Edward M Weaver1, Vishesh Kapur, Bevan Yueh. 1. Department of Otolaryngology-Head and Neck Surgery, Sleep Disorders Center, Washington, USA. eweaver@u.washington.edu
Abstract
BACKGROUND: While obstructive sleep apnea syndrome is defined by both polysomnographic (PSG) abnormalities and symptoms, severity is quantified primarily by the apnea-hypopnea index (AHI) alone. OBJECTIVE: To determine the correlation between standard PSG indices (AHI and others) and self-reported sleepiness, mental health status, and general health in patients with sleep apnea. DESIGN: Cross-sectional study. SETTING: University-affiliated outpatient sleep laboratory. PATIENTS: Ninety-six consecutive patients with PSG-confirmed sleep apnea (AHI >or=5). MEASUREMENTS: Patients completed a questionnaire that included the Epworth Sleepiness Scale, Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) mental health domain, and self-rated health on the evening of diagnostic PSG. Spearman correlation coefficients were computed. This sample had 85% power to detect a correlation of 0.3 or greater. The associations between PSG indices and self-reported measures were further assessed with multivariable regression techniques, adjusting for age, sex, body mass index, comorbidity, and PSG type. RESULTS: The PSG parameters correlated poorly with self-reported measures (15 correlations; range of magnitude, 0.004-0.24; mean, 0.09). AHI was not associated with self-reported sleepiness or general health, and it was associated with the SF-36 Health Status mental health domain only on multiple linear regression (P =.04) but not on multiple logistic regression (adjusted odds ratio, 1.02; 95% confidence interval, 1.00-1.04; P =.09). CONCLUSIONS: In general, PSG measures, and AHI in particular, correlated poorly with self-reported measures in a clinical sleep laboratory sample. After adjustment for potentially confounding variables, weak associations were found between some PSG indices and selected self-reported measures. These findings suggest that sleep apnea disease burden should be quantified with both physiologic and subjective measures.
BACKGROUND: While obstructive sleep apnea syndrome is defined by both polysomnographic (PSG) abnormalities and symptoms, severity is quantified primarily by the apnea-hypopnea index (AHI) alone. OBJECTIVE: To determine the correlation between standard PSG indices (AHI and others) and self-reported sleepiness, mental health status, and general health in patients with sleep apnea. DESIGN: Cross-sectional study. SETTING: University-affiliated outpatient sleep laboratory. PATIENTS: Ninety-six consecutive patients with PSG-confirmed sleep apnea (AHI >or=5). MEASUREMENTS: Patients completed a questionnaire that included the Epworth Sleepiness Scale, Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) mental health domain, and self-rated health on the evening of diagnostic PSG. Spearman correlation coefficients were computed. This sample had 85% power to detect a correlation of 0.3 or greater. The associations between PSG indices and self-reported measures were further assessed with multivariable regression techniques, adjusting for age, sex, body mass index, comorbidity, and PSG type. RESULTS: The PSG parameters correlated poorly with self-reported measures (15 correlations; range of magnitude, 0.004-0.24; mean, 0.09). AHI was not associated with self-reported sleepiness or general health, and it was associated with the SF-36 Health Status mental health domain only on multiple linear regression (P =.04) but not on multiple logistic regression (adjusted odds ratio, 1.02; 95% confidence interval, 1.00-1.04; P =.09). CONCLUSIONS: In general, PSG measures, and AHI in particular, correlated poorly with self-reported measures in a clinical sleep laboratory sample. After adjustment for potentially confounding variables, weak associations were found between some PSG indices and selected self-reported measures. These findings suggest that sleep apnea disease burden should be quantified with both physiologic and subjective measures.
Authors: Denise Christina Jarrin; Jennifer J McGrath; Janice E Silverstein; Christopher Drake Journal: Behav Sleep Med Date: 2012-11-08 Impact factor: 2.964
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