Obstructive Sleep Apnea: A Cluster Analysis at Time of Diagnosis.

ABSTRACT:

Background

The classification of obstructive sleep apnea is on the basis of sleep study criteria that may not adequately capture disease heterogeneity. Improved phenotyping may improve prognosis prediction and help select therapeutic strategies.

Objectives

This study used cluster analysis to investigate the clinical clusters of obstructive sleep apnea.

Methods

An ascending hierarchical cluster analysis was performed on baseline symptoms, physical examination, risk factor exposure and co-morbidities from 18,263 participants in the OSFP (French national registry of sleep apnea). The probability for criteria to be associated with a given cluster was assessed using odds ratios, determined by univariate logistic regression.

Results

Six clusters were identified, in w

SUBMITTER: Bailly S 

PROVIDER: S-EPMC4912165 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature