Polysomnographic and quantitative electroencephalographic correlates of subjective sleep complaints in chronic tinnitus
Bibliographic record
Abstract
Chronic tinnitus, or the perception of hearing sounds without the presence of external stimulation, is estimated at about 10-15% of the population, with highest prevalence after 50 years of age. Sleep complaints are among the most prominent complaints accompanying tinnitus, but objective data are rare. In this study, we examined prospectively the subjective and objective sleep parameters of this patient population in order to determine differences in sleep disturbances associated with chronic tinnitus compared to matched controls. Forty-four subjects (22 with tinnitus and 22 controls without tinnitus), unselected with respect to sleep complaints, participated in this study. The analysis involved 1-week sleep diaries, subjective sleep questionnaires and 1 night of polysomnographic (PSG) assessment. Compared to matched controls, the tinnitus group showed lower subjective sleep quality as measured with the Pittsburgh Sleep Quality Index (PSQI) and sleep diaries, but no significant difference in objective polysomnograph sleep parameters (i.e. sleep latency, efficiency). However, quantitative non-rapid eye movement sleep analysis revealed lower spectral power in the delta frequency band in the tinnitus group compared to controls, and this decrease was correlated with subjective sleep complaints (the lower the delta spectral power, the greater the complaints). This is the first report of an electrophysiological correlate of sleep difficulties supportive of subjective sleep complaints in the tinnitus population.
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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 | 0.002 |
| 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) | 0.001 | 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".