses were performed. RESULTS: Among 4782 patients from 10 studies, 3590 had SSHL with tinnitus, while 1192 had SSHL without tinnitus. All included studies had NOS scores ≥7. The hearing recovery rate was higher in the tinnitus group (57.44%) than in the non-tinnitus group (50.84%). Tinnitus was positively associated with better hearing recovery [odds ratio (OR) = 0.60; 95% CI, 0.42-0.85; I2 = 67.2%]. Subgroup analyses using Siegel criteria and systematic corticosteroid treatment yielded consistent results. However, no significant association was observed in the intratympanic corticosteroid subgroup (OR = 0.80; 95% CI, 0.45-1.44). CONCLUSIONS: Tinnitus may serve as a favorable prognostic indicator for hearing recovery in SSHL, except in patients receiving intratympanic corticosteroids. Systemic corticosteroids might be more effective for SSHL patients with tinnitus. Future studies could explore personalized SSHL treatment strategies using tinnitus as a stratification criterion.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.032 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".