The prevalence of obstructive sleep apnea in Japanese asthma patients
Bibliographic record
Abstract
Abstract Background Obstructive sleep apnea (OSA) occurs more commonly in asthma patients than in the general population because these conditions share some comorbidities. In Japan, the prevalence of OSA in the general population is reported to be approximately 20%; however, few reports have described the prevalence of OSA in asthma patients. Furthermore, the characteristics of Japanese patients with OSA and asthma are not clear. Methods Adult asthma patients were recruited from the outpatient departments of our institution between August 31, 2017, and March 31, 2019. In all included patients, the presence and severity of OSA were evaluated by the Epworth Sleepiness Scale (ESS) and a home sleep test (HST) using portable polysomnography (PSG). The rate of coexisting OSA in asthma patients and the characteristics of those patients according to the severity of OSA were investigated. Results Fifty-three patients were included. OSA was detected in 36 (67.9%) patients (mild, n = 15; moderate, n = 14; and severe, n = 7). Patients with OSA had significantly higher body mass index, Brinkman index, apnea-hypopnea index (AHI), and 3% oxygen desaturation index (ODI) values in comparison to those without OSA, while the percentage of the predicted value of forced vital capacity (%FVC) and lowest SpO2 levels were significantly lower. As the severity of OSA increased, age, brain natriuretic peptide level, AHI, and 3%ODI increased, and in contrast, FVC, %FVC, forced expiratory volume in one second (FEV1), percentage of the predicted value of FEV1 (%FEV1), Epworth Sleepiness Scale (ESS), 3%ODI, and lowest SpO2 levels decreased. In particular, the fact that the ESS value was inversely correlated with the severity of OSA in our patients was different from the general characteristics of OSA. Moreover, the AHI value was negatively correlated with FVC, %FVC, FEV1, and %FEV1. BMI was the only independent factor for the presence of OSA, and for asthma severity (FEV1, % of predicted), there was a weak correlation with smoking history. Conclusions This is the first report to investigate the prevalence of OSA in Japanese asthma patients, using an HST. This study suggests that an HST should be performed in addition to the sleep interview for asthma patients with refractory disease, a low pulmonary function, advanced age, and high BMI because the more severe the OSA, the lower the ESS value may be.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".