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Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea

BACKGROUND: Mechanisms underlying blood pressure changes in obstructive sleep apnoea (OSA) are incompletely understood. Increased respiratory effort is one of the main features of OSA and is associated with sympathetic overactivity, leading to increased vascular wall stiffness and remodelling. This...

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Autores principales: Martinot, Jean-Benoit, Le-Dong, Nhat-Nam, Malhotra, Atul, Pépin, Jean-Louis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: European Respiratory Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9978160/
https://www.ncbi.nlm.nih.gov/pubmed/36455958
http://dx.doi.org/10.1183/13993003.01486-2022
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author Martinot, Jean-Benoit
Le-Dong, Nhat-Nam
Malhotra, Atul
Pépin, Jean-Louis
author_facet Martinot, Jean-Benoit
Le-Dong, Nhat-Nam
Malhotra, Atul
Pépin, Jean-Louis
author_sort Martinot, Jean-Benoit
collection PubMed
description BACKGROUND: Mechanisms underlying blood pressure changes in obstructive sleep apnoea (OSA) are incompletely understood. Increased respiratory effort is one of the main features of OSA and is associated with sympathetic overactivity, leading to increased vascular wall stiffness and remodelling. This study investigated associations between a new measure of respiratory effort (percentage of total sleep time spent with increased respiratory effort based on measurement of mandibular jaw movements (MJM): REMOV, %TST) and prevalent hypertension in adults referred for evaluation of suspected OSA. METHODS: A machine learning model was built to predict hypertension from clinical data, conventional polysomnography (PSG) indices and MJM-derived parameters (including REMOV). The model was evaluated in a training subset and a test subset. RESULTS: The analysis included 1127 patients: 901 (80%) in the training subset and 226 (20%) in the test subset. The prevalence of hypertension was 31% and 30%, respectively, in the training and test subsets. A risk stratification model based on 18 input features including REMOV had good accuracy for predicting prevalent hypertension (sensitivity 0.75 and specificity 0.83). Using the Shapley additive explanation method, REMOV was the best predictor of hypertension after clinical risk factors (age, sex, body mass index and neck circumference) and time with oxygen saturation <90%, ahead of standard PSG metrics (including the apnoea–hypopnoea index and oxygen desaturation index). CONCLUSION: The proportion of sleep time spent with increased respiratory effort automatically derived from MJM was identified as a potential new reliable metric to predict prevalent hypertension in patients with OSA.
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spelling pubmed-99781602023-03-03 Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea Martinot, Jean-Benoit Le-Dong, Nhat-Nam Malhotra, Atul Pépin, Jean-Louis Eur Respir J Original Research Articles BACKGROUND: Mechanisms underlying blood pressure changes in obstructive sleep apnoea (OSA) are incompletely understood. Increased respiratory effort is one of the main features of OSA and is associated with sympathetic overactivity, leading to increased vascular wall stiffness and remodelling. This study investigated associations between a new measure of respiratory effort (percentage of total sleep time spent with increased respiratory effort based on measurement of mandibular jaw movements (MJM): REMOV, %TST) and prevalent hypertension in adults referred for evaluation of suspected OSA. METHODS: A machine learning model was built to predict hypertension from clinical data, conventional polysomnography (PSG) indices and MJM-derived parameters (including REMOV). The model was evaluated in a training subset and a test subset. RESULTS: The analysis included 1127 patients: 901 (80%) in the training subset and 226 (20%) in the test subset. The prevalence of hypertension was 31% and 30%, respectively, in the training and test subsets. A risk stratification model based on 18 input features including REMOV had good accuracy for predicting prevalent hypertension (sensitivity 0.75 and specificity 0.83). Using the Shapley additive explanation method, REMOV was the best predictor of hypertension after clinical risk factors (age, sex, body mass index and neck circumference) and time with oxygen saturation <90%, ahead of standard PSG metrics (including the apnoea–hypopnoea index and oxygen desaturation index). CONCLUSION: The proportion of sleep time spent with increased respiratory effort automatically derived from MJM was identified as a potential new reliable metric to predict prevalent hypertension in patients with OSA. European Respiratory Society 2023-03-02 /pmc/articles/PMC9978160/ /pubmed/36455958 http://dx.doi.org/10.1183/13993003.01486-2022 Text en Copyright ©The authors 2023. https://creativecommons.org/licenses/by-nc/4.0/This version is distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0. For commercial reproduction rights and permissions contact permissions@ersnet.org (mailto:permissions@ersnet.org)
spellingShingle Original Research Articles
Martinot, Jean-Benoit
Le-Dong, Nhat-Nam
Malhotra, Atul
Pépin, Jean-Louis
Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea
title Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea
title_full Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea
title_fullStr Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea
title_full_unstemmed Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea
title_short Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea
title_sort respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea
topic Original Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9978160/
https://www.ncbi.nlm.nih.gov/pubmed/36455958
http://dx.doi.org/10.1183/13993003.01486-2022
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