Study Objectives: This study aimed to quantify the impact of excessive daytime sleepiness (EDS) on patient and patient's partner health-related quality of life in the form of utility values typically used in health economic evaluations.
Methods: A time trade-off study was conducted in a UK general population sample (representing a societal perspective) to elicit utility values, measured on a 0 to 1 scale, for health states with varying obstructive sleep apnea-associated EDS severity. In a time trade-off study, health states are described, and participants "trade off" time in a specific higher severity state for a shorter amount of time in full health.
Results: Overall, the sample consisted of 104 participants, who were interviewed and took part in the time trade-off exercise to elicit utility values for patient and partner residual EDS health states. The average utility score declined with increasing obstructive sleep apnea-associated EDS severity for both patient (no EDS, 0.926; mild EDS, 0.794; moderate EDS, 0.614; severe EDS, 0.546) and partner (no EDS, 0.955; mild EDS, 0.882; moderate EDS, 0.751; severe EDS, 0.670) health states.
Conclusions: These results demonstrate the high impact that EDS in obstructive sleep apnea is estimated to have on patient and partner health-related quality of life.
Citation: Tolley K, Noble-Longster J, Mettam S, et al. Exploring the impact of excessive daytime sleepiness caused by obstructive sleep apnea on patient and partner quality of life: a time trade-off utility study in the UK general public. . 2022;18(9):2237-2246.
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http://dx.doi.org/10.5664/jcsm.10092 | DOI Listing |
PLoS One
January 2025
Department of Otolaryngology-Head and Neck Surgery, Virginia Commonwealth University, Richmond, Virginia, United States of America.
To assess the impact of resident involvement and resident postgraduate year (PGY) on head and neck obstructive sleep apnea (OSA) surgical outcomes. We analyzed head and neck OSA surgeries from 2005-2012 via the National Surgical Quality Improvement Program database. Demographic, preoperative, and postoperative variables were analyzed via multivariate regression to determine the impact of resident involvement and resident PGY on 30-day outcomes.
View Article and Find Full Text PDFJ Basic Clin Physiol Pharmacol
January 2025
Pharmacology, MGM Medical College and Hospital, MGM Institute of Health Sciences, Nerul, Navi Mumbai, Maharashtra, India.
Obstructive Sleep Apnea (OSA) is a prevalent sleep disorder marked by repeated episodes of partial or complete upper airway obstruction during sleep, which leads to intermittent hypoxia and fragmented sleep. These disruptions negatively impact cardiovascular health, metabolic function, and overall quality of life. Obesity is a major modifiable risk factor for OSA, as it contributes to both anatomical and physiological mechanisms that increase the likelihood of airway collapse during sleep.
View Article and Find Full Text PDFSleep Breath
January 2025
Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Background And Objective: There is no satisfactory treatment for obstructive sleep apnea (OSA) in patients with interstitial lung disease (ILD) because of poor tolerance of positive airway pressure (PAP) therapy. Supplemental oxygen therapy has been shown to reduce hypoxemia and is well tolerated in patients with ILD. However, little is known about the effect of nocturnal oxygen supplementation (NOS) on OSA in patients with ILD.
View Article and Find Full Text PDFSleep Breath
January 2025
Department of Respiratory and Critical Care Medicine, Medical School of Nantong University, Nantong Key Laboratory of Respiratory Medicine, Affiliated Hospital of Nantong University, Nantong, 226001, China.
Background: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still unknown, despite clinical reports linking the two conditions. After investigating potential roles for DM-related genes in the pathophysiology of OSA, our goal is to investigate the molecular significance of the condition. Machine learning is a useful approach to understanding complex gene expression data to find biomarkers for the diagnosis of OSA.
View Article and Find Full Text PDFSleep
January 2025
Santa Barbara Actuaries Inc., Santa Barbara, CA, USA.
Study Objectives: To determine the association between adherence to positive airway pressure and healthcare costs among a national sample of older adults with comorbid OSA and common chronic conditions.
Methods: Our data source was a random sample of Medicare administrative claims for years 2016-2019. Inclusion criteria included age >65 years and new diagnosis of OSA.
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