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O073 Traditional Clinical and Novel Oximetry Measures as Predictors of Cardiovascular Events
INTRODUCTION: Intermittent hypoxia is a key mechanism linking Obstructive Sleep Apnoea (OSA) to cardiovascular disease (CVD). Oximetry analysis could enhance understanding of which OSA phenotypes are associated with CVD risk. We investigated if traditional clinical and novel oximetry measures includ...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10109259/ http://dx.doi.org/10.1093/sleepadvances/zpac029.072 |
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author | de Chazal, P Sutherland, K Bin, Y Cook, K Cistulli, P |
author_facet | de Chazal, P Sutherland, K Bin, Y Cook, K Cistulli, P |
author_sort | de Chazal, P |
collection | PubMed |
description | INTRODUCTION: Intermittent hypoxia is a key mechanism linking Obstructive Sleep Apnoea (OSA) to cardiovascular disease (CVD). Oximetry analysis could enhance understanding of which OSA phenotypes are associated with CVD risk. We investigated if traditional clinical and novel oximetry measures including hypoxic burden (HB) calculated from the polysomnogram SpO2 signal can predict CVD outcomes in all-comers and OSA subsample cohorts from the Sleep Heart Health Study (SHHS). METHODS: CVD mortality outcome and complete covariate information was used. We implemented 31 oximetry measures and assessed the performance of the parameters in predicting CVD outcomes (CVD death or incident CVD) in the all-comers and sleep apnoea subsamples. The performance of each measure was assessed using an adjusted Cox proportional hazard ratio (HR) analysis. RESULTS: In the general subsample, HB successfully predicted CVD death (HR>1.8, p<0.05) but did not predict incident CVD. In the sleep apnoea subsample (AHI>5) with no CVD at baseline, none of the SpO2 measures we considered predicted incident CVD. DISCUSSION: The ability of HB to predict CVD outcomes depends on the cohort and the CVD outcome. Our analysis of the selected SpO2 measures in an OSA subsample did not find strong links between any oximetry measures and incident CVD, and therefore no strong candidates for CVD risk phenotyping in the sleep clinic. Further work is needed to understand the complex relationship between OSA-related intermittent hypoxia patterns and development of CVD to further understanding of OSA phenotypes at risk of CVD consequences. |
format | Online Article Text |
id | pubmed-10109259 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-101092592023-05-15 O073 Traditional Clinical and Novel Oximetry Measures as Predictors of Cardiovascular Events de Chazal, P Sutherland, K Bin, Y Cook, K Cistulli, P Sleep Adv ORAL PRESENTATIONS INTRODUCTION: Intermittent hypoxia is a key mechanism linking Obstructive Sleep Apnoea (OSA) to cardiovascular disease (CVD). Oximetry analysis could enhance understanding of which OSA phenotypes are associated with CVD risk. We investigated if traditional clinical and novel oximetry measures including hypoxic burden (HB) calculated from the polysomnogram SpO2 signal can predict CVD outcomes in all-comers and OSA subsample cohorts from the Sleep Heart Health Study (SHHS). METHODS: CVD mortality outcome and complete covariate information was used. We implemented 31 oximetry measures and assessed the performance of the parameters in predicting CVD outcomes (CVD death or incident CVD) in the all-comers and sleep apnoea subsamples. The performance of each measure was assessed using an adjusted Cox proportional hazard ratio (HR) analysis. RESULTS: In the general subsample, HB successfully predicted CVD death (HR>1.8, p<0.05) but did not predict incident CVD. In the sleep apnoea subsample (AHI>5) with no CVD at baseline, none of the SpO2 measures we considered predicted incident CVD. DISCUSSION: The ability of HB to predict CVD outcomes depends on the cohort and the CVD outcome. Our analysis of the selected SpO2 measures in an OSA subsample did not find strong links between any oximetry measures and incident CVD, and therefore no strong candidates for CVD risk phenotyping in the sleep clinic. Further work is needed to understand the complex relationship between OSA-related intermittent hypoxia patterns and development of CVD to further understanding of OSA phenotypes at risk of CVD consequences. Oxford University Press 2022-11-09 /pmc/articles/PMC10109259/ http://dx.doi.org/10.1093/sleepadvances/zpac029.072 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | ORAL PRESENTATIONS de Chazal, P Sutherland, K Bin, Y Cook, K Cistulli, P O073 Traditional Clinical and Novel Oximetry Measures as Predictors of Cardiovascular Events |
title | O073 Traditional Clinical and Novel Oximetry Measures as Predictors of Cardiovascular Events |
title_full | O073 Traditional Clinical and Novel Oximetry Measures as Predictors of Cardiovascular Events |
title_fullStr | O073 Traditional Clinical and Novel Oximetry Measures as Predictors of Cardiovascular Events |
title_full_unstemmed | O073 Traditional Clinical and Novel Oximetry Measures as Predictors of Cardiovascular Events |
title_short | O073 Traditional Clinical and Novel Oximetry Measures as Predictors of Cardiovascular Events |
title_sort | o073 traditional clinical and novel oximetry measures as predictors of cardiovascular events |
topic | ORAL PRESENTATIONS |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10109259/ http://dx.doi.org/10.1093/sleepadvances/zpac029.072 |
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