Asymmetrical Hearing Loss in Cases of Industrial Noise Exposure
Bibliographic record
Abstract
OBJECTIVE: Asymmetrical hearing thresholds are common in people claiming compensation for noise-induced hearing loss (NIHL). When present and otherwise unexplained, there is some controversy as to whether such asymmetry can be attributed to occupational noise exposure. In this review, our main objectives were to collate the overall prevalence of this finding in subjects with NIHL, and further, to provide a balanced argument regarding causality. DATA SOURCES: MEDLINE, CINAHL, EMBASE, Cochrane, Google Scholar. No date or language restrictions. STUDY SELECTION AND DATA EXTRACTION: A systematic review of the literature was performed and data on noise exposure, pure tone audiometry, and lateralized hearing outcomes were reviewed. Newcastle-Ottawa (N-O) criteria were employed to assess quality of studies where applicable. DATA SYNTHESIS: N/A CONCLUSION:: Six studies met the inclusion criteria giving a total of 4,735 individual cases with NIHL. Asymmetrical hearing loss accounted for between 2.4% and 22.6% of NIHL cases (L-R difference >15 dB for any frequency 0.5-8 kHz). However, the overwhelming majority of subjects in this review have symmetrical hearing loss when adjusted for other significant variables, e.g., age, sex, and binaural hearing deterioration. Subjects considered for noise exposure remuneration were men (94.3% SE ± 2.7), aged 52.9 years (inter-quartile range, 46.1-58.4), and from a broad range of industrial backgrounds. Future research will be needed to establish the influence of other factors such as smoking status, exposure to chemical agents, specific drugs, or genetic predisposition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".