Obstructive Sleep Apnea Screening in Psoriasis Using the STOP-Bang Questionnaire: A Cross-Sectional Study
Bibliographic record
Abstract
INTRODUCTION: Psoriasis is a chronic, immune-mediated inflammatory disease characterized by sharply circumscribed erythematous plaques on the trunk and limbs. Reports are suggesting low sleep quality and increased risk of Obstructive Sleep Apnea Syndrome (OSAS) in psoriasis patients. METHODS: The present study aimed to investigate the array of OSAS in psoriasis based on the STOP-Bang questionnaire. The study was cross-sectional. The sample was sequential and for convenience. The association between categorical variables was verified with Pearson's chi-square and Fischer's exact tests, and Pearson and Spearman's correlations were used to evaluate the relationships between the continuous variables. P<0.05 values were considered significant. RESULTS: A total of 104 patients were selected, 53 (51%) males, with a mean age of 51.7±14.8 years. Body mass index was 29.3±5 kg/m2. Hypertension was present in 38 (36.5%) and diabetes in 19 (18.3%) patients. Psoriasis was controlled in 87 (83.7%) patients, determined by the PASI Score below 10 points. Regarding the risk for sleep apnea, 36 (34.6%) were at high risk, 28 (26.9%) were at intermediate risk, and 40 (38.5%) were at low risk. There was no significant correlation between the degree of severity of psoriasis and the risk of apnea by the STOP-Bang score (p=0.6). CONCLUSIONS: The present study suggests an increased prevalence in high and intermediate-risk scores for OSA in the population with psoriasis. No association was observed between the degree of severity of psoriasis and apnea risk. Prospective controlled studies using the diagnosis of OSAS by polysomnography are necessary.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".