Multidimensional phenotyping to distinguish among distinct obstructive sleep apnea, chronic obstructive pulmonary disease, and overlap syndrome phenotypes

<bold>Background:</bold> Chronic obstructive pulmonary disease (COPD), obstructive sleep apnea (OSA) and their comorbid association Overlap Syndrome (OS) are frequent chronic diseases leading to a high individual and societal burden. There is a lack of precise description of the respective symptoms, comorbidities, and medications associated with these three conditions. <bold>Objective:</bold> To identify relevant phenotypes characterizing these 3 disorders. <bold>Methods:</bold> 308 patients with OSA, COPD and OS were prospectively assessed by a combination of body shape dimensions and multidimensional questionnaires. Comorbidities and medications were substantiated by physicians. 210 patients completed home blood pressure self-measurement with a wearable device for identifying undiagnosed or uncontrolled hypertension. <bold>Results:</bold> Three distinct relevant phenotypes were depicted in Figure 1. Furthermore, home blood pressure measurements via wearable device identified undiagnosed hypertension in 80% of patients and nearly 80% of hypertensive patients uncontrolled by their current medications. <bold>Conclusion:</bold> Our systematic multidimensional phenotyping approach has enabled identification of body shape dimensions, symptoms, and comorbidity profiles corresponding to the distinct relevant phenotypes of patients with OSA, COPD, and OS. <fig><object-id>erj;64/suppl_68/PA2692/F1</object-id><object-id>F1</object-id><object-id>F1</object-id><graphic></graphic></fig>

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Publication Details

Journal
Sleep Science
Published
2024-09-14
DOI
https://doi.org/10.1183/13993003.congress-2024.pa2692
Primary Topic
Delphi Technique in Research
Type
article
Field-Weighted Citation Impact
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article

Multidimensional phenotyping to distinguish among distinct obstructive sleep apnea, chronic obstructive pulmonary disease, and overlap syndrome phenotypes

Robin Terrail, Jean-Claude Cornu, Ophélie Coiffier, Marie Joyeux‐Faure et al.
Sleep Science
Delphi Technique in Research
article

Multidimensional phenotyping to distinguish among distinct obstructive sleep apnea, chronic obstructive pulmonary disease, and overlap syndrome phenotypes

Robin Terrail, Jean-Claude Cornu, Ophélie Coiffier, Marie Joyeux‐Faure, Jean‐Louis Pépin, Pasquale Tondo, Khier Amrani, Christian Caussé, Renaud Tamisier, Sébastien Bailly
article en

Abstract

<bold>Background:</bold> Chronic obstructive pulmonary disease (COPD), obstructive sleep apnea (OSA) and their comorbid association Overlap Syndrome (OS) are frequent chronic diseases leading to a high individual and societal burden. There is a lack of precise description of the respective symptoms, comorbidities, and medications associated with these three conditions. <bold>Objective:</bold> To identify relevant phenotypes characterizing these 3 disorders. <bold>Methods:</bold> 308 patients with OSA, COPD and OS were prospectively assessed by a combination of body shape dimensions and multidimensional questionnaires. Comorbidities and medications were substantiated by physicians. 210 patients completed home blood pressure self-measurement with a wearable device for identifying undiagnosed or uncontrolled hypertension. <bold>Results:</bold> Three distinct relevant phenotypes were depicted in Figure 1. Furthermore, home blood pressure measurements via wearable device identified undiagnosed hypertension in 80% of patients and nearly 80% of hypertensive patients uncontrolled by their current medications. <bold>Conclusion:</bold> Our systematic multidimensional phenotyping approach has enabled identification of body shape dimensions, symptoms, and comorbidity profiles corresponding to the distinct relevant phenotypes of patients with OSA, COPD, and OS. <fig><object-id>erj;64/suppl_68/PA2692/F1</object-id><object-id>F1</object-id><object-id>F1</object-id><graphic></graphic></fig>

Sleep Science
Inserm (FR), Centre Hospitalier Universitaire de Grenoble (FR), Bureau Veritas (France) (FR), Hôpital Couple Enfant (FR), Iltoo Pharma (France) (FR), Université Grenoble Alpes (FR)
Openalex Percentile: Top 69%
Delphi Technique in Research
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