Highlights
- •Severe OSAS is associated with increased comorbid burden and all-cause mortality.
- •The prognostic role of comorbidity remains poorly defined.
- •Age and comorbidity are crucial contributors to increased mortality in severe OSAS.
- •Clustering of comorbidities allows identify clinically meaningful phenotypes
Abstract
Background
Obstructive sleep apnoea syndrome (OSAS) is a highly prevalent disorder. The prognostic
role of comorbidity in patients with OSAS and their role for risk stratification remain
poorly defined.
Methods
We studied 1,592 patients with severe OSAS diagnosed by polysomnography. The primary
outcome was all-cause mortality. The standardized mortality ratio (SMR) was estimated
as the ratio of observed deaths to expected number of deaths in the general population.
The expected numbers of deaths were derived using mortality rates from the general
Apulian population. The association of comorbidities with all-cause mortality was
assessed using multivariable Cox regression analysis. Finally, recursive-partitioning
analysis was applied to identify the combinations of comorbidities that were most
influential for mortality and to cluster the patients into risk groups according to
individual comorbidities
Results
During 11,721 person-years of follow-up, 390 deaths (3.33 deaths/100 person-years)
occurred. The median follow-up was 7 (4–10) years. The SMR was 1.47 (95% confidence
intervals 1.33–1.63). Age, sex, obesity, cardiovascular diseases (CVD), moderate-to-severe
chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD) and malignancy
were independently associated with mortality risk. Recursive-partitioning analysis
allowed distinguishing three clinical phenotypes differentially associated with mortality
risk. The combination of CKD with CVDs or with moderate-to-severe COPD conferred the
highest risk.
Conclusions
Severe OSAS is associated with increased risk for all-cause death. Age and comorbidity
are crucial predictors of mortality in patients with severe OSAS. Clustering patients
according to comorbidities allows identifying clinically meaningful phenotypes.
Keywords
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Article info
Publication history
Published online: May 09, 2021
Accepted:
April 15,
2021
Received in revised form:
April 10,
2021
Received:
December 1,
2020
Identification
Copyright
© 2021 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.
