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


OBJECTIVE
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 which patients varied considerably in age, sex, symptoms, obesity, co-morbidities and environmental risk factors. The main significant differences between clusters were minimally symptomatic versus sleepy obstructive sleep apnea patients, lean versus obese, and among obese patients different combinations of co-morbidities and environmental risk factors.


CONCLUSIONS
Our cluster analysis identified six distinct clusters of obstructive sleep apnea. Our findings underscore the high degree of heterogeneity that exists within obstructive sleep apnea patients regarding clinical presentation, risk factors and consequences. This may help in both research and clinical practice for validating new prevention programs, in diagnosis and in decisions regarding therapeutic strategies.
Univ. Grenoble Alpes, HP2; Inserm, U1042, Grenoble, France.|IAME UMR 1137 Inserm Université Paris Diderot, F-75018, Paris, France.
Sébastien
S
Bailly
Univ. Grenoble Alpes, HP2; Inserm, U1042, Grenoble, France.|Grenoble- Alpes University Hospital, Laboratoire EFCR, Pôle THORAX et VAISSEAUX, Grenoble, France.
Marie
M
Destors
Pneumologist, Private Clinic, Valence, France.
Yves
Y
Grillet
Pneumologist, Private Clinic, St-Omer, France.
Philippe
P
Richard
Pneumologist, Saint Michel Private Clinic, Valenciennes, France.
Bruno
B
Stach
Univ. Grenoble Alpes, HP2; Inserm, U1042, Grenoble, France.
Isabelle
I
Vivodtzev
IAME UMR 1137 Inserm Université Paris Diderot, F-75018, Paris, France.|Medical and Infectious Diseases ICU - Paris Diderot University / Bichat Hospital, Paris, France.
Jean-Francois
JF
Timsit
Univ. Grenoble Alpes, HP2; Inserm, U1042, Grenoble, France.|Grenoble- Alpes University Hospital, Laboratoire EFCR, Pôle THORAX et VAISSEAUX, Grenoble, France.
Patrick
P
Lévy
Univ. Grenoble Alpes, HP2; Inserm, U1042, Grenoble, France.|Grenoble- Alpes University Hospital, Laboratoire EFCR, Pôle THORAX et VAISSEAUX, Grenoble, France.
Renaud
R
Tamisier
Univ. Grenoble Alpes, HP2; Inserm, U1042, Grenoble, France.|Grenoble- Alpes University Hospital, Laboratoire EFCR, Pôle THORAX et VAISSEAUX, Grenoble, France.
Jean-Louis
JL
Pépin
D000328:Adult; D000368:Aged; D001794:Blood Pressure; D015992:Body Mass Index; D005260:Female; D006801:Humans; D006973:Hypertension / Q000150:complications / Q000175:diagnosis / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000150:complications / Q000503:physiopathology*; D017286:Polysomnography; D011379:Prognosis; D012307:Risk Factors; D012720:Severity of Illness Index; D012890:Sleep / Q000502:physiology*; D020181:Sleep Apnea, Obstructive / Q000150:complications / Q000175:diagnosis* / Q000503:physiopathology*; D012894:Sleep Stages