Anxiety, depression and alexithymia in patients with obstructive sleep apnea syndrome
Bibliographic record
Abstract
We attempted to investigate anxiety (with Spielberger's Trait Anxiety), depression (with Beck Depression Inventory) and alexithymia (with Toronto Alexithymia Scale) in patients with newly diagnosed obstructive sleep apnea syndrome (OSAS) with an Apnea-Hypopnea Index (AHI) ≥ 5 events/hour. We present our results from 32 consecutive patients (age 51±9 years, AHI 54±16 events/hour, no significant cardiac or other comorbidities) who have performed full night polysomnography due to symptoms, sucha as snoring, disrupted sleep, witnessed apneas, morning headache, morning fatigue and daily hypersomnolence (estimated by Epworth Scale).We have found that 56.25% of patients had clinically important anxiety, 62.50% depression and 46.87% alexithymia. Apart from a weak correlation between anxiety and sleep latency, there was not any other correlation between the above psychologic parameters and age, AHI, nocturnal oxygenation and sleep efficiency. We found a cut-off level of AHI ≥ 70 events/hour and age ≥ 60 years old in combination, where all 9 patients in that specific subgroup had anxiety, depression and alexithymia. In conclusion, the incidence of anxiety, depression and alexithymia is significantly higher in OSAS patients as compared to the general population.Older age and more severe OSAS are factors predisposing to these psychologic disturbances. However, not any correlation has been found between the psychologic profile and severity of OSAS, abnormal oxygenation or sleep quality. Probably, other factors, unknown as of yet, may play a role.
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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) | 0.001 | 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".