BACKGROUND: Recent evidence suggests that obstructive sleep apnea (OSA) is common in patients with metabolic syndrome (MetS) and may contribute to metabolic deregulation, inflammation, and atherosclerosis in these patients. In clinical practice, however, OSA is frequently underdiagnosed. We sought to investigate the clinical predictors of OSA in patients with MetS. METHODS: We studied consecutive patients newly diagnosed with MetS (Adult Treatment Panel-III). All participants underwent clinical evaluation, standard polysomnography, and laboratory measurements. We performed a logistic regression model, including the following variables: gender, age >50 years, neck and waist circumferences, hypertension, diabetes, body mass index (BMI) >30 kg/m2, high risk for OSA by Berlin questionnaire, presence of excessive daytime somnolence (Epworth Sleepiness Scale), abnormal serum glucose, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol. RESULTS: We studied 197 patients (60% men; age: 49 ± 10 years; BMI: 32.9 ± 5.1 kg/m2). OSA (defined by an apnea-hypopnea index ≥15 events per hour) was diagnosed in 117 patients [59%; 95% confidence interval (CI): 52-66]. In multivariate analysis, male gender [odds ratio (OR): 3.28; 95% CI: 1.68-6.41; P < 0.01], abnormal glucose levels (OR: 3.01; 95% CI: 1.50-6.03; P < 0.01), excessive daytime sleepiness (OR: 2.38; 95% CI: 1.13-5.04; P = 0.02), and high risk for OSA by Berlin questionnaire (OR: 4.33; 95% CI: 2.06-9.11; P < 0.001) were independently associated with OSA. CONCLUSIONS: Simple clinical and metabolic characteristics may help to improve the underdiagnosis of OSA in patients with MetS.
BACKGROUND: Recent evidence suggests that obstructive sleep apnea (OSA) is common in patients with metabolic syndrome (MetS) and may contribute to metabolic deregulation, inflammation, and atherosclerosis in these patients. In clinical practice, however, OSA is frequently underdiagnosed. We sought to investigate the clinical predictors of OSA in patients with MetS. METHODS: We studied consecutive patients newly diagnosed with MetS (Adult Treatment Panel-III). All participants underwent clinical evaluation, standard polysomnography, and laboratory measurements. We performed a logistic regression model, including the following variables: gender, age >50 years, neck and waist circumferences, hypertension, diabetes, body mass index (BMI) >30 kg/m2, high risk for OSA by Berlin questionnaire, presence of excessive daytime somnolence (Epworth Sleepiness Scale), abnormal serum glucose, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol. RESULTS: We studied 197 patients (60% men; age: 49 ± 10 years; BMI: 32.9 ± 5.1 kg/m2). OSA (defined by an apnea-hypopnea index ≥15 events per hour) was diagnosed in 117 patients [59%; 95% confidence interval (CI): 52-66]. In multivariate analysis, male gender [odds ratio (OR): 3.28; 95% CI: 1.68-6.41; P < 0.01], abnormal glucose levels (OR: 3.01; 95% CI: 1.50-6.03; P < 0.01), excessive daytime sleepiness (OR: 2.38; 95% CI: 1.13-5.04; P = 0.02), and high risk for OSA by Berlin questionnaire (OR: 4.33; 95% CI: 2.06-9.11; P < 0.001) were independently associated with OSA. CONCLUSIONS: Simple clinical and metabolic characteristics may help to improve the underdiagnosis of OSA in patients with MetS.