Comparison of commonly used questionnaires to identify obstructive sleep apnea in a high-risk population Academic Article uri icon

abstract

  • STUDY OBJECTIVES:Sleep apnea is associated with adverse health outcomes. Despite being an important comorbidity in obesity, type 2 diabetes, heart failure, and resistant hypertension, it is underdiagnosed in these patient groups. An inexpensive and readily accessible sleep apnea screening tool would help address this problem. We sought to compare three commonly used screening tools. METHODS:We recruited 812 patients who had not previously been investigated for sleep apnea from our institution's diabetes (n = 512), obesity (n = 129), resistant hypertension (n = 74) and heart failure (n = 43) clinics. Patients completed three frequently used sleep apnea screening questionnaires (STOP-BANG, Berlin, and OSA50). A total of 758 patients had a valid (> 4 hours' duration) level 3 home sleep study. Studies were reported by a sleep physician and were deemed positive if they recorded a respiratory event index (REI) ≥ 15 events/h. RESULTS:The 758 patients with valid sleep studies were age 59 ± 11 years and 63% were male. A total of 38% of patients had a positive test. The respective sensitivities and specificities of the screening questionnaires at the recommended screening thresholds (REI ≥ 15 events/h) were STOP-BANG ≥ 3 (95% and 19%), STOP-BANG ≥ 5 (60% and 69%), Berlin (75% and 38%), and OSA50 (88% and 21%). We identified six independent predictors (age, sex, body mass index, neck circumference, snoring ≥ 3 days per week, observed apnea ≥ 3 days per week). However, combining these factors was no better than the STOP-BANG in predicting sleep apnea. All patients with a STOP-BANG < 3 had an REI < 30 events/h. CONCLUSIONS:There is a high prevalence of undiagnosed symptomatic sleep apnea in high-risk patient groups. The STOP-BANG questionnaire appeared superior, though all questionnaires had significant limitations. Incorporation of STOP-BANG ≥ 3 in this high-risk population might reduce the need for sleep testing in a resource-constrained setting.

authors

  • Kee, K
  • Dixon, J
  • Shaw, Jonathan
  • Vulikh, E
  • Schlaich, M
  • Kaye, DM
  • Zimmet, P
  • Naughton, MT

publication date

  • 2018