Screening for severe obstructive sleep apnea syndrome in hypertensive outpatients.

The authors attempted to validate a 2-stage strategy to screen for severe obstructive sleep apnea syndrome (s-OSAS) among hypertensive outpatients, with polysomnography (PSG) as the gold standard. Using a prospective design, outpatients with hypertension were recruited from medical outpatient clinics. Interventions included (1) assessment of clinical data; (2) home sleep testing (HST); and (3) 12-channnel, in-laboratory PSG. The authors developed models using clinical or HST data alone (single-stage models) or clinical data in tandem with HST (2-stage models) to predict s-OSAS. For each model, area under receiver operating characteristic curves (AUCs), sensitivity, specificity, negative likelihood ratio, and negative post-test probability (NPTP) were computed. Models were then rank-ordered based on AUC values and NPTP. HST used alone had limited accuracy (AUC=0.727, NPTP=2.9%). However, models that used clinical data in tandem with HST were more accurate in identifying s-OSAS, with lower NPTP: (1) facial morphometrics (AUC=0.816, NPTP=0.6%); (2) neck circumference (AUC=0.803, NPTP=1.7%); and Multivariable Apnea Prediction Score (AUC=0.799, NPTP=1.5%) where sensitivity, specificity, and NPTP were evaluated at optimal thresholds. Therefore, HST combined with clinical data can be useful in identifying s-OSAS in hypertensive outpatients, without incurring greater cost and patient burden associated with in-laboratory PSG. These models were less useful in identifying obstructive sleep apnea syndrome of any severity.

In-home, self-assembled sleep studies are useful in diagnosing sleep apnea in the elderly.

OBJECTIVES: Obstructive sleep apnea (OSA) is common and treatable among the elderly. Yet, few older adults seek evaluation for OSA at sleep disorders centers. The authors assessed the feasibility of a two-stage screening procedure for obstructive sleep apnea syndrome (OSAS) in a community-based sample of older adults. DESIGN: Prospective cohort study. SETTING: Participants' domicile (in-home) and academic sleep research center. PARTICIPANTS: There were 452 Medicare recipients residing in the greater Philadelphia metropolitan area with the complaint of daytime sleepiness. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: All participants underwent in-home unattended sleep studies that recorded airflow, and standard in-laboratory polysomnography. Additional measures included symptoms of sleep apnea, body mass index, neck circumference, age, and sex. When comparing diagnostic approaches, the best-performing single-stage model was one that combined apnea symptoms with age and neck circumference. This model had an area under the receiver operating characteristic curve (AUC) of 0.774 and negative posttest probability of 1.2%. The best-performing two-stage model combined symptoms, neck circumference, age, and sex in the first stage, followed by an unattended portable study with a corresponding AUC of 0.85 and negative posttest probability of 0.5%. CONCLUSIONS: Unattended, self-assembled, in-home sleep studies recording airflow and respiratory effort are most useful if applied in tandem with clinical data, including a carefully obtained sleep history. This two-stage model is accurate in identifying severe OSAS in older adults and represents a practical diagnostic approach for older adults. Incorporating clinical data was vital and increased accuracy well above that of unattended studies of airflow and effort alone.