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BioMed Research International
Volume 2015, Article ID 103686, 9 pages
Clinical Study

Prevalence and Diagnostic Approach to Sleep Apnea in Hemodialysis Patients: A Population Study

1Department of Nephrology and Hypertension, University Hospital of Lausanne (CHUV), 1011 Lausanne, Switzerland
2Centre for Investigation and Research in Sleep (CIRS), University Hospital of Lausanne (CHUV), 1011 Lausanne, Switzerland
3Hemodialysis Unit, Northern Vaud Hospital, 1400 Yverdon, Switzerland
4Hemodialysis Unit, Broye Intercantonal Hospital, 1530 Payerne, Switzerland
5Hemodialysis Unit, EHC Hospital, 1110 Morges, Switzerland
6Hemodialysis Unit, Riviera Providence Hospital, 1800 Vevey, Switzerland
7Hemodialysis Unit, Cecil Clinic, 1011 Lausanne, Switzerland

Received 17 March 2015; Accepted 16 June 2015

Academic Editor: Nikolaos Siafakas

Copyright © 2015 Valentina Forni Ogna et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. Previous observations found a high prevalence of obstructive sleep apnea (OSA) in the hemodialysis population, but the best diagnostic approach remains undefined. We assessed OSA prevalence and performance of available screening tools to propose a specific diagnostic algorithm. Methods. 104 patients from 6 Swiss hemodialysis centers underwent polygraphy and completed 3 OSA screening scores: STOP-BANG, Berlin’s Questionnaire, and Adjusted Neck Circumference. The OSA predictors were identified on a derivation population and used to develop the diagnostic algorithm, which was validated on an independent population. Results. We found 56% OSA prevalence (AHI ≥ 15/h), which was largely underdiagnosed. Screening scores showed poor performance for OSA screening (ROC areas 0.538 [SE 0.093] to 0.655 [SE 0.083]). Age, neck circumference, and time on renal replacement therapy were the best predictors of OSA and were used to develop a screening algorithm, with higher discriminatory performance than classical screening tools (ROC area 0.831 [0.066]). Conclusions. Our study confirms the high OSA prevalence and highlights the low diagnosis rate of this treatable cardiovascular risk factor in the hemodialysis population. Considering the poor performance of OSA screening tools, we propose and validate a specific algorithm to identify hemodialysis patients at risk for OSA for whom further sleep investigations should be considered.