Obstructive Sleep Apnea In Schizophrenia : How To Screen, Why To Treat?
Bibliographic record
Abstract
INTRODUCTION: High risk of obstructive sleep apnea (OSA) was reported in patients with schizophrenia. However, existing screening questionnaires haven't been validated in this population, and the impact of comorbidity in this population has rarely been studied.OBJECTIVES: The study was lead to show the prevalence and impact of comorbid OSA in patients with schizophrenia and validate the existing OSA screening scales.METHOD: Patients with schizophrenia consecutively admitted to hospital (n=51,18 F, age 37,7 u00b1 12,1) and patients with schizophrenia and obesity (n=31,16 F, age 38,6 u00b1 12,0 ) were compared to healthy controls (n=51, 18 F, age 37,9 u00b1 11,0). Berlin Questionnaire , Epworth Sleepiness scale , STOP-BANG questionnaire, NoSAS and No-Apnea scales were used to assess apnea risk. Severity of symptoms of schizophrenia was measured with PANSS and Calgary scales and B-CATS tests. OSA was diagnosed using Embletta system.RESULTS: In diagnostic examination OSA was found more frequent in obese schizophrenia patients compared to consecutively admitted to hospital schizophrenia patients (45% vs. 22%, p<0,05). Significant differences between patients with and without OSA were found in negative symptoms PANSS subscale, B-CATS digit symbol test and daytime sleepiness. No existing screening scale showed satisfactory sensitivity and specificity. Neck circumference above 41 cm (F) and 43 cm (M) with BMIu226530 (BMI-NECK model) allowed to predict OSA in 76,8% of cases (PPV=68,0%, NPV=80,7%).CONCLUSIONS: OSA should be screened in patients with schizophrenia as it's common, has negative influence on schizophrenia symptoms and may add up to higher mortality of these patients The assessment of BMI and neck circumference proves satisfactory screening test in ambulatory conditions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".