A Systematic Review and Meta-Analysis of Extended High-Frequency Hearing Thresholds in Tinnitus With a Normal Audiogram
Bibliographic record
Abstract
OBJECTIVES: Current evidence supports the growing application of extended high-frequency (EHF: 9 to 20 kHz) audiometry in hearing research, which likely results from the high vulnerability of this frequency region to damage induced by known auditory risk factors. The present systematic review and meta-analysis were performed to investigate whether adults with a normal audiogram and tinnitus show increased EHF hearing thresholds relative to control peers. DESIGN: A comprehensive search was undertaken on electronic databases consisting of PubMed, ScienceDirect, Wiley, and Google Scholar using combined keywords: "tinnitus," "extended high frequency," "normal audiogram," and "hidden hearing loss." RESULTS: From 261 articles found by searching databases, nine studies met the inclusion criteria for the meta-analysis. A significant difference was observed between tinnitus and control groups in the effect size analysis of hearing thresholds at 10, 12.5, 14, 16, and 18 kHz ( p ≤ 0.001), and the I-square heterogeneity analysis was below 50% in all studies ( p ≥ 0.131). Visual inspection by the Funnel plot and Egger's regression test ( p ≥ 0.211) also exhibited no publication bias in the meta-analyses. CONCLUSIONS: Our findings are in support of the idea that in most cases, tinnitus is associated with some degree of cochlear mechanical dysfunction, which may not be detected by conventional audiometry alone. This finding underscores the significance of EHF audiometry in clinical practice, which may help both early identification of individuals susceptible to developing tinnitus and reduce the number of new cases through preventive counseling programs.
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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 | 0.015 | 0.041 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".