Correspondence to Pauline Balagny; [email protected]
STRENGTHS AND LIMITATIONS OF THIS STUDY
The first large prognostic prospective study in France on this subject taking advantage of the implementation of the Innovations in Atherothrombosis Science (iVASC)/French Cohort of Myocardial Infarction Evaluation registry.
Exhaustive data collection through the National Health Data System follow-up.
Minor risk related to polygraphy with a significant benefit if sleep-disordered breathing/sleep apnoea syndrome (SAS) is diagnosed.
An economic evaluation embedded in this multicentre study, addressing the cost-benefit and cost-utility of systematic SAS screening and treatment on health resource consumption.
Use of simplified polygraphy rather than polysomnography is a limitation, but central scoring is a strength.
Introduction
Sleep-disordered breathing (SDB) is defined by the occurrence of more than five episodes of apnoea (complete cessation of breathing) or hypopnoea (a ≥30% reduction in airflow during sleep for ≥10 s) during sleep— known as the apnoea-hypopnoea index (AHI).1 Sleep apnoea syndrome (SAS) refers to SDB that is associated with clinical symptoms, which can include excessive daytime sleepiness, unrefreshing sleep, fatigue or insomnia, awakenings with a choking sensation, witnessed heavy snoring and/or breathing pauses, and nycturia.2
SDB is highly prevalent, affecting 4% of males and 2% of females according to a seminal study.3 Prevalence rates have reached 50% in men and 23% in women in more recent studies.4 5 SDB and SAS are particularly common in individuals with ischaemic heart disease, with a prevalence rate of up to 83%.6–8 Furthermore, SDB/SAS often remain undiagnosed even after admission for an acute myocardial infarction (AMI).9
Studies suggested that coexisting SDB influences outcomes after acute coronary syndrome (ACS)10–12 or after percutaneous coronary intervention,13 14 but most were Asian studies, and few data are available in Europe. Furthermore, the pathophysiology of ACS seems to differ from that of stable angina, mainly due to specific features of the atherosclerotic plaque.15 The elevated cardiovascular risk associated with ACS is caused by the loss of integrity of the protective covering of some atherosclerotic plaques, due to erosion or rupture of the fibrous cap, and leading to thrombus formation and subsequent vessel obstruction.16 Both sleep apnoea and sleep disruption have been associated with an imbalance in circulatory thrombotic and antithrombotic activity17 but also oxidative stress, inflammatory response, endothelial dysfunction as well as sympathetic activation18 19 that induce insulin resistance,20–22 hypertension23–25 and dyslipidaemia,26 27 the major risk factors for atherothrombosis which worsens cardiovascular prognosis in SDB patients.19 However, currently available evidence linking the presence and severity of sleep apnoea to increased mortality and cardiovascular morbidity in individuals with established or unstable coronary artery disease (CAD) is conflicting and inconclusive.6 7 28–32 Furthermore, it is not yet clear whether these findings represent coincidence or causality. Specifically, does SDB contribute to cardiovascular disease progression and triggering of cardiovascular events? This issue is critical: if the cardiovascular risk associated with SDB in individuals with CAD/ACS is modifiable, then effective treatment of SDB offers the possibility of a new cardiovascular preventive treatment in this setting.
The French Cohort of Myocardial Infarction Evaluation (FRENCHIE) is an ongoing, prospective nationwide multicentre registry that enrols all consecutive eligible patients with AMI who have been admitted to the hospital within 48 hours of symptom onset (NCT04050956). The current study (AMI-Sleep) addresses a subset of individuals enrolled in FRENCHIE in selected centres and willing to perform polysomnography and investigated associations between the presence and severity of SDB/SAS and the occurrence of cardiovascular events and all-cause mortality in the first year after AMI.
Methods and analysis
Study design and setting
AMI-Sleep is a prospective study that uses data from the iVASC/FRENCHIE cohort (iVASC is a consortium of researchers, clinicians and businesses that aims to study the role of oral health and SDB in atherothrombosis). The study is being conducted in France and has an enrolment period of 4 years and a total study duration of 5 years to assess primary endpoint 1 year after discharge. Inclusion started in January 2019 with the expected publication of primary outcome results in 2025. The study design schematic is provided in figure 1.
Enlarge this image.Figure 1. Study design schematic. AMI, acute myocardial infarction; SAS, sleep apnoea syndrome; SDB, sleep-disordered breathing; SNDS, National Health Data System.
Eligibility criteria
All patients hospitalised for AMI occurring within 48 hours of symptom onset, whether with ST-segment elevation myocardial infarction or non-ST-segment elevation myocardial infarction, are eligible in the FRENCHIE registry (further information about the selection of the study population is detailed in the rationale of the FRENCHIE cohort previously published33).
All individuals enrolled in FRENCHIE in AMI-Sleep-trained centres are eligible. Those who have received treatment for SDB/SAS prior to inclusion in FRENCHIE, those with cognitive disorders or communication difficulties that would prevent them from completing questionnaires (in the opinion of the investigator), and those with a life expectancy of ≤6 months are excluded. The study flow diagram is presented in figure 2.
Enlarge this image.Figure 2. Study flow diagram. AMI, acute myocardial infarction; SAS, sleep apnoea syndrome; SDB, sleep-disordered breathing.
Interventions
In addition to management based on routine clinical care, participants will be evaluated using cardiorespiratory polygraphy during the initial hospitalisation for AMI and complete several questionnaires (see below for details).
Outcomes
The primary outcome is the association between the type and severity of SDB/SAS and the rate of incident cardiovascular events, cardiovascular deaths and all-cause mortality after AMI. A cardiovascular event is defined as an incident of ACS, stroke or cardiovascular death (HR and 95% CI). The time elapsed from discharge to the first event will be recorded. The type and severity of SDB will be determined based on data from cardiorespiratory polygraphy (including the AHI; see below for details).
Secondary objectives include the following: associations (ORs and 95% CI) between the presence, type and severity of SDB and the severity of initial coronary disease, based on the number of major coronary arteries with plaque of 50% or more or previous revascularisation, number of stents, prior history of coronary revascularisation (with percutaneous coronary intervention or coronary artery bypass surgery); validation of the Berlin Questionnaire as a tool to screen for SDB/SAS in individuals with AMI based on agreement between responses and the presence of central SDB/SAS on polygraphy; evaluation of SDB-related healthcare consumption and related costs during the year after hospital discharge; evaluation and comparison of healthcare consumption and associated costs during the year after inclusion in individuals with CAD who do versus do not have SDB, including comparison between individuals who have mild, moderate or severe sleep apnoea (AHI 5 to <15/hour, 15 to <30/hour and≥30/hour, respectively), and in those who are or are not receiving treatment for SDB; characterisation of profiles for individuals at higher risk of developing short-term and long-term complications of CAD; and determination of whether the presence of SDB/SAS is associated with healthcare costs during the first year after AMI.
Follow-up
Follow-up after discharge will be obtained for all participants using direct matching to the National Health Data System (SNDS). As a key component of the French universal health insurance system, the SNDS collects data on national health insurance (Système national d'information inter-régimes de l'Assurance Maladie—SNIIRAM), hospitalisations (Programme de Médicalisation des Systèmes d’Information—PMSI), National Death Registry—CepiDc and disability (Maison départementale des personnes handicapées—MDPH and Caisse nationale de solidarité pour l'autonomie—CNSA).
In particular, this database includes comprehensive information on diagnostic codes from all medical institutions in France (office practice and hospital, private or public) and exhaustive tracing of all reimbursed medications and medical devices as well as mortality data provided by the National Death Registry.
Baseline and in-hospital data collection
Baseline demographic characteristics; data collected during initial management, data on hospital management and details of all patients’ medication that are based on routine clinical care; and in-hospital outcomes are collected for all participants in the FRENCHIE registry.33 Cardiorespiratory diagnosis is performed during the initial hospitalisation for AMI. This includes recording of respiratory flow (via a nasal cannula), respiratory movement (using a thoracic belt with inductance plethysmography), and oxygen saturation and heart rate (based on fingertip transcutaneous oximetry). The device used (ApneaLink+Air; ResMed SAS, France) has been validated for SDB screening in cardiology34 and non-cardiology35 36 populations. Trained nurses in the cardiology ward will set up the device for overnight recording within the first 48 hours after admission. The timing to start and end polygraphy recording will be determined to reflect each individual’s usual sleep hours (based on patient interview).
Study participants will also be asked to complete the Pittsburgh Sleep Quality Index (PSQI)37 and the Berlin Questionnaire,38 and to provide feedback on sleep quality and duration during the night of the recording (questionnaire to be completed on the morning following polygraphy).
Polygraphy data are anonymised before being sent to the AirView Cloud and therefore to the core lab. Data will be scored by trained physicians in a centralised manner at a single centre (Centre du sommeil, Service d’Explorations Fonctionnelles, Bichat Hospital). After signal quality checking and prescoring, a trained physician will ascertain SDB characteristics (central or obstructive) and severity. An apnoea is identified by a complete or near-complete cessation of airflow that lasts for at least 10 s, and a hypopnoea is identified by a clearly discernible decrease in airflow or chest plethysmograph amplitude that lasts for at least 10 s that is accompanied by oxygen desaturation of ≥3% as per current scoring rules1). Obstructive events are distinguished from central events by the persistence of thoracic movements during apnoea, presence of snoring, flattening of the inspiratory flow curve and abrupt resumption of ventilation. The AHI is defined as the average number of apnoeas and hypopneas per hour of sleep (sleep duration is based on self-report in the morning after overnight screening).
Results of the polygraphy will be sent to the cardiology department with advice to consider undergoing formal investigation in a local sleep centre or respiratory department. Treatment and follow-up of a possible SDB will be done per usual care and not included in the study analysis.
In cases where the signal quality is poor or the recording duration is too short (<4 hours), screening can be repeated if the patient remains in the hospital, and data from the second recording will be used. If a participant with inadequate data from the initial screening has been discharged, they will be given the option to have repeat polygraphy at home (as per usual care). However, these data from at-home polygraphy will not be included in the AMI-Sleep analysis.
Data management of the FRENCHIE registry is detailed in the rationale of the FRENCHIE cohort previously published.33
The polygraphy data recorded by the device are encrypted into Airview Cloud located on a server accredited for secured health data storage (HADS, hébergeur agréé données de santé) based in France and used in usual care. This centralised scoring of polygraphy data is performed via a Cloud-based device data management solution (AirView software, ResMed, France) with compatible SDB diagnosis (ApneaLink+Air Solution).
AirView data are hosted by an authorised health data host (IDS, Montceau Les Mines http: //www.ids-assistance.com/) and kept for 10 years. AirView is not a system for archiving or permanently storing medical records. In accordance with the Public Health Code, the sponsor (Assistance Publique—Hôpitaux de Paris) acknowledges and agrees that it is their responsibility to download and maintain all data generated in connection with the use of AirView in their own system.
End of study
Study procedures are completed after SDB/SAS screening during the initial hospitalisation. Data on outcomes will continue to be collected for all participants after the index AMI using the SNDS database.
Statistical analysis
Sample size
Over a period of 2 years, the AMI-Sleep study is expected to recruit approximately 2000 participants. Based on an expected SAS prevalence in AMI patients of 11% in women and 24% in men,30 and approximately 25% of patients with ST-segment elevation AMI being women,39 the total number of individuals with SDB/SAS is estimated to be 400, 50 of whom would be women. Assuming at least a 10% rate of incident cardiovascular events over 1 year,40 there would be an estimated 200 events during the first year of follow-up. This should be sufficient to determine associations between SDB/SAS and cardiovascular events in multivariate analysis.
Primary outcome analysis
The contribution made by the presence, type and severity of SDB/SAS to cardiovascular events and mortality will be assessed using a Cox proportional hazards model. Survival time is defined as the time from discharge to the first event. The first event is defined as an ACS, stroke or cardiovascular death. For patients without an event, survival time is defined as the time from discharge to the time of last known status. Models will be adjusted for the following baseline parameters: age (continuous variable or dichotomised (<70 and ≥70 years)); sex; body mass index; smoking status (with indicator variables for current and former smoking); total and high-density lipoprotein cholesterol levels; diabetes mellitus; hypertension (systolic blood pressure, diastolic blood pressure and use of antihypertensive medications) and other parameters collected at baseline or at discharge in the FRENCHIE registry if relevant. The interaction between sex and SDB/SAS with respect to the occurrence of outcome events will be investigated, and separate analysis in males and females and sensitivity analysis considering the initiation of SDB/SAS treatment (identified in the SNDS) during follow-up may be performed if relevant.
Secondary outcome analysis
The contribution made by the presence, type and severity of SDB/SAS to each component of the primary outcome individually will be assessed using a Cox proportional hazards model in the same manner as the composite primary outcome. Associations between the presence, type and severity of SDB and the severity of initial coronary disease will be assessed using a Pearson’s χ2-squared test or a Fisher’s exact test, as appropriate. Agreement between the Berlin questionnaire findings and the presence of obstructive or central SDB/SAS will be assessed using Cohen’s kappa coefficient. Collection of outcomes and overall healthcare services after hospital discharge will be analysed using descriptive statistics.
Different patient phenotypes will be described using an Ascending Hierarchical Classification based on factors that have previously been reported to be associated with cardiovascular disease. These include breathing disturbance, autonomic dysregulation, hypoxaemia and sleep disturbance. Categorical variables (eg, snoring) will be excluded due to cluster analysis requirements. Individuals with missing data for any polygraphy variables and those with <4 hours of recording time will be excluded. Next, associations between the identified clusters and the occurrence of CAD will be performed using a Cox proportional hazards model or a logistic regression model, adjusted based on whether or not treatment for SDB was given after diagnosis.
A risk score designed to predict the occurrence of CAD complications in new patients based on clinical, sleep and SDB characteristics will be developed using a logistic regression model. The model will be constructed on a learning sample and will be applied on a randomly selected validation sample from the study population to assess reproducibility.
To determine whether the presence of SDB/SAS is associated with higher costs after AMI, patient-level data on all healthcare resources used during a 1 year period will be collected (payer perspective). Cost determinants will be analysed using multilinear regression and a general linear model to adjust for other known cost drivers, including age, sex, comorbid conditions estimated from the Charlson index, education level and place of residence. The proportion of healthcare utilisation that is attributable to the presence of SDB/SAS will be determined as a starting point for a cost-effectiveness analysis of the systematic diagnosis of SDB/SAS after AMI.
Study coordination
Bichat University Hospital Centre is coordinating the study, the principal investigator is Professor Marie-Pia d’Ortho and the scientific director is Professor Philippe Gabriel Steg. Study management, data management, statistical analysis and coordination of clinical operations are performed by URC-EST (Unité de Recherche Clinique URC Paris Est) at Saint-Antoine University Hospital, France, and the healthcare cost analysis will be performed by URC-Eco (Hotel Dieu University Hospital, France).
Patient and public involvement
Patients and/or the public were not involved in this study.
Ethics and dissemination
Eligible individuals who experience an AMI are provided with information about the AMI-Sleep study by a study investigator and asked if they are willing to provide written informed consent.
The AMI-Sleep study protocol was approved by the Ethics Committee (CPP Ouest II – Angers, RCB N°2018-A00719-46) on 17 February 2019. All study procedures will be conducted in accordance with Article L.1122-1-1 of the Code de la Santé Publique—CSP (French Public Health Code) and with the principles of Good Clinical Practice and the Declaration of Helsinki. The study registration number is (NCT04064593).
In accordance with the French Public Health Code, people with direct access to source data will take all necessary precautions to ensure the confidentiality of information relating to the clinical research and the individuals who are participating, especially with respect to their identity and the results obtained.
Study results will be submitted to peer-reviewed journals for consideration of publication and will be submitted for presentation at scientific conferences.
Discussion
The main objective of the AMI-Sleep study is to determine the independent contribution of the presence and type/severity of SDB/SAS to incident cardiovascular events and all-cause mortality after AMI. The study also has a number of important secondary objectives, as described above. The key hypotheses are that SAS is an initiating factor for the development of cardiac and vascular diseases, that SAS in acute coronary syndrome is associated with worse prognosis and that SAS accelerates disease progression in individuals with established cardiovascular conditions.
There is a recognised association between SAS and ACS.41 However, the prevalence of SDB in current literature varies from 32% to 93% and these data come from single-centre studies that are often limited by small sample size.42 Furthermore, there is a relative lack of data in France. In 2023, a large French prospective study conducted by Rabec et al showed that known sleep apnoea in AMI patients was associated with poor cardiovascular outcome; however, this study considered only diagnosed sleep apnoea that represents the tip of the iceberg given the major underdiagnosis of the disorder5 43 44 that could be increased in a high-risk population like post-AMI patients. As the first French large prognostic prospective study involving systematic screening of SDB/SAS in AMI patients, AMI-Sleep will provide relevant and contemporary information about these lifestyle-related diseases and comprehensive data in the French setting based on utilisation of the FRENCHIE registry and the SNDS database that guaranteed an exhaustive follow-up.
Data from uncontrolled studies indicate that untreated moderate-to-severe SAS is associated with increased rates of non-fatal cardiovascular events, even after relatively short follow-up.45 Over the long term, Marin et al showed that cardiovascular morbidity and mortality were only increased in individuals with untreated severe SAS, whereas simple snorers, individuals with mild SAS or those with severe SAS who accepted CPAP treatment experienced morbidity and mortality rates quite similar to those in the general population46). In another long-term study by Doherty et al, it was suggested that untreated SAS might increase the severity, rather than the prevalence, of cardiovascular diseases.47 These results were obtained in the general population, and systematic diagnosis of SDB to identify individuals who would benefit from treatment could be more relevant in high-risk patients. The AMI-Sleep study should help determine whether the severity of SDB/SAS on polygraphy is relevant in terms of cardiovascular risk after AMI.
Polysomnography (PSG) is the gold-standard test for diagnosis of OSA1 but requires overnight stay in a sleep laboratory and is not widely accessible.48 In addition, use of PSG in large epidemiological studies is limited by its cost. Using risk scores, such as the Berlin Questionnaire, is an alternative general population screening approach. The Berlin Questionnaire has been validated in this setting and has sensitivity of 86%, specificity of 77%, and a positive predictive value of 89% for detecting SDB.38 This questionnaire is widely used49–54 but has not been validated in clinical populations, such as individuals with AMI. Therefore, the AMI-Sleep study will provide data on whether the Berlin Questionnaire is appropriate to use as a comparatively cheap and simple screening method for detecting SDB/SAS in a post-AMI population, and therefore provide information that could help to improve the management of this patient group.
Compared with PSG, the use of a portable sleep apnoea diagnostic device has acceptable reliability55 and is more convenient and safer during the early phase of ACS. Furthermore, it would be expected that polygraphy would have better sensitivity and positive predictive value in a selected (rather than general) population.
One pathophysiological process that could explain the link between SDB/SAS and cardiovascular disease is endothelial dysfunction. Severe SDB has been reported to be associated with endothelial function in individuals with obesity56 but not in those with type 2 diabetes mellitus.57 These differing findings suggest that defining the risk profile for an individual and identifying patient phenotypes (clusters) could be relevant in terms of individualising disease management. This will also allow the targeting of preventive strategies and interventions in future studies.
One of the objectives of AMI-Sleep is to use routine clinical and polygraphy data to capture the physiological heterogeneity of SAS with respect to clinically relevant cardiovascular outcomes. Specifically, we hypothesise that unique clusters (phenotypes) could be identified by applying unsupervised learning methods to the study data, and that the risk of adverse cardiovascular outcomes (ACS, stroke or death) will differ between clusters. The ultimate goal is to be able to identify high-risk individuals who could be included in interventional studies designed to determine whether treatment of SDB/SAS could improve cardiovascular risk.
While systematic screening for SDB/SAS in the general population is not cost effective, more targeted screening in high-risk populations may be of value. The economic evaluation that will be performed as part of the AMI-Sleep study will address the cost benefit and cost utility of systematic SAS screening and treatment in post-AMI individuals with respect to health resource consumption. The use of CPAP in general populations with moderate to severe obstructive sleep apnoea has been shown to be cost effective,58 59 and AMI-Sleep will help to determine whether this is also the case in a post-AMI population.
Our study has several limitations. Polygraphy in the AMI-Sleep study was performed in most cases in the intensive care unit, a situation where sleep quality might be affected, which could influence the data generated. However, human central scoring and the feedback provided on sleep quality and duration during the night of the recording allow for better result interpretation. Furthermore, use of polygraphy could potentially overestimate the prevalence of SAS because individuals with heart failure can have a high rate of central sleep apnoea41; nevertheless, these patients should have a higher risk of developing obstructive sleep apnoea thereafter. Finally, although SNDS does provide comprehensive follow-up and allows detailed monitoring of healthcare consumption, it remains an administrative rather than a medical database where, despite data quality monitoring, some coding errors could remain and which do not provide some important clinical and biological variables.
Among the strengths of our study, besides the large sample and the exhaustive follow-up provided by the SNDS database, minor risk was related to polygraphy with a significant benefit if SDB/SAS is diagnosed. In addition, the economic evaluation embedded in this multicentre study permitted addressing the cost-benefit and the cost-utility of systematic SAS screening and treatment on health resource consumption.
In summary, taking advantage of the FRENCHIE cohort will allow AMI-Sleep to generate comprehensive data that are relevant to the French post-AMI population. It is hoped that the findings will improve care and outcomes for individuals with AMI who also have SDB/SAS.
The authors thank Elodie Drouet for study management. Medical writing assistance was provided by Nicola Ryan, independent medical writer, funded by Plan d’Investissement d’Avenir-3 (PIA3-RHU, Ministry of Health). The authors thank the teams involved in the follow-up data process. We thank the third party of confidence, Gabriel Baron (Université de Paris, Center of Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, AP-HP, Hôpital Hôtel-Dieu, Paris, France) and the DEMEX team of the Caisse Nationale d’Assurance Maladie et de Travailleurs Salariés (CNAMTS) for the matching process. We also thank the CONSTANCES team (UMS 11 - Cohortes en population, Université de Paris, INSERM, Paris Saclay University, UVSQ) for data management of the delivered SNDS bases. Access to some confidential data, on which this work is based, was made possible within a secure environment provided by the Centre d’accès sécurisé aux données (CASD) (Ref. 10.34724/CASD)
Ethics statements
Patient consent for publication
Not applicable.
PB and M-PD’O contributed equally.
Collaborators AMI SLEEP investigators: Frenchie Steering Committee: Tabassome Simon (URCEst), Nicolas Danchin (HEGP Paris), Gabriel Steg (Bichat-Paris), Claire Bouleti (Poitiers), Denis Angoulvant (Tours).
Contributors MPO, PGS and TS designed the study and wrote the study protocol. AR supervised data management and statistical analysis. JG supervised the data management of the delivered SNDS bases. PB and MPO wrote the article based on the study protocol. PB, MPO, LB, AR, JG, PR, IDZ, TS and PGS critically revised the manuscript and approved the submitted manuscript. PB is the guarantor.
Funding The sponsor was Assistance Publique–Hôpitaux de Paris (Direction de la Recherche Clinique et de l’Innovation). The study was supported by the Recherche Hospitalo-Universitaire (RHU) iVASC grant (www.ivasc.eu) ‘#ANR-16-RHUS-00010’ from the French National Research Agency (ANR) and funded by Plan d’Investissement d’Avenir-3 (PIA3-RHU, Ministry of Health). Funders were not involved in any activity or study management.
Competing interests PGS has received grants from Amarin, AstraZeneca, Bayer, Sanofi and Servier, consulting fees from Amgen, AstraZeneca, BMS/Myokarddia, Merck, Novo-Nordisk and Regeneron, Steering Comitee or Critical Event Committee from Amarin, AstraZeneca, Bayer, Boerhriger Ingelheim, BristolMyers Squibb, Idorsia, Novartis, PhaseBio, Pfizer, Sanofi and Servier, payments for lectures from AstraZeneca, Novartis and Novo-Nordisk, support for attending meetings from AstraZeneca and participation on a Data Safety Monitoring Board or Advisory Board from Servier, Sanofi, PHRI and Monash University and no other relationships or activities that could appear to have influenced the submitted work. All other authors have no competing interests.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
1 Berry RB, Budhiraja R, Gottlieb DJ, et al. Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med 2012; 8: 597–619. doi:10.5664/jcsm.2172
2 Cumpston E, Chen P. Sleep apnea syndrome. In: StatPearls. Treasure Island (FL): StatPearls Publishing, 2023.
3 Young T, Palta M, Dempsey J, et al. The occurrence of sleep-disordered breathing among middle-aged adults. N Engl J Med 1993; 328: 1230–5. doi:10.1056/NEJM199304293281704
4 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: 310–8. doi:10.1016/S2213-2600(15)00043-0
5 Balagny P, Vidal-Petiot E, Renuy A, et al. Prevalence, treatment and determinants of obstructive sleep apnoea and its symptoms in a population-based French cohort. ERJ Open Res 2023; 9: 00053-2023. doi:10.1183/23120541.00053-2023
6 Fox H, Purucker H-C, Holzhacker I, et al. Prevalence of Sleep-Disordered Breathing and Patient Characteristics in a Coronary Artery Disease Cohort Undergoing Cardiovascular Rehabilitation. J Cardiopulm Rehabil Prev 2016; 36: 421–9. doi:10.1097/HCR.0000000000000192
7 Ludka O, Stepanova R, Vyskocilova M, et al. Sleep apnea prevalence in acute myocardial infarction--the Sleep Apnea in Post-acute Myocardial Infarction Patients (SAPAMI) Study. Int J Cardiol 2014; 176: 13–9. doi:10.1016/j.ijcard.2014.06.020
8 Randerath W, Bonsignore MR, Herkenrath S. Obstructive sleep apnoea in acute coronary syndrome. Eur Respir Rev 2019; 28: 180114. doi:10.1183/16000617.0114-2018
9 Konecny T, Kuniyoshi FHS, Orban M, et al. Under-diagnosis of sleep apnea in patients after acute myocardial infarction. J Am Coll Cardiol 2010; 56: 742–3. doi:10.1016/j.jacc.2010.04.032
10 Wang X, Fan J, Guo R, et al. Association of obstructive sleep apnoea with cardiovascular events in women and men with acute coronary syndrome. Eur Respir J 2023; 61: 2201110. doi:10.1183/13993003.01110-2022
11 Fan J, Wang X, Ma X, et al. Association of Obstructive Sleep Apnea With Cardiovascular Outcomes in Patients With Acute Coronary Syndrome. J Am Heart Assoc 2019; 8: e010826. doi:10.1161/JAHA.118.010826
12 Mazaki T, Kasai T, Yokoi H, et al. Impact of Sleep-Disordered Breathing on Long-Term Outcomes in Patients With Acute Coronary Syndrome Who Have Undergone Primary Percutaneous Coronary Intervention. J Am Heart Assoc 2016; 5: e003270. doi:10.1161/JAHA.116.003270
13 Lee C-H, Sethi R, Li R, et al. Obstructive Sleep Apnea and Cardiovascular Events After Percutaneous Coronary Intervention. Circulation 2016; 133: 2008–17. doi:10.1161/CIRCULATIONAHA.115.019392
14 Wang X, Fan J-Y, Zhang Y, et al. Association of obstructive sleep apnea with cardiovascular outcomes after percutaneous coronary intervention. Medicine (Baltimore) 2018; 97: e0621. doi:10.1097/MD.0000000000010621
15 Iannaccone M, Quadri G, Taha S, et al. Prevalence and predictors of culprit plaque rupture at OCT in patients with coronary artery disease: a meta-analysis. Eur Heart J Cardiovasc Imaging 2016; 17: 1128–37. doi:10.1093/ehjci/jev283
16 Libby P. Current concepts of the pathogenesis of the acute coronary syndromes. Circulation 2001; 104: 365–72. doi:10.1161/01.cir.104.3.365
17 Terada S, Koyama T, Watanabe H, et al. Abnormal coagulation and platelet profile in patients with obstructive sleep apnea syndrome. Int J Cardiol 2011; 146: 423–5. doi:10.1016/j.ijcard.2010.10.095
18 Bradley TD, Floras JS. Obstructive sleep apnoea and its cardiovascular consequences. The Lancet 2009; 373: 82–93. doi:10.1016/S0140-6736(08)61622-0
19 Yeghiazarians Y, Jneid H, Tietjens JR, et al. Obstructive Sleep Apnea and Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation 2021; 144: e56–67. doi:10.1161/CIR.0000000000000988
20 Meslier N, Gagnadoux F, Giraud P, et al. Impaired glucose-insulin metabolism in males with obstructive sleep apnoea syndrome. Eur Respir J 2003; 22: 156–60. doi:10.1183/09031936.03.00089902
21 Punjabi NM, Sorkin JD, Katzel LI, et al. Sleep-disordered breathing and insulin resistance in middle-aged and overweight men. Am J Respir Crit Care Med 2002; 165: 677–82. doi:10.1164/ajrccm.165.5.2104087
22 Punjabi NM, Shahar E, Redline S, et al. Sleep-disordered breathing, glucose intolerance, and insulin resistance: the Sleep Heart Health Study. Am J Epidemiol 2004; 160: 521–30. doi:10.1093/aje/kwh261
23 Nieto FJ, Young TB, Lind BK. Association of Sleep-Disordered Breathing, Sleep Apnea, and Hypertension in a Large Community-Based Study. JAMA 2000; 283: 1829. doi:10.1001/jama.283.14.1829
24 Lavie P, Herer P, Hoffstein V. Obstructive sleep apnoea syndrome as a risk factor for hypertension: population study. BMJ 2000; 320: 479–82. doi:10.1136/bmj.320.7233.479
25 Young T, Peppard P, Palta M, et al. Population-based study of sleep-disordered breathing as a risk factor for hypertension. Arch Intern Med 1997; 157: 1746–52.
26 Newman AB, Spiekerman CF, Md PE, et al. Daytime Sleepiness Predicts Mortality and Cardiovascular Disease in Older Adults. J Am Geriatr Soc 2000; 48: 115–23. doi:10.1111/j.1532-5415.2000.tb03901.x
27 Börgel J, Sanner BM, Bittlinsky A, et al. Obstructive sleep apnoea and its therapy influence high-density lipoprotein cholesterol serum levels. Eur Respir J 2006; 27: 121–7. doi:10.1183/09031936.06.00131304
28 Carpio C, Alvarez-Sala R, García-Río F. Epidemiological and Pathogenic Relationship between Sleep Apnea and Ischemic Heart Disease. Pulm Med 2013; 2013: 405827. doi:10.1155/2013/405827
29 Gottlieb DJ, Yenokyan G, Newman AB, et al. Prospective study of obstructive sleep apnea and incident coronary heart disease and heart failure: the sleep heart health study. Circulation 2010; 122: 352–60. doi:10.1161/CIRCULATIONAHA.109.901801
30 Hagenah GC, Gueven E, Andreas S. Influence of obstructive sleep apnoea in coronary artery disease: A 10-year follow-up. Respir Med 2006; 100: 180–2. doi:10.1016/j.rmed.2005.04.009
31 Hedner J, Grote L, Bonsignore M, et al. The European Sleep Apnoea Database (ESADA): report from 22 European sleep laboratories. Eur Respir J 2011; 38: 635–42. doi:10.1183/09031936.00046710
32 Mooe T, Franklin KA, Holmström K, et al. Sleep-disordered breathing and coronary artery disease: long-term prognosis. Am J Respir Crit Care Med 2001; 164: 1910–3. doi:10.1164/ajrccm.164.10.2101072
33 Gautier A, Danchin N, Ducrocq G, et al. Rationale and design of the FRENch CoHort of myocardial Infarction Evaluation (FRENCHIE) study. Arch Cardiovasc Dis 2024; 117: 417–26. doi:10.1016/j.acvd.2024.04.004
34 McEvoy RD, Antic NA, Heeley E, et al. CPAP for Prevention of Cardiovascular Events in Obstructive Sleep Apnea. N Engl J Med 2016; 375: 919–31. doi:10.1056/NEJMoa1606599
35 BaHammam AS, Kendzerska T, Gupta R, et al. Comorbid depression in obstructive sleep apnea: an under-recognized association. Sleep Breath 2016; 20: 447–56. doi:10.1007/s11325-015-1223-x
36 Kleisiaris CF, Kritsotakis EI, Daniil Z, et al. Assessing the risk of obstructive sleep apnoea-hypopnoea syndrome in elderly home care patients with chronic multimorbidity: a cross-sectional screening study. Springerplus 2016; 5: 34. doi:10.1186/s40064-016-1672-0
37 Buysse DJ, Reynolds CF, Monk TH, et al. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res 1989; 28: 193–213. doi:10.1016/0165-1781(89)90047-4
38 Netzer NC, Stoohs RA, Netzer CM, et al. Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med 1999; 131: 485–91. doi:10.7326/0003-4819-131-7-199910050-00002
39 Puymirat E, Simon T, Cayla G, et al. Acute Myocardial Infarction: Changes in Patient Characteristics, Management, and 6-Month Outcomes Over a Period of 20 Years in the FAST-MI Program (French Registry of Acute ST-Elevation or Non-ST-Elevation Myocardial Infarction) 1995 to 2015. Circulation 2017; 136: 1908–19. doi:10.1161/CIRCULATIONAHA.117.030798
40 Deharo P, Ducrocq G, Bode C, et al. Timing of Angiography and Outcomes in High-Risk Patients With Non-ST-Segment-Elevation Myocardial Infarction Managed Invasively: Insights From the TAO Trial (Treatment of Acute Coronary Syndrome With Otamixaban). Circulation 2017; 136: 1895–907. doi:10.1161/CIRCULATIONAHA.117.029779
41 Somers VK, White DP, Amin R, et al. Sleep apnea and cardiovascular disease: an American Heart Association/american College Of Cardiology Foundation Scientific Statement from the American Heart Association Council for High Blood Pressure Research Professional Education Committee, Council on Clinical Cardiology, Stroke Council, and Council On Cardiovascular Nursing. In collaboration with the National Heart, Lung, and Blood Institute National Center on Sleep Disorders Research (National Institutes of Health). Circulation 2008; 118: 1080–111. doi:10.1161/CIRCULATIONAHA.107.189375
42 Huang Z, Zheng Z, Luo Y, et al. Prevalence of sleep-disordered breathing in acute coronary syndrome: a systemic review and meta-analysis. Sleep Breath 2017; 21: 217–26. doi:10.1007/s11325-016-1398-9
43 Young T, Evans L, Finn L, et al. Estimation of the clinically diagnosed proportion of sleep apnea syndrome in middle-aged men and women. Sleep 1997; 20: 705–6. doi:10.1093/sleep/20.9.705
44 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: 687–98. doi:10.1016/S2213-2600(19)30198-5
45 Pendlebury ST, Pépin JL, Veale D, et al. Natural evolution of moderate sleep apnoea syndrome: significant progression over a mean of 17 months. Thorax 1997; 52: 872–8. doi:10.1136/thx.52.10.872
46 Marin J, Carrizo S, Vicente E, et al. Long-term cardiovascular outcomes in men with obstructive sleep apnoea-hypopnoea with or without treatment with continuous positive airway pressure: an observational study. The Lancet 2005; 365: 1046–53. doi:10.1016/S0140-6736(05)74229-X
47 Doherty LS, Kiely JL, Swan V, et al. Long-term effects of nasal continuous positive airway pressure therapy on cardiovascular outcomes in sleep apnea syndrome. Chest 2005; 127: 2076–84. doi:10.1378/chest.127.6.2076
48 Portable Monitoring Task Force of the American Academy of Sleep Medicine. Clinical Guidelines for the Use of Unattended Portable Monitors in the Diagnosis of Obstructive Sleep Apnea in Adult Patients. J Clin Sleep Med 2007; 03: 737–47. doi:10.5664/jcsm.27032
49 Correia LCL, Souza AC, Garcia G, et al. Obstructive sleep apnea affects hospital outcomes of patients with non-ST-elevation acute coronary syndromes. Sleep 2012; 35: 1241–5A. doi:10.5665/sleep.2078
50 Gus M, Gonçalves SC, Martinez D, et al. Risk for Obstructive Sleep Apnea by Berlin Questionnaire, but not daytime sleepiness, is associated with resistant hypertension: a case-control study. Am J Hypertens 2008; 21: 832–5. doi:10.1038/ajh.2008.184
51 Jesus E de, Dias-Filho EB, Mota B de M, et al. Suspicion of obstructive sleep apnea by Berlin Questionnaire predicts events in patients with acute coronary syndrome. Arq Bras Cardiol 2010; 95: 313–20. doi:10.1590/s0066-782x2010005000103
52 Margallo VS, Muxfeldt ES, Guimarães GM, et al. Diagnostic accuracy of the Berlin questionnaire in detecting obstructive sleep apnea in patients with resistant hypertension. J Hypertens 2014; 32: 2030–6. doi:10.1097/HJH.0000000000000297
53 Martinez D, da Silva RP, Klein C, et al. High risk for sleep apnea in the Berlin questionnaire and coronary artery disease. Sleep Breath 2012; 16: 89–94. doi:10.1007/s11325-010-0460-2
54 Massierer D, Martinez D, Fuchs SC, et al. Obstructive sleep apnea, detected by the Berlin Questionnaire: an associated risk factor for coronary artery disease. Cad Saude Publica 2012; 28: 1530–8. doi:10.1590/s0102-311x2012000800011
55 Chen H, Lowe AA, Bai Y, et al. Evaluation of a portable recording device (ApneaLink) for case selection of obstructive sleep apnea. Sleep Breath 2009; 13: 213–9. doi:10.1007/s11325-008-0232-4
56 Azuma M, Chihara Y, Yoshimura C, et al. Association Between Endothelial Function (Assessed on Reactive Hyperemia Peripheral Arterial Tonometry) and Obstructive Sleep Apnea, Visceral Fat Accumulation, and Serum Adiponectin. Circ J 2015; 79: 1381–9. doi:10.1253/circj.CJ-14-1303
57 Bironneau V, Goupil F, Ducluzeau PH, et al. Association between obstructive sleep apnea severity and endothelial dysfunction in patients with type 2 diabetes. Cardiovasc Diabetol 2017; 16: 39. doi:10.1186/s12933-017-0521-y
58 Ayas NT, FitzGerald JM, Fleetham JA, et al. Cost-effectiveness of continuous positive airway pressure therapy for moderate to severe obstructive sleep apnea/hypopnea. Arch Intern Med 2006; 166: 977–84. doi:10.1001/archinte.166.9.977
59 Guest JF, Helter MT, Morga A, et al. Cost-effectiveness of using continuous positive airway pressure in the treatment of severe obstructive sleep apnoea/hypopnoea syndrome in the UK. Thorax 2008; 63: 860–5. doi:10.1136/thx.2007.086454
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; Marie-Pia D’Ortho 2 ; Berard, Laurence 3 ; Rousseau, Alexandra 3 ; Gourmelen, Julie 4 ; Ravaud, Philippe 5 ; Durand-Zaleski, Isabelle 6
; Tabassome Simon 3 ; Steg, Philippe Gabriel 7 1 Department of Physiology and Functional Exploration - Bichat Hospital, Assistance Publique - Hopitaux de Paris, Paris, Île-de-France, France; UMS 011, Population-based Cohorts Unit, INSERM, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France
2 Department of Physiology and Functional Exploration - Bichat Hospital, Assistance Publique - Hopitaux de Paris, Paris, Île-de-France, France; Inserm, NeuroDiderot, Université Paris Cité, Paris, Île-de-France, France
3 Department of Clinical Pharmacology-Clinical Research Platform - Saint Antoine Hospital, French Alliance for Cardiovascular Trials, Sorbonne Université, Assistance Publique - Hopitaux de Paris, Paris, Île-de-France, France
4 UMS 011, Population-based Cohorts Unit, INSERM, Paris Saclay University, Université de Versailles Saint-Quentin-en-Yvelines, Paris, France
5 METHODS Team, CRESS, INSERM, INRAE, Université Paris Cité, Paris, Île-de-France, France; Centre d’Épidémiologie Clinique - Hotel Dieu Hospital, Assistance Publique - Hopitaux de Paris, Paris, Île-de-France, France
6 Research Centre of Research Epidemiology and Statistics (CRESS-UMR1153), Inserm, University of Paris, Paris, France; DRCI-URC Eco Ile-de-France, Assistance Publique - Hopitaux de Paris, Paris, France
7 Department of cardiology - Bichat Hospital, Assistance Publique - Hopitaux de Paris, Paris, Île-de-France, France; INSERM U1148, Laboratory for Vascular Translational Science, Université Paris Cité, Paris, Île-de-France, France; Institut Universitaire de France, Paris, Île-de-France, France