Dataset Information

Sleep in Chronic Obstructive Pulmonary Disease: Evidence Gaps and Challenges.

ABSTRACT: Chronic obstructive pulmonary disease (COPD) prevalence is rising to epidemic proportions due to historical smoking trends, the aging of the population, and air pollution. Although blaming the victims has been common in COPD, the majority of COPD worldwide is now thought to be nonsmoking related, that is, caused by air pollution and cookstove exposure. It is increasingly appreciated that subjective and objective sleep disturbances are common in COPD, although strong epidemiological data are lacking. People with obstructive sleep apnea (OSA) plus COPD (the so-called overlap syndrome) have a high risk of cardiovascular death, although again mechanisms are unknown and untested. This review aims to draw attention to the problem of sleep in COPD, to encourage clinicians to ask their patients about symptoms, and to stimulate further research in this area given the large burden of the disease.

SUBMITTER: Jen R

PROVIDER: S-EPMC4916278 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Sleep in Chronic Obstructive Pulmonary Disease: Evidence Gaps and Challenges.

Jen Rachel R Li Yanru Y Owens Robert L RL Malhotra Atul A

Canadian respiratory journal 20160608

Chronic obstructive pulmonary disease (COPD) prevalence is rising to epidemic proportions due to historical smoking trends, the aging of the population, and air pollution. Although blaming the victims has been common in COPD, the majority of COPD worldwide is now thought to be nonsmoking related, that is, caused by air pollution and cookstove exposure. It is increasingly appreciated that subjective and objective sleep disturbances are common in COPD, although strong epidemiological data are lack ...[more]

PMID: 27445564

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Project description:BACKGROUND AND HYPOTHESIS: Heterogeneity in clinical manifestations and disease progression in Chronic Obstructive Pulmonary Disease (COPD) lead to consequences for patient health risk assessment, stratification and management. Implicit with the classical "spill over" hypothesis is that COPD heterogeneity is driven by the pulmonary events of the disease. Alternatively, we hypothesized that COPD heterogeneities result from the interplay of mechanisms governing three conceptually different phenomena: 1) pulmonary disease, 2) systemic effects of COPD and 3) co-morbidity clustering, each of them with their own dynamics. OBJECTIVE AND METHOD: To explore the potential of a systems analysis of COPD heterogeneity focused on skeletal muscle dysfunction and on co-morbidity clustering aiming at generating predictive modeling with impact on patient management. To this end, strategies combining deterministic modeling and network medicine analyses of the Biobridge dataset were used to investigate the mechanisms of skeletal muscle dysfunction. An independent data driven analysis of co-morbidity clustering examining associated genes and pathways was performed using a large dataset (ICD9-CM data from Medicare, 13 million people). Finally, a targeted network analysis using the outcomes of the two approaches (skeletal muscle dysfunction and co-morbidity clustering) explored shared pathways between these phenomena. RESULTS: (1) Evidence of abnormal regulation of skeletal muscle bioenergetics and skeletal muscle remodeling showing a significant association with nitroso-redox disequilibrium was observed in COPD; (2) COPD patients presented higher risk for co-morbidity clustering than non-COPD patients increasing with ageing; and, (3) the on-going targeted network analyses suggests shared pathways between skeletal muscle dysfunction and co-morbidity clustering. CONCLUSIONS: The results indicate the high potential of a systems approach to address COPD heterogeneity. Significant knowledge gaps were identified that are relevant to shape strategies aiming at fostering 4P Medicine for patients with COPD.

Dataset Information

Sleep in Chronic Obstructive Pulmonary Disease: Evidence Gaps and Challenges.

Publications

Sleep in Chronic Obstructive Pulmonary Disease: Evidence Gaps and Challenges.

Similar Datasets

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