Cochlear dysfunction is associated with styrene exposure in humans
Bibliographic record
Abstract
AIM: Occupational exposure to styrene has been shown to be associated with an increased probability of developing hearing loss. However, the sites of lesions in the auditory system in humans remain unknown. The aim of this study was to investigate the possible adverse effects of styrene exposure on the cochlea of human subjects. DESIGN: The hearing function of 98 styrene-exposed male workers from the glass fibre-reinforced plastics industry (mean concentration of 55 mg/m3) was evaluated bilaterally using pure-tone audiometry (1000-16000 Hz), distortion product otoacoustic emissions (DPOAEs), and auditory brainstem response (ABR). The results were compared to a group of 111 male workers exposed to noise (above 85 dBA) and 70 male white-collar workers exposed to neither noise nor solvents. Age and noise exposure levels were accounted for as confounding variables in all statistical models. RESULTS: Styrene exposure was significantly associated with poorer pure-tone thresholds (1-8 kHz), lower DPOAE amplitudes (5-6 kHz), and shorter wave V latencies in both ears compared to control-group subjects. Similar results were found among noise-exposed subjects. A further analysis with wave V latency showed that styrene-exposed subjects showed significantly shorter latencies than expected according to normative data. These results suggest that occupational exposure to styrene at moderate concentrations is associated with cochlear dysfunction, at least at high frequencies. DPOAEs may be considered a valuable diagnostic tool in hearing conservation programs in workers exposed to styrene.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".