A population-based estimate of the health care burden of obstructive sleep apnea using a STOP-BAG questionnaire in South Carolina.

STUDY OBJECTIVES: Population based estimates of obstructive sleep apnea (OSA) frequency and health impact are incomplete. The aim of this study was to determine the prevalence of risk factors for physician and sleep study diagnosed OSA among individuals in a state-based surveillance program. METHODS: Using questions inserted into the 2016 (n = 5,564) and 2017 (n = 10,884) South Carolina Behavioral Risk Factor Surveillance System of the Centers for Disease Control and Prevention, we analyzed the prevalence of physician diagnosed OSA and associated comorbidities. The validated STOP-BANG questionnaire without neck circumference (STOP-BAG) defined populations at moderate risk (score 3-4) and high risk (score 5-7). Statistical analysis using weighted prevalence and means and their 95% confidence intervals (CI) thus reflect population estimates of disease burden. RESULTS: The population-based prevalence of physician diagnosed OSA in South Carolina was 9.7% (95% CI: 9.0-10.4). However, the populations with moderate risk (18.5%, 95% CI: 17.3-19.8) and high risk (25.5%, 95% CI: 23.9-27.1) for OSA, as determined by the STOP-BAG questionnaire, were much higher. Compared to those at low risk for OSA, those at high risk were more often diagnosed with coronary heart disease, stroke, asthma, skin cancer, other cancers, chronic obstructive pulmonary disease, arthritis, depression, kidney disease, and diabetes (all P < .001). CONCLUSIONS: OSA is common and strongly associated with major comorbidities. As such, this public health crisis warrants more diagnostic and therapeutic attention. The STOP-BAG questionnaire provides a public health platform to monitor this disease.

[Study on hypoxemia during sleep in patients with chronic obstructive pulmonary disease].

OBJECTIVE: To investigate the influence of hypoxemia during sleep on elements of polysomnography (PSG) in patients with chronic obstructive pulmonary disease (COPD) and the correlation of sleep hypoxemia and arterial blood gases, pulmonary function in daytime. METHODS: Two hundred and four moderate to very severe stable COPD patients with an age range of 40-75 years [mean age was (70.41+/-7.84) years ] were admitted. All patients underwent overnight PSG, and percentage of the time with oxygen saturation below 0.90 and total sleep time (T90)>or=5% was taken as nocturnal oxygen desaturation (NOD), and if not, they were non-NOD. Arterial blood gases, lung function and PSG examinations were performed in all patients. RESULTS: Ninety-five patients (46.57%) had NOD were enrolled. Compared with patients of non-NOD, both daytime oxygen saturation (SaO2, 0.90+/-0.04 vs. 0.94+/-0.01) and nocturnal mean SaO2 (MSaO2, 0.83+/-0.08 vs. 0.93+/-0.02) in NOD were lower significantly (both P<0.01). Sleep-related elements such as awake period (minutes: 97.86+/-41.74 vs. 76.13+/-55.15), awake frequency (times: 31.50+/-15.69 vs. 23.23+/-19.81), mean heart rate (beat per min: 80.80+/-12.80 vs. 66.21+/-6.53), sleep components [(S1+S2)%: (74.36+/-16.52)% vs. (67.55+/-12.62)%, (S3+S4)%: (12.99+/-12.18)% vs. (19.35+/-12.71)%] in NOD were significantly different from non-NOD (all P<0.01). The levels of arterial partial pressure of carbon dioxide (PaCO2), arterial partial pressure of oxygen (PaO2), percentage of forced expiratory volume in one second (FEV1) and anticipate value, percentage of forced vital capacity (FVC) and anticipate value, percentage of FEV1/FVC and anticipate value in daytime were respectively correlated with the T90, MSaO2 and minimum SaO2 (miniSaO2) in sleep. Among these measurements, PaCO2 was best correlated with sleep hypoxemia (r1=0.767, r2=-0.758, r3=-0.689, all P<0.01). CONCLUSION: Sleep hypoxemia existed generally in patients with moderate to very severe stable COPD. There was significant difference in nocturnal SaO2, daytime SaO2 and sleep-related elements between NOD and non-NOD. The measurements in daytime are correlated with sleep hypoxemia, and some of them may predict sleep hypoxemia.