Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 May 6;65(5):2401883.
doi: 10.1183/13993003.01883-2024. Print 2025 May.

Heart rate response and cardiovascular risk during obstructive sleep apnoea: an easy biomarker derived from pulse oximetry

Margaux Blanchard  1   2 , Théo Imler  3   2 , Wen-Hsin Hu  4 , Adrien Waeber  3 , Geoffroy Solelhac  3 , José Haba-Rubio  3 , Sandrine Kerbrat  5 , Abdelkebir Sabil  1   6 , Wojciech Trzepizur  7 , François Goupil  8 , Audrey Thomas  9 , Sébastien Bailly  1   10 , Ali Azarbarzin  4 , Peter Vollenweider  11 , Pedro Marques-Vidal  11 , Julien Vaucher  11 , Raphael Heinzer  3   12 , Frédéric Gagnadoux  13   12
Affiliations

Heart rate response and cardiovascular risk during obstructive sleep apnoea: an easy biomarker derived from pulse oximetry

Margaux Blanchard et al. Eur Respir J. .

Abstract

Background: Sleep apnoea-specific heart rate response (ΔHR) has been identified as a promising biomarker for stratifying cardiovascular (CV) risk and predicting positive airway pressure (PAP) benefit in obstructive sleep apnoea (OSA). However, the need for prior manual scoring of respiratory events potentially limits the accessibility and reproducibility of ΔHR. We aimed to evaluate the association of pulse rate response to oxygen desaturations automatically derived from pulse oximetry (ΔHRoxi) with CV risk in OSA.

Methods: ΔHRoxi and ΔHR were measured in OSA patients from the Institut de Recherche en Santé Respiratoire Pays de la Loire Sleep Cohort (PLSC; n=5002) and the HypnoLaus cohort (n=1307). The primary outcome was major adverse CV events (MACEs), a composite of mortality, stroke and cardiac diseases. Cox regression analyses were conducted to evaluate the association of ΔHRoxi and ΔHR, categorised into low, midrange and high categories, with MACEs.

Results: MACEs occurred in 768 patients from PLSC and 87 patients from HypnoLaus (median follow-up 8.0 and 7.5 years, respectively). Multivariable Cox models showed that subjects with high ΔHRoxi (versus midrange) had higher risk of MACEs in PLSC (hazard ratio (HR) 1.42, 95% CI 1.18-1.71) and HypnoLaus (HR 1.72, 95% CI 1.03-2.87). Similar findings were observed for high ΔHR. Among 2718 patients from PLSC treated with PAP, the association of PAP adherence (PAP use ≥4 h·night-1 versus non-adherent) with MACEs was modified by baseline ΔHR and ΔHRoxi (pinteraction<0.05).

Conclusion: ΔHRoxi could constitute a reliable and easy to measure biomarker for stratifying CV risk and predicting CV benefit of PAP in OSA.

PubMed Disclaimer

Conflict of interest statement

Conflict of interest: M. Blanchard reports grants from CIDELEC and IRSR-PL. G. Solelhac reports grants from Ligue Pulmonaire Vaudoise, consultancy fees from Wellnest Retreats, payment or honoraria for lectures, presentations, manuscript writing or educational events from Idorsia and Wellnest Retreats, and participation on a data safety monitoring board or advisory board with Idorsia. A. Sabil is an employee of SEFAM Medical. W. Trzepizur reports payment or honoraria for lectures, presentations, manuscript writing or educational events from AstraZeneca and Biprojet, and support for attending meetings from Asten Santé. A. Thomas reports receipt of equipment, materials, drugs, medical writing, gifts or other services from CIDLE. S. Bailly reports receipt of equipment, materials, drugs, medical writing, gifts or other services from CIDLE. A. Azarbarzin reports grants from the American Heart Association, NIH, American Academy of Sleep Medicine and Somnifix, consultancy fees from Somnifix, ZOLL Respicardia, Eli Lilly, Apnimed, Inspire and Cerebra, payment or honoraria for lectures, presentations, manuscript writing or educational events from Philips Respironics, ProSomnus and the British Royal Society of Medicine, patents for “System and method for endo-phenotyping and risk stratifying obstructive sleep apnoea” and “Method, non-transitory computer readable medium and apparatus for arousal intensity scoring”, and receipt of equipment from Philips Respironics. P. Vollenweider reports support for the present manuscript from GSK. J. Vaucher reports grants from the Swiss National Science Foundation (grant 32473B-182210), Leenaards Foundation, University of Fribourg, Swiss Society of Internal Medicine and AGLA Foundation. R. Heinzer reports support for the present study from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne and the Swiss National Science Foundation (grants 33CSCO-122661, 33CS30-139468, 33CS30-148401, 33CS30_177535 and 3247730_204523), grants from Ligue Pulmonaire Vaudoise and Apnimed, consultancy fees from ResMed, Philips and Apnimed, and payment or honoraria for lectures, presentations, manuscript writing or educational events from ResMed, Jazz, Inspire, Bioprojet, Philips, Merck, Medtronic, Nestlé and Löwenstein. F. Gagnadoux reports support for the present study from ALTADIR and Institut Recherche en Santé Respiratoire des Pays de Loire (IRSR-PL), consultancy fees from ResMed, Inspire Medical, SEFAM, Bioprojet and Asten Santé, payment or honoraria for lectures, presentations, manuscript writing or educational events from ResMed, Inspire Medical, SEFAM, Bioprojet and CIDELEC, and support for attending meetings from ResMed, Inspire Medical, SEFAM and Bioprojet. The remaining authors have no potential conflicts of interest to disclose.

Figures

FIGURE 1
FIGURE 1
Illustration of post-event increases in a) heart rate (ΔHR) derived from manually scored sleep recording and b) heart rate response to oxygen desaturations (ΔHRoxi) automatically derived from single-channel pulse oximetry. Pink bars: manually scored obstructive events; blue bars: automatically detected oxygen desaturations. AU: arbitrary units. Also see supplementary figure S1 and supplementary material for details.
FIGURE 2
FIGURE 2
Flow diagram of the study populations: a) Pays de la Loire Sleep Cohort (PLSC) and b) HypnoLaus. PSG: polysomnography; HSAT: home sleep apnoea testing; OSA: obstructive sleep apnoea; SNDS: French administrative healthcare database; MACEs: major adverse cardiovascular events; AHI: apnoea–hypopnoea index; TST: total sleep time; TRT: total recording time; PAP: positive airway pressure.
FIGURE 3
FIGURE 3
Adjusted cumulative incidence curves showing the incidence of major adverse cardiovascular events (MACEs) according to oximetry-derived change in heart rate (ΔHRoxi) categories in a) Pays de la Loire Sleep Cohort (PLSC) and b) HypnoLaus, and according to ΔHR categories in c) PLSC and d) HypnoLaus. Data were adjusted for age, gender, body mass index, smoking status, medical history of diabetes, hypertension, dyslipidaemia, use of β-blockers and calcium channel blockers, event-related minimum pulse rate and sleep apnoea-specific hypoxic burden in PLSC and HypnoLaus, and for COPD, positive airway pressure (PAP) status (non-treated, PAP adherent or PAP non-adherent), study site and type of sleep study in PLSC. HR: hazard ratio.
FIGURE 4
FIGURE 4
Multivariable Cox regression analyses assessing the association of oximetry-derived change in heart rate (ΔHRoxi) with distinct incident non-fatal cardiovascular (CV) outcomes and all-cause mortality in the Pays de la Loire Sleep Cohort. Data were adjusted for age, gender, body mass index, smoking status, medical history of diabetes, hypertension, dyslipidaemia, COPD, use of β-blockers and calcium channel blockers, study site, type of sleep study, event-related minimum pulse rate, positive airway pressure (PAP) status (non-treated, PAP adherent or PAP non-adherent), sleep apnoea-specific hypoxic burden and the competing risk of death for non-fatal CV events. We used a Fine–Gray model to consider death as a competing event for non-fatal CV events. MACEs: major adverse cardiovascular events; CAD: coronary artery disease. *: p<0.05.
FIGURE 5
FIGURE 5
Adjusted cumulative incidence curves showing the incidence of major adverse cardiovascular events according to positive airway pressure adherence in patients with a) low or b) high oximetry-derived change in heart rate (ΔHRoxi) and those with c) low or d) high ΔHR in the Pays de la Loire Sleep Cohort. Data were adjusted for: age, gender, body mass index, smoking status, medical history of diabetes, hypertension, dyslipidaemia, COPD, use of β-blockers and calcium channel blockers, study site, type of sleep study and event-related minimum pulse rate and sleep apnoea-specific hypoxic burden.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Heinzer R, Vat S, Marques-Vidal P, et al. . Prevalence of sleep-disordered breathing in the general population: the HypnoLaus study. Lancet Respir Med 2015; 3: 310–318. doi:10.1016/S2213-2600(15)00043-0 - DOI - PMC - PubMed
    1. Benjafield AV, Ayas NT, Eastwood PR, et al. . Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respir Med 2019; 7: 687–698. doi:10.1016/S2213-2600(19)30198-5 - DOI - PMC - PubMed
    1. Cowie MR, Linz D, Redline S, et al. . Sleep disordered breathing and cardiovascular disease: JACC State-of-the-Art Review. J Am Coll Cardiol 2021; 78: 608–624. doi:10.1016/j.jacc.2021.05.048 - DOI - PubMed
    1. Dong J-Y, Zhang Y-H, Qin L-Q. Obstructive sleep apnea and cardiovascular risk: meta-analysis of prospective cohort studies. Atherosclerosis 2013; 229: 489–495. doi:10.1016/j.atherosclerosis.2013.04.026 - DOI - PubMed
    1. Redline S, Azarbarzin A, Peker Y. Obstructive sleep apnoea heterogeneity and cardiovascular disease. Nat Rev Cardiol 2023; 20: 560–573. doi:10.1038/s41569-023-00846-6 - DOI - PubMed

LinkOut - more resources