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

Détails

Ressource 1Télécharger: 103686.pdf (1364.10 [Ko])
Etat: Public
Version: Final published version
ID Serval
serval:BIB_FD7B90AC94CA
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Prevalence and Diagnostic Approach to Sleep Apnea in Hemodialysis Patients: A Population Study.
Périodique
Biomed Research International
Auteur(s)
Forni Ogna V., Ogna A., Pruijm M., Bassi I., Zuercher E., Halabi G., Phan O., Bullani R., Teta D., Gauthier T., Cherpillod A., Mathieu C., Mihalache A., Cornette F., Haba-Rubio J., Burnier M., Heinzer R.
ISSN
2314-6141 (Electronic)
Statut éditorial
Publié
Date de publication
2015
Volume
2015
Pages
103686
Langue
anglais
Notes
Publication types: Journal Article ; Multicenter Study ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Résumé
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.
Mots-clé
Aged, Female, Humans, Logistic Models, Male, Middle Aged, Multivariate Analysis, Prevalence, ROC Curve, Renal Dialysis, Sleep Apnea, Obstructive/diagnosis, Sleep Apnea, Obstructive/epidemiology, Switzerland/epidemiology
Pubmed
Web of science
Open Access
Oui
Création de la notice
14/01/2016 10:22
Dernière modification de la notice
20/08/2019 17:28
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