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Obstructive Sleep Apnea is a Risk Factor for Incident COVID-19 Infection.

Stuart F QuanMatthew D WeaverMark É CzeislerLaura K BargerLauren A BookerMark E HowardMelinda L JacksonChristine Faye McDonaldAnna RidgersRebecca RobbinsPrerna VarmaShantha M W RajaratnamCharles A Czeisler
Published in: medRxiv : the preprint server for health sciences (2024)
Cross-sectional studies suggest that obstructive sleep apnea (OSA) is a potential risk factor for incident COVID-19 infection, but longitudinal studies are lacking. In this study, two surveys from a large general population cohort, the COVID-19 Outbreak Public Evaluation (COPE) Initiative, undertaken 147 ± 58 days apart were analyzed to determine whether the pre-existing OSA was a risk factor for the incidence of COVID-19. Of the 24,803 respondents completing the initial survey, 14,950 were negative for COVID-19; data from the follow-up survey were available for 2,325 respondents. Those with incident COVID-19 infection had a slightly higher prevalence of OSA (14.3 vs. 11.5%, p=0.068). Stratification by treatment status revealed that those untreated for their OSA were at greater risk for developing COVID-19 infection (OSA Untreated, 14.2 vs. 7.4%, p≤0.05). In a logistic regression model adjusted for comorbidities, demographic and socioeconomic factors and the interaction between vaccination status and OSA, incident COVID-19 infection was 2.15 times more likely in those with untreated OSA (aOR: 2.15, 95% CI: 1.18-3.92, p≤0.05). Stratification by treatment status revealed only untreated OSA participants were at greater risk for COVID-19 (aOR: 3.21, 95% CI: 1.25-8.23, p≤0.05). The evidence from this study confirms untreated OSA as a risk factor for acquiring COVID-19 infection and highlights the importance of actively treating and managing OSA as a preventative mechanism against COVID-19 disease.
Keyphrases
  • obstructive sleep apnea
  • positive airway pressure
  • cross sectional
  • coronavirus disease
  • sars cov
  • sleep apnea
  • cardiovascular disease
  • single cell
  • emergency department
  • risk assessment
  • big data