About article
Development of Arabic version of Berlin questionnaire to identify obstructive sleep apnea at risk patients
Background: Obstructive sleep apnea (OSA) is a common, under-recognized, under diagnosed, under treated, and serious medical condition in adults. Polysomnography (PSG) is the gold standard for diagnosis of OSA; however, prohibitive cost of the test and rarity of sleep laboratory in the Arabic nations limit its access. So, searching for another simple, economical, reliable, and valid tool for identification of OSA at risk patients is of special public concern. Objective: This study was conducted to evaluate the reliability and validity of Arabic version of Berlin questionnaire (ABQ) in detection of OSA at risk patients. Methods: After hospital ethics approval and formal patients consent, 100 patients were subjected to full night PSG study after their response to the developed ABQ. The patients were classified into both low (30) and high risk (70) for OSA using ABQ and validated against apnea hypopnea index (AHI). Reliability was assessed by internal consistency using Cronbach's alpha test and consistency over time using test retest correlation. Results: The study demonstrated a high degree of internal consistency and stability over time for the developed ABQ. The Cronbach's alpha coefficient for the 10-item tool was 0.92. Validation of ABQ against AHI at cutoff >5 revealed a sensitivity of 97%, specificity of 90%, positive and negative predictive values of 96% and 93%, respectively. Conclusion: The ABQ is reliable and valid scale in screening patients for the risk of OSA among Arabic-speaking nations, especially in resource-limited settings.
Saleh, A. B. M., et al. (2011). "Development of Arabic version of Berlin questionnaire to identify obstructive sleep apnea at risk patients." Annals of Thoracic Medicine 6(4): 212-216.
Methods | Condition | Gender | Age | Country | Setting | Sample size |
---|---|---|---|---|---|---|
|
Patients | Both |
Germany |
Healthcare Facility | 100 |
Measure does not require training
Less than 5 min
baset_saleh@gawab.com