Cardiovascular benefit of continuous positive airway pressure according to high-risk obstructive sleep apnoea: a multi-trial analysis

Ali Azarbarzin; Daniel Vena; Neda Esmaeili; Andrew Wellman; Lucía Pinilla; Ludovico Messineo; Andrey Zinchuk; Raichel Alex; Mathias Baumert; Kelly A Loffler; Craig S Anderson; David P White; Susan Redline; Daniel J Gottlieb; Ferran Barbé; Yuksel Peker; Manuel Sánchez-de-la-Torre; Doug McEvoy; Scott A Sands

doi:10.1093/eurheartj/ehaf447

. Author manuscript; available in PMC: 2026 Feb 6.

Published before final editing as: Eur Heart J. 2025 Aug 5:ehaf447. doi: 10.1093/eurheartj/ehaf447

Cardiovascular benefit of continuous positive airway pressure according to high-risk obstructive sleep apnoea: a multi-trial analysis

Ali Azarbarzin ^1,^*, Daniel Vena ¹, Neda Esmaeili ¹, Andrew Wellman ¹, Lucía Pinilla ^2,³, Ludovico Messineo ¹, Andrey Zinchuk ⁴, Raichel Alex ¹, Mathias Baumert ⁵, Kelly A Loffler ², Craig S Anderson ^6,^7,⁸, David P White ¹, Susan Redline ¹, Daniel J Gottlieb ¹, Ferran Barbé ^3,⁹, Yuksel Peker ^10,^11,^12,¹³, Manuel Sánchez-de-la-Torre ^3,¹⁴, Doug McEvoy ², Scott A Sands ¹

¹Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital and Harvard Medical School, 221 Longwood Ave, Boston, MA 02115, USA

²Flinders Health and Medical Research Institute: Sleep Health, College of Medicine and Public Health, Flinders University, Level 2, Building A, Mark Oliphant Building, 5 Laffer Drive, Bedford Park, South Australia 5042, Australia

³Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III (ISCIII), Av. Monforte de Lemos, 3-5, Pavilion 11, Ground Floor, 28029 Madrid, Spain

⁴Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, Yale School of Medicine, 300 Cedar Street TAC - 441 South, New Haven, CT 06520, USA

⁵Discipline of Biomedical Engineering, School of Electrical and Mechanical Engineering, The University of Adelaide, Level 3, Ingkarni Wardli Building, Adelaide, South Australia 5005, Australia

⁶The George Institute for Global Health, University of New South Wales, Level 18, International Towers 3, 300 Barangaroo Ave, Sydney, New South Wales 2000, Australia

⁷Institute for Science and Technology for Brain-Inspired Intelligence, Fudan University, 220 Handan Road, Shanghai 200433, China

⁸Royal Prince Alfred Hospital, 50 Missenden Rd, Camperdown, New South Wales 2050, Australia

⁹Group of Translational Research in Respiratory Medicine, University Hospital Arnau de Vilanova and Santa María, University of Lleida, IRBLleida, Av. Rovira Roure, 80, 25198 Lleida, Spain

¹⁰Department of Pulmonary Medicine, Koc University, Davutpasa cad, No 4 TR-34010 Zeytinburnu, Istanbul, Turkey

¹¹Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, 413 45 Göteborg, Sweden

¹²Department of Clinical Sciences, Respiratory Medicine and Allergology, Faculty of Medicine, Lund University, Wigerthuset, Remissgatan 4, plan 2, SUS, 221 85 Lund, Sweden

¹³Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh School of Medicine, NW 628 UPMC Montefiore, 3459 Fifth Avenue, Pittsburgh, PA 15213, USA

¹⁴Group of Precision Medicine in Chronic Diseases, Hospital Nacional de Parapléjicos, IDISCAM, Department of Nursing, Physiotherapy and Occupational Therapy, Faculty of Physiotherapy and Nursing, University of Castilla-La Mancha, Carretera Finca la Peraleda, sn, 45071 Toledo, Spain

Corresponding author. aazarbarzin@bwh.harvard.edu

PMCID: PMC12874658 NIHMSID: NIHMS2129181 PMID: 40794640

Abstract

Background and Aims

Randomized trials of continuous positive airway pressure (CPAP) treatment for obstructive sleep apnoea (OSA) in patients with cardiovascular disease have not detected reduced risk of major adverse cardiovascular and cerebrovascular events (MACCEs). This study tested whether the cardiovascular benefit of CPAP occurs preferentially in high-risk OSA, characterized by greater OSA-related heart rate acceleration or hypoxaemia.

Methods

In a post hoc analysis of pooled Randomized Intervention with Continuous Positive Airway Pressure in Coronary Artery Disease and Obstructive Sleep Apnoea, Impact of Continuous Positive Airway Pressure on Patients with Acute Coronary Syndrome and Nonsleepy Obstructive Sleep Apnoea, and Sleep Apnoea Cardiovascular Endpoints Study randomized trials; outcomes were stratified by high-risk OSA status, defined by heart rate response following OSA respiratory events >9.4 b.p.m. (third tertile) or oxygen desaturation area under baseline (hypoxic burden) > 87.1% min/h (third tertile). Cox mixed models quantified the CPAP treatment effect on MACCE (including cardiovascular mortality, myocardial infarction, and stroke) within high-risk OSA and the difference vs low-risk status (primary test). Secondary analyses examined participants without excessive sleepiness (Epworth <11 points) or without increased blood pressure (systolic/diastolic <140/90 mmHg).

Results

In 3549 participants, 16.6% and 16.3% reached the MACCE endpoint with CPAP (n = 1778) and usual care (n = 1771), respectively. The CPAP treatment effect was greater in participants with vs without high-risk OSA [interaction hazard ratio (iHR) .69, 95% confidence interval (CI) .50–.95, P_interaction = .024; N_high-risk = 1832]. The differential effect was stronger in those without excessive sleepiness (iHR .59, 95% CI .41–.84; N_high-risk = 1509), or without increased blood pressure (iHR .54, 95% CI .36–.81; N_high-risk = 1244). Continuous positive airway pressure benefits in high-risk OSA were observed alongside harm in low-risk OSA.

Conclusions

Continuous positive airway pressure preferentially improves cardiovascular outcomes in high-risk OSA, while harm in low-risk OSA may counteract this effect. These findings provide a pathway to identify patients likely to benefit.

Keywords: Obstructive sleep apnoea, MACCE, Phenotype, Precision medicine, Heart rate response, Hypoxic burden

Structured Grahical Abstract

graphic file with name nihms-2129181-f0003.jpg

Study objective, methods, key results, and clinical implications of continuous positive airway pressure (CPAP) therapy on cardiovascular outcomes in patients with high-risk obstructive sleep apnoea (OSA). MACCE, major adverse cardiovascular and cerebrovascular events.

Introduction

Obstructive sleep apnoea (OSA) is a common disorder¹ associated with an increased risk of major adverse cardiovascular and cerebrovascular events (MACCEs), particularly when the condition is severe.^2–4 Observational studies have suggested that continuous positive airway pressure (CPAP) therapy may offer cardiovascular protection.^5–7 However, the three large randomized trials of CPAP for secondary cardiovascular prevention—including the Randomized Intervention with Continuous Positive Airway Pressure in Coronary Artery Disease and Obstructive Sleep Apnoea (RICCADSA; NCT00519597), the Impact of Continuous Positive Airway Pressure on Patients with Acute Coronary Syndrome and Nonsleepy Obstructive Sleep Apnoea (ISAACC; NCT01335087), and the Sleep Apnoea Cardiovascular Endpoints Study (SAVE; NCT00738179)—did not show a significant reduction in the risk of a primary composite cardiovascular endpoint (MACCE).^8–10 These findings suggest that the cardiovascular benefits of CPAP may be minimal or absent. Consequently, current clinical use of CPAP primarily focuses on improving symptoms and quality of life rather than preventing cardiovascular disease. Multiple potential explanations for the failure to improve OSA-related cardiovascular risks have been proposed,^11–14 including (i) OSA may not directly cause increased cardiovascular morbidity; instead, its associations with cardiovascular disease may reflect unmeasured confounders such as visceral obesity^11,15; (ii) participants in the trials may not have been representative of the symptomatic OSA population treated in sleep clinics, as sleepier patients were excluded due to ethical concerns^16,17; (iii) CPAP adherence may have been insufficient to produce cardiovascular benefits,¹⁸ with post hoc analyses showing benefit only among adherent patients; however, such analyses are limited by healthy user bias, as adherence to placebo treatment is also associated with better cardiovascular outcomes¹⁹; (iv) interventions may have been initiated too late in the course of cardiovascular disease to reverse its progression; and (v) standard cardioprotective pharmacotherapy may have reduced the cardiovascular risks associated with OSA.^20,21 Alternatively, we propose that only a subgroup of patients with OSA are at increased cardiovascular risk, leading to a dilution of any cardioprotective effect of CPAP in broader study populations. This idea is supported by data from community-based cohort studies,^22–29 suggesting that the OSA impact on major cardiovascular outcomes is predicted by two key physiological markers of OSA severity, namely the degree of OSA-related heart rate acceleration (‘heart rate response’) and the degree of OSA-related hypoxaemia (‘hypoxic burden’).^30,31 Indeed, effect-modification analyses of RICCADSA showed that participants with a greater heart rate response exhibited a meaningful MACCE risk reduction with CPAP vs usual care,³⁰ while in ISAACC, those with a greater hypoxic burden exhibited such CPAP benefit.³¹ These findings suggest that individuals with either of these high-risk physiological characteristics may derive greater cardiovascular protection from CPAP therapy. Accordingly, we conducted a post hoc mechanistic analysis using pooled individual patient data from RICCADSA, ISAACC, and SAVE trials to examine whether CPAP preferentially reduces MACCE risk in patients with vs without high-risk OSA. For primary analysis, high-risk OSA was defined as the presence of either a high pulse rate response or the presence of a high hypoxic burden (see Methods). Continuous positive airway pressure effects were compared between high-risk and low-risk groups, with effect modification as the primary statistical comparison. For secondary analysis, we restricted analysis to patients without excessive daytime sleepiness, based on the assumption that these individuals are less likely to seek CPAP for symptomatic relief and recent evidence, suggesting greater cardiovascular benefit in non-sleepy patients.³² We also restricted analysis to patients without increased blood pressure, considering the possibility that OSA-related risks may counteract those of uncontrolled high blood pressure. Recent analyses have suggested that OSA treatment benefit may be most evident in those with less severe or less established cardiovascular disease.^33–35 Ultimately, our goal was to identify key characteristics associated with a reversible OSA-related MACCE risk through CPAP therapy in order to inform clinical practice and guide the design of future prospective trials.

Methods

Study design

This is a post hoc analysis of pooled randomized controlled trials (RICCADSA,⁸ ISAACC,¹⁰ and SAVE⁹) evaluating CPAP treatment of OSA in adults to reduce risk of MACCE in adults with established cardiovascular disease. Trials were identified per formal and registered systematic review (Supplementary data online, Appendix).

Participants

Trial details have been summarized and compared previously.¹⁸ The RICCADSA trial studied patients with angiography-verified coronary artery disease with recent (6 months) percutaneous coronary intervention or coronary artery bypass surgery. The ISAACC trial studied patients recently admitted for acute coronary syndrome to the coronary care unit or cardiology hospitalization ward. The SAVE trial studied patients with a diagnosis of coronary artery disease or cerebrovascular disease. For randomization, the presence of OSA was confirmed using apnoea–hypopnoea index ≥15 events/h or an equivalent 4% oxygen desaturation index of ≥12 events/h (SAVE). Patients with Epworth sleepiness scale scores <10, <11, and <16 units were eligible for RICCADSA, ISAACC, and SAVE, respectively. Institutional review board approvals were obtained, and written informed consent was documented before enrolment. Patient flow is shown in Figure 1.

Flow diagram presenting ascertainment of the study sample. CPAP, continuous positive airway pressure; ISAACC, Impact of Continuous Positive Airway Pressure on Patients with Acute Coronary Syndrome and Nonsleepy Obstructive Sleep Apnoea; RICCADSA, Randomized Intervention with Continuous Positive Airway Pressure in Coronary Artery Disease and Obstructive Sleep Apnoea; SAVE, Sleep Apnoea Cardiovascular Endpoints Study; SpO₂, oxygen saturation

Procedures

Unattended overnight sleep studies included oximetry-based oxygen saturation and pulse rate, with nasal pressure airflow. Randomized Intervention with Continuous Positive Airway Pressure in Coronary Artery Disease and Obstructive Sleep Apnoea employed in-laboratory studies with electroencephalography; ISAACC and SAVE employed home sleep studies without electroencephalography. Apnoeas were defined by a reduction in flow of ≥90% for ≥10 s (all trials); hypopnoeas were based on a reduction in airflow associated with at least a 4% oxygen desaturation (all trials). In RICCADSA, clear hypopnoeas per 50% reduction in flow regardless of de-saturation³⁶ were also included (in addition to hypopnoeas that were associated with at least a 4% desaturation).

Epworth sleepiness scale values were documented during baseline screening (scores range from 0 to 24; scores above 11 are taken as excessive sleepiness). Baseline in-office automated blood pressure measurements were taken from a single measure (RICCADSA) or the mean of two measures (ISAACC and SAVE).

Continuous positive airway pressure intervention

Patients were randomized to CPAP or usual care in a 1:1 ratio. After initiating auto-titrating CPAP, ISAACC and SAVE but not RICCADSA switched to fixed pressures for therapy. Continuous positive airway pressure adherence, available in all trials at 24 months, was reported as average hours of use per night (i.e. average hours of use per nights used, multiplied by the proportion of days used in the recent treatment period), including zeros for patients who ceased CPAP use, but excluding missing data (e.g. moved).

Cardiovascular endpoint

The primary composite outcome (MACCE) included cardiovascular mortality, myocardial infarction, and stroke. Randomized Intervention with Continuous Positive Airway Pressure in Coronary Artery Disease and Obstructive Sleep Apnoea also included repeat revascularization.⁸ The ISAACC and SAVE trials also included hospitalization for heart failure, unstable angina, or transient ischaemic attack.^9,10

Derivation of heart rate response and hypoxic burden

Heart rate response^24,30 and hypoxic burden^22,37 were calculated following published methods.³⁸ Briefly, the heart rate response quantifies the mean increase in pulse rate following individual apnoea–hypopnoea events.^24,30 The hypoxic burden quantifies the mean ‘area under the oxygen desaturation curve’ temporally associated with individual apnoea–hypopnoea events^22,37 multiplied by apnoea–hypopnoea index. For ISAACC, annotated respiratory event files were not available for all sleep studies, thus automatically identified desaturation events were used in place of respiratory events for analyses.^31,37 Neither heart rate response nor hypoxic burden data from SAVE have been evaluated or reported previously.

High-risk obstructive sleep apnoea

For primary analysis, patients with a heart rate response >9.4 b.p.m. (third tertile of the current study population) or a hypoxic burden >87.1% min/h (third tertile) were defined as high-risk OSA; remaining individuals were low-risk OSA. Use of both variables provided a means to simultaneously incorporate the two key predictive risk factors in primary testing. Tertiles were chosen based on prior experience with these risk factors.^30,39

Statistical analysis

Analysis details are outlined in a statistical analysis plan. Missing data due to the absence of hypoxic burden or heart rate response, or covariates (below), were uncommon (Figure 1) and were considered missing at random; hence, a complete case analysis was performed. Continuous variables are presented as median (interquartile range), and categorical variables as counts and percentages. Statistical analysis was performed using the R statistical package.

Primary analysis

Cox-proportional hazard mixed models¹⁸ quantified the differential treatment effect of CPAP vs control on the MACCE composite outcome in high-risk vs low-risk OSA (per CPAP × subgroup interaction). Models were adjusted for covariates age, sex, body mass index, baseline apnoea–hypopnoea index, Epworth score, and systolic and diastolic blood pressures to maximize model precision; trial was included as a random effect. The primary quantitative test was for significance of the treatment by high-risk OSA status interaction (effect modification); P < .05 was considered statistically significant (two-sided test). As a major goal was to evaluate which patients benefit most from CPAP, treatment effects within high-risk OSA were evaluated, and reported alongside treatment effects within low-risk OSA for context.

Secondary analyses

Primary analysis was repeated in the subgroup of patients without excessive sleepiness (Epworth score <11), and in participants without increased blood pressure (systolic and diastolic levels <140 and <90 mmHg, respectively). Further analysis examined patients meeting both criteria. Significance was considered at P < .05 if all earlier secondary tests were also significant. Formal evaluation of three-way interactions (CPAP × high-risk subgroup × excessive sleepiness, CPAP × high-risk subgroup × increased blood pressure) supported the secondary analyses.

Additional analyses

Four additional analyses were reported. (i) We evaluated whether, in this clinical trial sample, untreated high-risk OSA is associated with greater MACCE risk than untreated low-risk OSA; the hazard ratios associated with high- vs low-risk OSA within usual care were quantified using the above primary/secondary models. (ii) To estimate optimal patient selection characteristics for CPAP treatment benefit, we repeated analyses using alternative thresholds for Epworth scores and blood pressures (broader ranges explored in the Supplementary data online, Appendix). For optimizing statistical power for a future trial, we considered the upper 95% confidence interval (CI) of the hazard ratio in high-risk OSA. For optimal prevention of MACCE endpoints across the OSA population, we estimated the number of endpoint events mitigated when treating all high-risk OSA, expressed per thousand patients with OSA (N_saved = absolute risk reduction × high-risk group prevalence). (iii) To assess the dependence of our findings on CPAP adherence, reanalysis was performed with CPAP subgroups restricted to: non-users, non-adherents (>0 to <4 h), and adherents (≥4 h); usual care arm controls could not be restricted by adherence (the only analysis with concerns for healthy user bias). Further, findings were reported: (iv) for each trial evaluated separately, (v) redefining high-risk OSA using different thresholds, (vi) redefining high-risk OSA using heart rate response and hypoxic burden measures examined separately, (vii) within women and men separately, (viii) using separate components of the MACCE composite outcome, (ix) redefining high-risk OSA based on apnoea–hypopnoea index or oxygen desaturation index alone, (x) within individuals with diagnosed hypertension, and (xi) within those without a history of atrial fibrillation (Supplementary data online, Appendix).

Results

In total, 3549 participants were included (Figure 1, Table 1). At enrolment, participants had a median age of 61 years, and 18% were female. Median body mass index was 28 kg/m², median apnoea–hypopnoea index was 25 events/h, and median Epworth score was 7. Median heart rate response was 7.7 b.p.m., and median hypoxic burden was 62.5% min/h. The median duration of follow-up was 3.1 years. Median adherence in the first 24 months was 3.3 h/night.

Table 1.

Baseline characteristics of the study participants

Characteristic	All n = 3549	SAVE n = 2623	ISAACC n = 706	RICCADSA n = 220	High risk		Low risk
Characteristic	All n = 3549	SAVE n = 2623	ISAACC n = 706	RICCADSA n = 220	CPAP n = 914	Usual care n = 918	CPAP n = 864	Usual care n = 853
Trial
SAVE	2623 (73.9%)	2623 (100%)	0 (.00%)	0 (.00%)	725 (79.3%)	737 (80.3%)	590 (68.3%)	571 (66.9%)
ISAACC	706 (19.9%)	0 (.00%)	706 (100%)	0 (.00%)	137 (15.0%)	136 (14.8%)	215 (24.9%)	218 (25.6%)
RICCADSA	220 (6.20%)	0 (.00%)	0 (.00%)	220 (100%)	52 (5.69%)	45 (4.90%)	59 (6.83%)	64 (7.50%)

Age, year	61 (55–68)	61 (56–67)	59 (52–67)	67 (61–72)	61 (55–67)	61 (54–67)	62 (56–68)	62 (56–68)

Female sex, n (%)	642 (18.1%)	500 (19.1%)	110 (15.6%)	32 (14.5%)	136 (14.9%)	128 (13.9%)	189 (21.9%)	189 (22.2%)

Body mass index, kg/m²	28 (26–31)	28 (26–31)	29 (26–32)	28 (26–30)	28 (26–31)	28 (26–31)	28 (26–31)	28 (26–31)

Current smoking, n (%)	783 (22.1%)	398 (15.2%)	351 (49.7%)	34 (15.5%)	210 (23.0%)	204 (22.2%)	195 (22.6%)	174 (20.4%)

Hypertension, n (%)	2591 (73.0%)	2060 (78.5%)	395 (55.9%)	136 (61.8%)	676 (74.0%)	692 (75.4%)	628 (72.7%)	595 (69.8%)

Diabetes, n (%)	1024 (28.9%)	782 (29.8%)	190 (26.9%)	52 (23.6%)	270 (29.5%)	233 (25.4%)	264 (30.6%)	257 (30.1%)

Coronary artery disease, n (%)	1417 (39.9%)	1061 (40.4%)	136 (19.3%)	220 (100%)	349 (38.2%)	347 (37.8%)	372 (43.1%)	349 (40.9%)

Antihypertensive medication use, n (%)	2606 (73.6%)	2050 (78.2%)	351 (49.7%)	205 (95.8%)	656 (71.9%)	667 (72.7%)	650 (75.4%)	633 (74.3%)

Lipid-lowering medication use, n (%)	2000 (56.4%)	1533 (58.4%)	264 (37.4%)	203 (94.9%)	481 (52.7%)	499 (54.4%)	512 (59.4%)	508 (59.6%)

Antithrombotic medication use, n (%)	2370 (66.9%)	1980 (75.5%)	178 (25.2%)	212 (98.6%)	604 (66.2%)	618 (67.4%)	582 (67.5%)	566 (66.4%)

Percutaneous coronary intervention, n (%)	1664 (46.9%)	892 (34.0%)	608 (86.1%)	164 (74.5%)	367 (40.2%)	377 (41.1%)	456 (52.8%)	464 (54.4%)

Coronary artery bypass graft, n (%)	406 (11.5%)	312 (11.9%)	38 (5.46%)	56 (25.5%)	83 (9.10%)	86 (9.39%)	127 (14.7%)	110 (13.0%)

Epworth sleepiness scale	7 (4–9)	7 (5–10)	5 (3–7)	6(4–7)	7 (5–10)	7 (5–10)	6 (4–9)	6 (4–9)
Normal 0–7 points, n (%)	2109 (59.4%)	1383 (52.7%)	561 (79.5%)	165 (75.0%)	511 (55.9%)	485 (52.8%)	559 (64.7%)	554 (64.9%)
Mild 8–10 points, n (%)	902 (25.4%)	702 (26.8%)	145 (20.5%)	55 (25.0%)	241 (26.4%)	272 (29.6%)	197 (22.8%)	192 (22.5%)
Excessive >10 points, n (%)	538 (15.2%)	538 (20.5%)	0 (.00%)	0 (.00%)	162 (17.7%)	161 (17.5%)	108 (12.5%)	107 (12.5%)

Systolic blood pressure, mmHg	130 (120–140)	130 (120–140)	120 (110–131)	130 (120–150)	130 (120–140)	130 (119–140)	129 (120–140)	130 (116–140)

Diastolic blood pressure, mmHg	79 (70–85)	80 (72–87)	71 (65–79)	80 (70–85)	80 (73–88)	80 (72–86)	77 (70–84)	76 (69–83)
Normal blood pressure, n (%)	2437 (68.7%)	1748 (66.6%)	578 (81.9%)	111 (50.5%)	605 (66.2%)	639 (69.6%)	601 (69.6%)	592 (69.4%)
High blood pressure, n (%)	1112 (31.3%)	875 (33.4%)	128 (18.1%)	109 (49.5%)	309 (33.8%)	279 (30.4%)	263 (30.4%)	261 (30.6%)

Apnoea–hypopnoea index, events/h	25 (16–39)	22 (15–35)	31 (21–46)	35 (23–57)	34 (22–47)	34 (21–49)	19 (14–25)	19 (14–26)

Heart rate response, b.p.m.	7.7 (5.6–10.5)	8.7 (6.4–11.3)	5.5 (4.2–7.1)	6.5 (4.8–8.40)	10.3 (7.5–12.7)	10.4 (7.9–12.9)	6.2 (4.8–7.8)	6.2 (4.9–7.54)

Hypoxic burden, %min/h	62.5 (39.3–107)	59.0 (36.6–109)	72.5 (51.9–103)	56.8 (34.4–107)	103 (61.4–155)	107 (63.3–162)	45.9 (31.1–61.5)	44.3 (31.6–61.2)

CPAP adherence at first 24 months^a	3.3 (1.2–5.2)	3.5 (1.6–5.2)	2.4 (.1–4.9)	1.9 (.0–5.3)	3.5 (1.5–5.3)		3.0 (.9–5.1)
0 h/night, n (%)	127 (7.87%)	53 (4.11%)	29 (13.4%)	45 (42.5%)	58 (6.83%)		69 (9.03%)
0–4 h/night, n (%)	818 (50.7%)	689 (53.4%)	107 (49.3%)	22 (20.8%)	421 (49.6%)		397 (52.0%)
≥4 h/night, n (%)	668 (41.4%)	548 (42.5%)	81 (37.3%)	39 (36.8%)	370 (43.6%)		298 (39.0%)

Follow-up duration, years	3.1 (2.1–4.6)	3.2 (2.2–4.6)	2.5 (1.1–4.0)	4.4 (3.0–5.9)	3.3 (2.2–4.8)	3.2 (2.1–4.7)	3.0 (2.0–4.5)	3.0 (2.0–4.5)

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Continuous variables are represented by the median (interquartile range). Dichotomous variables are represented by n (%).

Adherence data were available in 98%, 62%, and 95% of participants in the CPAP arm of SAVE, ISAACC, and RICCADSA, respectively.

Primary analysis

The primary endpoint occurred in 584 (16.5%) participants, 296 (16.6%) in the CPAP group, and 288 (16.3%) events in the usual-care group [adjusted hazard ratio (aHR) with CPAP 1.00 (95% CI .85–1.18)]. Within those with low-risk OSA, the endpoint occurred in 157 (18.2%) in the CPAP group and 127 (14.9%) in the usual-care group [aHR for CPAP vs usual care 1.22 (95% CI .96–1.54); Table 2]. Within the high-risk OSA group, there were 139 (15.2%) events in the CPAP group and 161 (17.5%) in the usual-care group [aHR for CPAP vs usual care .83 (95% CI .66–1.05)]. There was a significant interaction of risk group by treatment group favouring CPAP treatment in those at high-risk OSA [interaction HR (iHR) .69 (95% CI .50–.95); P_interaction = .024], which confirms our primary study hypothesis. Survival curves are shown in Figure 2A–C.

Table 2.

Effect of continuous positive airway pressure on the primary composite endpoint in high-risk vs low-risk obstructive sleep apnoea

Participant group	High-risk group			Low-risk group			High-risk vs low-risk interaction hazard ratio (95% CI)
	CPAP	Usual care	Hazard ratio (95% CI) n (%)	CPAP	Usual care	Hazard ratio (95% CI) n (%)
	n events/n subjects (%)		Hazard ratio (95% CI) n (%)	n events/n subjects (%)		Hazard ratio (95% CI) n (%)
All	139/914 (15.2%)	161/918 (17.5%)	.83 (.66–1.05) 1832 (51.6%)	157/864 (18.2%)	127/853 (14.9%)	1.22 (.96–1.54) 1717 (48.4%)	.69 (.50–.95) ^a
Without excessive sleepiness^b	113/752 (15.0%)	141/757 (18.6%)	.76 (.60–.98) 1509 (42.5%)	141/756 (18.7%)	109/746 (14.6%)	1.30 (1.01–1.66) 1502 (42.3%)	.59 (.41–.84)
Without increased blood pressure^c	82/605 (13.6%)	115/639 (18.0%)	.72 (.54–.95) 1244 (35.1%)	114/601 (19.0%)	84/592 (14.2%)	1.33 (1.00–1.76) 1193 (33.6%)	.54 (.36–.81)
Without increased blood pressure or excessive sleepiness	68/505 (13.5%)	103/536 (19.2%)	.65 (.48–.89) 1041 (29.3%)	102/537 (19.0%)	74/524 (14.1%)	1.35 (1.00–1.82) 1061 (29.9%)	.48 (.31–.74)

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CPAP, continuous positive airway pressure.

The primary statistical test comparison, i.e. P_interaction = .024. n (%) refers to sample size for the participant group and the percentage of the larger study population that the hazard ratio applies to.

Defined by Epworth sleepiness scale <11 units.

Defined by systolic blood pressure <140 mmHg and diastolic blood pressure <90 mmHg at baseline. The ‘Without increased blood pressure or excessive sleepiness’ group was defined by the exclusion of individuals who either had increased blood pressure or had excessive sleepiness, thus leaving a group characterized by non-increased blood pressure and non-excessive sleepiness levels. n events refer to the number of participants meeting the MACCE outcome endpoint. ‘All’ participants provided the analytic group for primary analysis. Successive rows describe secondary analyses performed in a restricted subpopulation. The hazard ratios for high-risk and low-risk groups describe the CPAP benefit (or harm) estimated from following Cox-proportional hazards mixed model structure: MACCE ~ CPAP + CPAP × Subgroup + Subgroup + Covariates + 1|Trial. Hazard ratio values below 1.0 indicate CPAP-related benefit. Bold indicates 95% confidence intervals (CIs) that do not overlap 1.0. The interaction hazard ratio (CPAP × Subgroup) describes how much extra risk reduction is obtained from CPAP treatment in high-risk OSA compared with low-risk OSA. A value below 1 indicates greater CPAP benefit in the high-risk group when compared with the low-risk group.

Kaplan–Meier survival curves showing the effect of continuous positive airway pressure on major adverse cardiovascular and cerebrovascular events in al-comers (*A, D, G*, and J), in those with high-risk (*C, F, I*, and L) and low-risk (*B, E, H*, and K) obstructive sleep apnoea in all participants (first row), in those without excessive sleepiness (Epworth sleepiness scale < 11; second row), without increased blood pressure (systolic/diastolic <140/90 mmHg; third row), and those without increased blood pressure or excessive sleepiness (bottom row). MACCE, major adverse cardiovascular and cerebrovascular events

Secondary analyses

The preferential benefit of CPAP in high-risk OSA seen in the primary analysis was found to be contingent on excessive sleepiness status and increased blood pressure (three-way interaction analysis, Supplementary data online, Table S2). When primary analysis was restricted to participants without excessive sleepiness (Table 2), the effect modification strengthened [iHR .59 (95% CI .41–.84)] and CPAP benefit [aHR for CPAP vs usual care .76 (.60–.98)] became evident within the 1509 non-sleepy participants with high-risk OSA (Table 2). Likewise, when analysis was restricted to participants without increased blood pressure (blood pressure <140/90 mmHg), effect modification was also strengthened [iHR .54 (95% CI .36–.81)], and CPAP benefit [aHR for CPAP vs usual care .72 (95% CI .54–.95)] became evident within the 1244 participants with high-risk OSA and non-elevated blood pressures (Table 2). Analysis restricted to participants with neither excessive sleepiness nor increased blood pressures illustrated further strengthened effect modification [iHR .48 (95% CI .31–.74)], and CPAP benefit [aHR for CPAP vs usual care .65 (95% CI .48–.89)] was evident within the 1041 participants with high-risk OSA (Table 2; baseline characteristics of patients without either excessive sleepiness or increased blood pressure are provided in Supplementary data online, Table S1).

In contrast, within low-risk OSA, the risk of MACCE was higher in those randomized to CPAP than in those randomized to usual care [without excessive sleepiness, aHR 1.30 (95% CI 1.01–1.66); without increased blood pressure, HR 1.33 (95% CI 1.00–1.76); without either increased blood pressure or excessive sleepiness, HR 1.36 (95% CI 1.01–1.83); Table 2]. Survival curves are shown in Figure 2D–L.

Additional analyses

Within usual care, analysis confirmed that high-risk vs low-risk OSA was associated with increased likelihood of MACCE [all patients, aHR 1.32 (95% CI 1.02–1.69); without excessive sleepiness, HR 1.45 (95% CI 1.11–1.89); without increased blood pressure: HR 1.36 (95% CI 1.01–1.83); without either increased blood pressure or excessive sleepiness, HR 1.51 (95% CI 1.10–2.06)].

To test the dependence of our findings on CPAP use per se, we re-examined findings by CPAP adherence groups. Within high-risk OSA, a slightly strengthened effect of CPAP on MACCE risk reduction was observed (Table 3, compare with Table 2); a dose–response relationship was observed between non-users, partial users (>0 and <4 h/night), and CPAP adherent patients (≥4 h). Likewise, a tendency for increased MACCE risk remained present in low-risk OSA groups using CPAP (Table 3).

Table 3.

Adherence analysis

Hazard ratio (95% CI) n CPAP: n usual care	CPAP non-users vs us usual care			CPAP >0 and <4 h vs usual care			CPAP ≥ 4 h vs usual care
Participant group	High-risk group	Low-risk group	Interaction hazard ratio (95% CI)	High-risk group	Low-risk group	Interaction hazard ratio (95% CI)	High-risk group	Low-risk group	Interaction hazard ratio (95% CI)
All	.93 (.50–1.72) 58:918	.99 (.54–1.80) 69:853	.94 (.40–2.19)	.97 (.74–1.29) 421:918	1.35 (1.02–1.79) 397:853	.72 (.49–1.07)	.72 (.53–.99) 370:918	1.14 (.83–1.57) 298:853	.64 (.41–.99)
Without excessive sleepiness^a	.89 (.48–1.67) 56:757	.96 (.52–1.80) 66:746	.93 (.39–2.22)	.81 (.59–1.12) 341:757	1.46 (1.08–1.97) 334:746	.56 (.36–.86)	.73 (.52–1.02) 294:757	1.23 (.87–1.72] 258:746	.59 (.37–.95)
Without increased blood pressure^b	1.01 (.44–2.31) 32:639	1.08 (.52–2.24) 47:592	.93 (.31–2.80)	.82 (.58–1.17) 287:639	1.31 (.93–1.85) 277:592	.63 (.39–1.03)	.62 (.42–.92) 243:639	1.42 (.98–2.05) 205:592	.43 (.25–.75)
Without increased blood pressure or excessive sleepiness	.99 (.43–2.26) 30:536	1.13 (.54–2.35) 46:524	.87 (.29–2.62)	.74 (.50–1.08) 238:536	1.34 (.92–1.93) 239:524	.55 (.32–.93)	.56 (.36–.86) 197:536	1.43 (.97–2.11) 182:524	.39 (.22–.70)

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Primary, secondary, and exploratory analyses repeated, including subgroups of patients allocated to CPAP treatment based on levels of adherence to CPAP at 24 months. Patients with unknown adherence were excluded from all analyses (n = 165). A strengthened signal in the CPAP adherent group would be consistent with benefit in high-risk OSA that is contingent on use of the intervention. It is also possible that the strengthened signal in the CPAP adherent group could be driven in part by healthy user bias (i.e. the ‘usual care’ comparison group includes all patients, regardless of whether or not they make up an unbiased reference group). We also note that we observed signs of a dose-response relationship between non-users, partial users (>0 and <4 h/night), and CPAP adherent patients (≥4 h), consistent with an interpretation that CPAP use per se is beneficial for MACCE risk reduction within high-risk OSA.

Bold values indicate statistically significant results (p < 0.05).

Defined by Epworth sleepiness scale <11 units.

Defined by systolic blood pressure <140 mmHg and diastolic blood pressure <90 mmHg at baseline.

When examining each trial separately, the magnitude of effect modification and CPAP benefit in high-risk OSA (Supplementary data online, Table S3) showed a consistent direction across trials, and the findings remained stable in secondary analyses restricted to patients without excessive sleepiness or increased blood pressure. In robustness analysis, effect modification and CPAP benefit in high-risk OSA increased with progressively stricter sleepiness and blood pressure criteria (Supplementary data online, Table S4). Exploratory analysis revealed that optimal statistical power was observed [aHR .54 (95% CI .37–.79)] in the 19% of participants with high-risk OSA, Epworth <8 units, and blood pressure <140/90 mmHg, and optimal MACCE endpoints saved was calculated for 39% of participants with high-risk OSA, Epworth <11 units, and blood pressure <160/90 mmHg (N_saved = 22/1000 patients).

When employing exploratory alternative thresholds for heart rate response and hypoxic burden to define high-risk OSA (Supplementary data online, Tables S5–S7 and Appendix), findings were directionally consistent. However, findings appeared consistently weakened when using heart rate response alone or hypoxic burden alone to define high-risk OSA, compared with primary analysis (Supplementary data online, Table S8). In both women and men, a progressive lowering of the high-risk hazard ratio (CPAP vs usual care effect within high-risk OSA) and the iHR (differential CPAP benefit in high-risk vs low-risk OSA) was observed as the analysis was restricted to patients without excessive sleepiness, increased blood pressure, or neither characteristic (Supplementary data online, Table S9). Findings were consistent for separate components of the MACCE composite outcome; notably, MACCE defined by a composite of cardiovascular death, myocardial infarction, or stroke provided a stronger effect in all analyses (Table 4). Furthermore, redefining high-risk OSA based on apnoea–hypopnoea index or oxygen desaturation index did not result in any significant or meaningful effect modification (Supplementary data online, Table S10). Finally, findings were also consistent in additional analyses restricted to patients with diagnosed hypertension at baseline (Supplementary data online, Table S11) or those without a known history of atrial fibrillation (Supplementary data online, Table S12).

Table 4.

Findings based on separate components of the major adverse cardiovascular and cerebrovascular event composite outcome

High-risk hazard ratio (95% CI) Low-risk hazard ratio (95% CI) Interaction hazard ratio (95% CI)	MACCE all	CV death, MI, stroke	CV death	MI	Stroke
Participant group

All	.83 (.66–1.05)	.84 (.61–1.16)	.77 (.39–1.50)	.96 (.58–1.60)	.90 (.58–1.40)
	1.22 (.96–1.54)	1.24 (.88–1.74)	1.57 (.66–3.75)	1.38 (.85–2.23)	1.14 (.70–1.58)
	.69 (.50–.95)	.68 (.43–1.09)	.49 (.16–1.47)	.70 (.34–1.42)	.79 (.41–1.53)

Without excessive sleepiness (≥11 units)	.76 (.60–.98)	.76 (.53–1.09)	.70 (.34–1.45)	.81 (.46–1.42)	1.00 (.61–1.62)
	1.30 (1.01–1.66)	1.36 (.95–1.97)	1.80 (.67–4.81)	1.62 (.95–2.77)	1.14 (.69–1.89)
	.59 (.41–.84)	.56 (.33–.93)	.39 (.11–1.32)	.50 (.23–1.09)	.88 (.43–1.76)

Without increased blood pressure (≥140/90 mmHg)	.72 (.54–.95)	.59 (.39–.89)	.64 (.30–1.40)	.69 (.36–1.32)	.74 (.42–1.32)
	1.33 (1.00–1.76)	1.53 (.98–2.37)	.94 (.24–3.78)	1.51 (.84–2.70)	1.49 (.75–2.98)
	.54 (.36–.81)	.39 (.21–.71)	.68 (.14–3.35)	.46 (.19–1.10)	.50 (.20–1.23)

Without excessive sleepiness (≥11 units)	.65 (.48–.89)	.55 (.35–.87)	.60 (.25–1.41)	.63 (.33–1.23)	.83 (.44–1.57)

or increased blood pressure (≥140/90)	1.35 (1.00–1.82)	1.63 (1.01–2.64)	1.42 (.24–8.50)	1.68 (.88–3.21)	1.36 (.67–2.75)

	.48 (.31–.74)	.34 (.17–.65)	.42 (.06–3.08)	.38 (.15–.95)	.61 (.24–1.58)

Optimal future trial criteria:	.54 (.37–.79)	.46 (.27–.80)	.49 (.17–1.42)	.47 (.21–1.04)	.65 (.30–1.43)

Without increased sleepiness (≥8 units)	1.35 (.95–1.90)	1.83 (1.02–3.30)	∞(0–∞)	1.77 (.79–3.95)	1.68 (.74–3.80)

or increased blood pressure (≥140/90)	.40 (.24–.67)	.25 (.11–.56)	0 (0–∞)	.26 (.09–.82)	.39 (.13–1.21)

Optimal endpoints mitigated in the OSA population criteria:	.70 (.54–.91)	.64 (.44–.94)	.75 (.35–1.61)	.76 (.43–1.36)	.78 (.45–1.35)

Without excessive sleepiness (≥11 units)	1.32 (1.02–1.71)	1.37 (.94–2.01)	1.74 (.59–5.12)	1.70 (.96–3.01)	1.09 (.64–1.84)

or increased blood pressure (≥160/100)	.53 (.37–.77)	.47 (.27–.80)	.43 (.11–1.62)	.45 (.20–1.02)	.72 (.34–1.53)

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Primary, secondary, and exploratory analyses repeated for components of the composite adverse cardiovascular outcome (MACCE). The analysis presented is exploratory in nature. Note that the findings were consistent between the primary MACCE definition (‘MACCE all’) and the composite of CV death, MI, and stroke. The hazard ratios appeared somewhat smaller for the composite of CV death, MI, and stroke. No separate component appeared to be a driver of the overall study findings. The number of subjects in the high-risk subgroup, from top to bottom row, is 1832 (51.6%), 1509 (42.5%), 1244 (35.1%), 1041 (29.3%), 688 (19.4%), and 1391 (39.2%). The number of outcome events for MACCE per original definition—across high risk and low risk, both CPAP and usual care—was 584, 504, 395, 347, 247, and 460 for Rows 1–6, respectively. The number of outcome events for the composite of CV death, MI, and stroke was 311, 264, 192, 165, 117, and 235, respectively. The number of events for CV death was 60, 51, 36, 29, 18, and 46, respectively. The number of adverse events for MI was 132, 112, 87, 78, 54, and 101, respectively. The number of events for stroke was 148, 127, 83, 71, 52, and 109, respectively.

Bold values indicate statistically significant results (p < 0.05).

CV, cardiovascular; MI, myocardial infarction.

Discussion

Our reanalysis of the three major secondary prevention randomized CPAP trials has shown that CPAP preferentially reduces risk of MACCE in individuals stratified by high-risk vs low-risk OSA according to elevated OSA-related heart rate responses or hypoxic burden (Structred Graphical Abstract). Notably, analysis restricted to patients without excessive sleepiness (Epworth <11), or without increased blood pressure (systolic/diastolic levels <140/90 mmHg), strengthened the preferential benefit (effect modification), and yielded a meaningful reduction in MACCE risk with CPAP within the high-risk OSA group (24% and 28% relative risk reduction vs usual care). Analysis further restricted to patients with neither excessive sleepiness nor increased blood pressure further strengthened the preferential benefit and yielded a 35% relative risk reduction in high-risk OSA participants. Conversely, in the group with low-risk OSA, the risk of MACCE was higher in CPAP vs usual care, providing evidence of harm that counters benefits seen in high-risk OSA. Our work demonstrates that the phenotypic subgroup of OSA characterized by greater apnoea–hypopnoea–related cardiac acceleration, and hypoxaemia exhibits a preferential effect of CPAP for the secondary prevention of major long-term cardiovascular outcomes. Our study provides novel evidence—based on all three large trials—that a recognizable subgroup of individuals with OSA may exhibit long-term cardiovascular benefit from CPAP and could be targeted for MACCE risk reduction.

Novel insights

The current study expands on accumulating observational cohort study data demonstrating increased cardiovascular risks in individuals with elevated OSA-related heart rate responses and/or hypoxic burden.^22–24,26 In the Sleep Heart Health Study, the Osteoporotic Fractures in Men study, and the Multi-Ethnic Study of Atherosclerosis, individuals with increased hypoxic burden exhibited an increased risk of cardiovascular mortality and incident cardiovascular disease compared with individuals with lower hypoxic burden.^22–24,26 In the Sleep Heart Health Study, adverse cardiovascular outcomes were also augmented in people with increased heart rate responses.²⁴ Building on these observational findings, the usual care data in the current study revealed that high-risk OSA was also associated with a 32–51% increased risk of MACCE, demonstrating consistency across community-based cohort studies and the clinical trial patient population.

Using data from the three large CPAP trials, the current study demonstrated that individuals with high-risk vs low-risk OSA exhibit differential effects of CPAP for MACCE risk attenuation. These findings are consistent with smaller analyses of the RICCADSA and ISAACC trials^30,31 and support the notion that high-risk OSA drives the elevated risks seen in observational analyses, and that such risks are modifiable with intervention. Taken together with short-term treatment response studies examining blood pressure and cardiac function,^35,39 there is now a substantial body of evidence indicating that individuals with high-risk sleep apnoea characteristics preferentially benefit from sleep apnoea interventions for cardiovascular risk reduction.

A meaningful CPAP benefit in high-risk OSA was not unconditionally observed, but rather was limited to high-risk OSA individuals without increased sleepiness or increased blood pressure. A greater benefit in non-sleepy individuals will appear controversial given community-cohort observational evidence that sleepy individuals with OSA have greater cardiovascular risks than non-sleepy individuals.^40,41 However, not all observational data support this association,^29,32 and available CPAP response data instead suggested an increase in MACCE risk reduction in less sleepy patients.³² Notably, non-sleepy status has been found to accompany increased sympathoexcitation as well as greater heart rate fluctuations in response to apnoeas/hypopnoeas^42–44 (albeit not in all studies⁴⁵), and may provide a physiological basis for the strengthened CPAP-related MACCE risk reduction. Likewise, a greater CPAP benefit in high-risk OSA patients who have lower blood pressure may appear unexpected if major beneficial effects of CPAP are exerted via blood pressure lowering.^46–48 For example, in a recent meta-analysis, CPAP was found to have the greatest effect on blood pressure lowering in individuals with uncontrolled hypertension, and little impact on those with controlled hypertension.⁴⁹ However, even in uncontrolled hypertension the effect of CPAP on blood pressure is relatively modest (<3 mmHg).⁴⁹ Thus, those with baseline systolic/diastolic levels at 140/90 mmHg or higher, with CPAP, are likely continue to exhibit a residual high blood pressure, and the attendant blood pressure risks may overwhelm the benefit of ameliorating high-risk OSA. If true, our findings appear to challenge the notion the CPAP exerts its primary long-term cardiovascular benefit via blood pressure lowering. Alternatively, patients without elevated blood pressure may have more reversible cardiovascular disease status, and thereby greater remaining scope for CPAP-related benefit; this notion is consistent with analyses from ISAACC suggesting that absence of prior cardiovascular disease³³ or absence of baseline hypercholesterolaemia³⁴ might yield greater CPAP benefits.

While our work focused on CPAP benefit in high-risk individuals, the corollary is that there appears to be treatment-related hazard associated with CPAP in low-risk OSA. As was the case for CPAP benefit in the high-risk group, the excess cardiovascular risk associated with CPAP use was greater in non-sleepy individuals and those without high blood pressure (Table 2), effects observed even in our on-treatment analyses (Table 3). A potential explanation may lie with recent findings of CPAP-related elevation of a pro-inflammatory lung-stretch biomarker in several studies, including RICCADSA.^50–52 Alternatively, administration of CPAP via the mask apparatus may cause sleep disruption particularly in non-sleepy patients; indeed use of sham CPAP is known to increase light sleep and reduce restorative deep sleep and rapid-eye-movement sleep stages⁵³ that may have downstream cardiovascular consequences.

Clinical implications

Currently, clinical CPAP administration for OSA focuses on symptomatic relief and improvement of quality of life, on the basis that randomized trial-level evidence for cardiovascular risk reduction has been lacking.⁵⁴ By delineating a subgroup of patients who exhibited long-term cardiovascular benefit from CPAP across multiple trials, our study provides the strong evidence suggesting that OSA treatment can yield meaningful improvements in key cardiovascular outcomes, and thus an opportunity to treat a subgroup of people with OSA for cardiovascular health purposes. Notably, favourable effects were detected despite relatively modest overall adherence (3.4 h), suggesting findings may be generalizable to real-world settings. Across multiple criteria, meaningful magnitudes of risk reduction in sizeable subgroups were observed. Most notably, a subgroup of 39% of OSA patients was identified (Epworth <11 units, blood pressure <160/100 mmHg) who exhibited an optimal CPAP-related reduction in MACCE events by an estimated 23 per thousand OSA patients. For the design of an optimal future trial, a subgroup of 19% of OSA patients (Epworth <8 units, blood pressure <140/90 mmHg) exhibited a 46% CPAP-related relative risk reduction.

On the other hand, our study raises concern that a CPAP-related hazard appears in low-risk OSA individuals, at least in cardiovascular patients without sleepiness or increased blood pressures. Fortunately, for this subgroup, there is already a reduced clinical impetus to treat, given minimal expectation of symptomatic benefit per non-sleepy status, or a blood pressure–lowering effect given non-elevated blood pressure. Our data suggest there is no rationale for CPAP administration for cardiovascular risk mitigation in this subgroup.

Limitations

The study has several limitations for consideration. First, the study requires cautious interpretation due to the nature of post hoc analysis; heart rate response and hypoxic burden measures were developed after the trials, thus analysis was not pre-specified. We specified the aim of examining these two factors as determinants of CPAP benefit prior to analysing the pooled data, and a range of sensitivity analyses suggest the findings are robust, reproducible across trials, and unlikely related to chance. Second, the findings may not apply to patients with OSA without cardiovascular disease, and it is also unclear how much the trial population differs from typical clinical populations.⁵⁵ Third, the method to obtain pulse rate response and hypoxic burden differed subtly between trials, with oximetry-based events used in ISAACC.³¹ Fourth, the study population was predominantly male, such that a CPAP benefit in women with high-risk OSA remains less certain; of interest, however, hazard ratio magnitudes appeared strongest in women. Fifth, the definition of MACCE varied between trials; notably, analysis using a harmonized composite endpoint of myocardial infarction, stroke or cardiovascular death yielded strengthened effect estimates despite half the endpoint events. Sixth, the in-office blood pressure measurements were used to identify individuals with increased blood pressure; future studies with more accurate measurement of blood pressure (e.g. 24 h blood pressure monitoring) may be needed to confirm these findings. Seventh, modest adherence to treatment remains a major limitation, but nonetheless, a meaningful cardiovascular benefit from CPAP vs usual care was evident.

Conclusions

In summary, in high-risk OSA, defined by augmented OSA-related pulse rate acceleration and/or hypoxaemia, CPAP provides a preferential benefit for MACCE prevention in patients with cardiovascular disease. The differential benefit is further strengthened in individuals without excessive sleepiness or elevated blood pressure, in whom a CPAP treatment effect was clinically meaningful. Continuous positive airway pressure–related benefits in high-risk OSA were observed alongside harms in low-risk OSA subgroups, providing a putative mechanistic explanation for the overall negative trial results. Ultimately, our findings provide a much-needed basis for recognising favourable long-term cardiovascular responses to CPAP for future prospective evaluations.

Supplementary Material

Online Supplement

NIHMS2129181-supplement-Online_Supplement.pdf^{(473.7KB, pdf)}

Supplementary data are available at European Heart Journal online.

Key Question

Randomized trials of continuous positive airway pressure (CPAP) have failed to show benefit for secondary cardiovascular outcome prevention. Does CPAP confer cardiovascular benefit preferentially in patients with high-risk obstructive sleep apnoea (OSA)?

Key Finding

In this pooled analysis of three trials, the benefit of CPAP in reducing major adverse cardiovascular and cerebrovascular events was greater in patients with high-risk OSA compared to those with low-risk OSA. In low-risk OSA, CPAP may increase cardiovascular risk.

Take Home Message

Assessment of OSA phenotypes may guide the indication for CPAP to reduce cardiovascular risk.

Acknowledgements

The authors are very grateful to the investigators and all those involved in the design and data collection for the SAVE, ISAACC, and RICCADSA parent studies.

Funding

A.A. was supported by the National Heart, Lung, and Blood Institute (R01HL153874 and R21 HL161766), American Heart Association (19CDA34660137), and the American Academy of Sleep Medicine (SR-2217). S.A.S. is supported by National Heart, Lung, and Blood Institute (R01HL146697 and R01HL168067). A.V.Z. is supported by National Heart, Lung, and Blood Institute (K23HL159259). F.B. is supported by the Generalitat de Catalunya, Vetenskapsrådet (521-2011-537 and 521-2013-3439), the Swedish Heart-Lung Foundation (20080592, 20090708, and 20100664), ResMed Foundation.

Disclosure of Interest

All authors have completed ICMJE uniform disclosure form and declare: A.A. reports grant support from Somnifix and serves as a consultant for Somnifix, Respicardia, Eli Lilly, Amgen, Inspire, Cerebra and Apnimed. Apnimed is developing pharmacological treatments for OSA. A.A.’s interests were reviewed by Brigham and Women’s Hospital and Mass General Brigham in accordance with their institutional policies. A.W. has financial interest in Apnimed, a company developing pharmacologic therapies for sleep apnoea; his interests are managed by Brigham and Women’s Hospital and Mass General Brigham in accordance with their conflict-of-interest policies. A.W. also consults for Apnimed, Nox Medical, Inspire, Somnifix, Mosanna, iNos Technologies, and Takeda, and received grants from Somnifix. S.R. received personal fees from Eli Lilly Inc. and is an unpaid consultant to Apnimed Inc. and an unpaid Board of Director for the National Sleep Foundation and Alliance of Sleep Apnea Partners. L.M. reports grant support from Apnimed. S.A.S. receives personal fees as a consultant for Nox Medical, Merck, Apnimed, Respicardia, Inspire, Lilly, LinguaFlex, and Forepont outside the submitted work and receives grant support from Apnimed, Prosomnus, and Dynaflex for unrelated studies. D.P.W. consults for Bairitone, Cerebra Health, Cryosa, Mosanna, Onera, Philips Respironics, Resonea, Xtrodes, Apnimed, and SleepRes. D.J.G. receives consulting fees from Apnimed and Signifier Medical Technologies. Y.P. reports grant support from the ResMed Foundation. A.V.Z. works as a consultant for Restful Robotics Inc. and receives grant support from ResMed Co. N.E., D.V., and L.P. have no conflict of interest to disclose.

Footnotes

Ethical Approval

The SAVE, RICCADSA, and ISAACC trials were approved by the relevant institutional ethics committees, and all participants provided written informed consent prior to enrolment.

Pre-registered Clinical Trial Number

The SAVE, RICCADSA, and ISAACC trials were registered at ClinicalTrials.gov. The registration numbers are NCT00738179, NCT00519597, and NCT01335087.

Data Availability

Deidentified signals, covariates, and outcomes data were obtained under separate collaborative agreements from the parent studies. Raw signals data can be obtained through agreements with parent studies. Individual data presented in the current study can be obtained by request but may require a three-way data use agreement with parent trial investigators. Methods for calculating pulse rate response and hypoxic burden have been published, and tools for their calculation have been made freely available for non-industry academic use.

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Associated Data

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Supplementary Materials

Online Supplement

NIHMS2129181-supplement-Online_Supplement.pdf^{(473.7KB, pdf)}

Data Availability Statement

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PERMALINK

Cardiovascular benefit of continuous positive airway pressure according to high-risk obstructive sleep apnoea: a multi-trial analysis

Ali Azarbarzin

Daniel Vena

Neda Esmaeili

Andrew Wellman

Lucía Pinilla

Ludovico Messineo

Andrey Zinchuk

Raichel Alex

Mathias Baumert

Kelly A Loffler

Craig S Anderson

David P White

Susan Redline

Daniel J Gottlieb

Ferran Barbé

Yuksel Peker

Manuel Sánchez-de-la-Torre

Doug McEvoy

Scott A Sands

Abstract

Background and Aims

Methods

Results

Conclusions

Structured Grahical Abstract

Introduction

Methods

Study design

Participants

Figure 1.

Procedures

Continuous positive airway pressure intervention

Cardiovascular endpoint

Derivation of heart rate response and hypoxic burden

High-risk obstructive sleep apnoea

Statistical analysis

Primary analysis

Secondary analyses

Additional analyses

Results

Table 1.

Primary analysis

Table 2.

Figure 2.

Secondary analyses

Additional analyses

Table 3.

Table 4.

Discussion

Novel insights

Clinical implications

Limitations

Conclusions

Supplementary Material

Key Question

Key Finding

Take Home Message

Acknowledgements

Funding

Disclosure of Interest

Footnotes

Data Availability

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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