Abstract
Background
Obstructive sleep apnea (OSA) is prevalent among patients with cardiovascular disease and is associated with increased risk of major adverse cardiovascular events (MACE). Continuous positive airway pressure (CPAP) is the standard treatment for OSA, but its impact on cardiovascular outcomes remains uncertain, particularly in randomized controlled trials (RCTs).
Objectives
To evaluate the effect of CPAP therapy on cardiovascular outcomes in patients with OSA, and to explore the influence of adherence on treatment efficacy.
Methods
We conducted a systematic review and meta-analysis of RCTs comparing CPAP with placebo or usual care in adults with OSA. Databases including PubMed, Scopus, Ovid, and CINAHL were searched from inception to December 2024. Primary outcome was MACE; secondary outcomes included cardiovascular mortality, all-cause mortality, myocardial infarction, stroke, angina, heart failure, and new-onset atrial fibrillation. Subgroup analyses were performed based on CPAP adherence (≥4 hours/night vs <4 hours/night). Risk ratios (RRs) with 95 % confidence intervals (CIs) were pooled using fixed-effects model.
Results
Eleven RCTs comprising 6139 participants were included. Overall, CPAP did not significantly reduce MACE (RR = 1.00; 95 % CI: 0.87–1.14) or secondary cardiovascular outcomes. However, in patients adherent to CPAP (≥4 hours/night), MACE was significantly reduced (RR = 0.71; 95 % CI: 0.52–0.97), and cardiovascular mortality decreased (RR = 0.36; 95 % CI: 0.14–0.91). Subgroup analyses revealed no significant benefits in non-adherent patients. Heterogeneity was low for most outcomes.
Conclusion
CPAP therapy does not significantly reduce overall cardiovascular risk in OSA patients, except among adherent individuals. These findings underscore adherence as a critical determinant of CPAP’s cardiovascular efficacy. Future trials should prioritize strategies to optimize adherence to fully evaluate CPAP’s cardioprotective potential.
Keywords: Continuous airway pressure, Obstructive sleep apnea, Cardiovascular outcomes, Major adverse cardiovascular events
1. Introduction
Obstructive sleep apnea (OSA) is a chronic sleep-related breathing disorder characterized by recurrent episodes of upper airway collapse during sleep, leading to intermittent hypoxemia and reduced sleep quality. Common signs of OSA include snoring, daytime sleepiness, and witnessed apneas [1].
OSA is associated with a range of complications, including gastrointestinal conditions, metabolic disorders such as diabetes, and renal impairment [2]. In addition, observational studies have demonstrated an association between OSA and cardiovascular diseases, indicating that OSA is linked to an increased risk of cardiovascular events such as hypertension, myocardial infarction, heart failure, arrhythmia, stroke, and sudden cardiac death [3]. The prevalence of OSA among patients with established cardiovascular disease is estimated to be between 40 % and 60 %, revealing the clinical overlap between these conditions [4–6].
Continuous Positive Airway Pressure (CPAP) is currently considered the treatment of choice for OSA and is effective at relieving symptoms and improving quality of life [1]. CPAP has also been shown to lower blood pressure, particularly in patients with resistant hypertension, and to improve metabolic outcomes [7,8]. However, its benefit in reducing cardiovascular events has not been consistently confirmed by clinical trials [3].
The inconsistent evidence of the cardiovascular benefits of CPAP in clinical trials may be attributed to low levels of adherence to CPAP therapy, limitations in trial design and failure to account for the heterogeneity of OSA [3]. Moreover, previous meta-analyses suggested that the lack of cardiovascular benefit is largely explained by poor CPAP adherence [9,10].
Given the high prevalence of OSA in patients with cardiovascular disease and the ongoing uncertainty regarding CPAP’s impact on cardiovascular outcomes, a comprehensive synthesis of randomized controlled trial (RCT) evidence is warranted. Importantly, our meta-analysis incorporates a larger number of contemporary RCTs than previous reviews and evaluates a broader range of cardiovascular outcomes, providing a more comprehensive and an updated evaluation of whether CPAP therapy is effective in reducing cardiovascular events compared with usual care or placebo in patients with OSA.
2. Methodology
We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement guidelines (PRISMA) during the preparation of this systematic review in reporting our methodology and findings [11].
2.1. Search strategy
We conducted a systematic literature search to identify all RCTs comparing CPAP therapy with placebo or usual care in patients with OSA. Searches were performed in PubMed, Scopus, Ovid, and CINAHL from inception to December 2024, with no language restrictions. The search strategy combined specific keywords and Medical Subject Headings (MeSH) terms relevant to our study objectives. The search strategy consisted of the following predefined terms and Boolean operators to: “Obstructive Sleep Apnea,” “Sleep Apnea Syndromes,” “OSA,” “Continuous Positive Airway Pressure,” “CAP,” “Positive Airway Pressure,” “Cardiovascular Diseases,” “Major Adverse Cardiovascular Events,” “MACE,” “Myocardial Infarction,” “Stroke,” “Heart Failure,” and “Mortality.” Additionally, we manually screened the reference lists of all eligible studies and relevant prior meta-analyses to identify any additional studies not retrieved through the initial search.
2.2. Study selection criteria
Studies were eligible for inclusion if they met the following criteria: (1) RCT; (2) compared CPAP with placebo or usual care; (3) included adult patients diagnosed with OSA; and (4) reported at least one of the following outcomes: Major Adverse Cardiovascular Events (MACE), cardiovascular mortality, all-cause mortality, stroke, new-onset atrial fibrillation, myocardial infarction, heart failure, or angina. We excluded non-randomized studies, studies on central sleep apnea, case reports, editorials, reviews, and theses without original data.
The screening process was performed independently by two reviewers (SA and ML) in two stages: first, the titles and abstracts of retrieved studies were assessed for relevance, followed by full-text review of potentially eligible studies. Discrepancies were resolved through discussion until consensus was reached. Screening was conducted using Rayyan software (https://www.rayyan.ai/).
2.3. Data extraction
Four authors independently extracted data using a standardized online data extraction form. Extracted information was categorized into the following domains: (1) study characteristics, including key methodological aspects; (2) baseline characteristics of the study population, such as age, sex, and body mass index (BMI); (3) quality assessment, conducted using the Cochrane Risk of Bias tool (ROB 1); and (4) outcomes, including the primary outcome (MACE, as defined per each study) and secondary outcomes (cardiovascular mortality, all-cause mortality, stroke, new-onset atrial fibrillation, myocardial infarction, heart failure, and angina). Outcomes were reported at the longest follow-up.
2.4. Quality assessment of the included studies
Two authors (SA and ML) independently evaluated the methodological quality of the included RCTs using the Cochrane Risk of Bias (ROB 2) tool, assessing five domains: bias arising from the randomization process, bias due to deviations from intended interventions, bias due to missing outcome data, bias in measurement of the outcome, and bias in selection of the reported result [12]. Each domain was graded as having a low risk, some concerns, or high risk of bias. Discrepancies between reviewers were resolved through discussion or, when necessary, consultation with a third reviewer.
2.5. Data analysis and synthesis
For the meta-analyses, risk ratios (RRs) with 95 % confidence intervals (CIs) were used for all the categorical outcomes. Data from variables reported in at least two studies were pooled using the Mantel–Haenszel method.
Heterogeneity between studies was assessed by visually inspecting forest plots and calculating the Chi-square test and the I2 statistic. If significant heterogeneity was detected (I2 > 50 % or Chi-square p < 0.1), a random-effects model was applied to account for differences in study methods and participant characteristics; otherwise, a fixed-effects model was used [13]. Sensitivity analyses were conducted by sequentially excluding studies to test the robustness of the findings and to assess the influence of individual studies on the overall results.
Subgroup analyses were conducted according to mean CPAP adherence (<4 hours/night vs ≥4 hours/night). All p-values were two-tailed and considered statistically significant at ≤0.05. All statistical analyses were performed using Review Manager (RevMan), version 5.4 (Cochrane Collaboration, Copenhagen, Denmark).
2.6. Publication bias
Assessment of publication bias was not feasible because fewer than 10 studies were included for each outcome, which is below the recommended threshold for reliable funnel plot evaluations [14].
3. Results
3.1. Search results
As illustrated in Fig. 1, a total of 2266 records were retrieved from four electronic databases. After removing duplicates, 1792 unique records remained for title and abstract screening. Of these, the majority were excluded due to being reviews, editorials, conference abstracts, non-randomized designs, or irrelevant to the topic of interest. Subsequently, a total of 15 full-text articles were assessed for eligibility. After full-text review, 4 studies were excluded for reasons such as inclusion of patients with central sleep apnea, lack of cardiovascular outcomes, or use of alternative interventions. Ultimately, 11 RCTs meeting all inclusion criteria were included in the final meta-analysis.
Fig. 1.
PRISMA study flow diagram.
3.2. Study and baseline characteristics
A total of 11 RCTs were included, enrolling 6139 participants (CPAP = 3056; control = 3083), with individual study sample sizes ranging from 70 to 2687. The mean follow-up duration ranged from 3 months to 56.9 months. Diagnostic methods for obstructive sleep apnea included polysomnography, respiratory polygraphy, or home sleep-study screening device. The baseline characteristics of included studies are outlined in Table 1.
Table 1.
Characteristics of included studies.
| Study ID | Study design | Number of participants | Follow-up duration (months) | CPAP adherence time (hour/night)b | Groups | OSA assessment |
|---|---|---|---|---|---|---|
| Parra et al. [35] | Prospective, randomised, controlled and multicentre study | 126 | 60 | 5.3 (±1.9) | nCPAP/no active intervention | Polysomnography |
| Barbe et al. [36] | Multicenter, parallel-group, randomized controlled trial | 725 | 48 | 5 (2.18, 6.25) | CPAP/no active intervention | Polysomnography or cardiorespiratory study |
| Craig et al. [37] | Multicentre, randomised controlled, parallel, hospital-based trial | 391 | 6 | 2:39 (0:36, 4:59) | CPAP/standard care | Overnight respiratory polygraphy |
| McMillan et al. [38] | Multicenter, randomized trial | 278 | 12 | 01:26 (00:04, 04:45) | CPAP with best supportive care/best supportive care alone | Overnight respiratory polygraphy |
| Gottlieb et al.a [39] | Four-site, randomized, parallel-group clinical trial | 184 | 3 | 3.5 (±2.7) | CPAP/nocturnal supplemental oxygen | Assessed using Berlin Questionnaire for OSA screening |
| Huang et al. [40] | Prospective, randomized, single-center clinical trial of parallel groups | 83 | 36 | 4.5 (±1.1) | CPAP/no active intervention | Polysomnography |
| McEvoy et al. [15] | International, multicenter, randomized, parallel-group, open-label trial. | 2687 | 44 | 3.3 (±2.3) | CPAP plus usual care/usual care alone | Assessed using home sleep study device (ApneaLink, ResMed) with ODI ≥12; data reviewed centrally |
| Peker et al. [41] | Single-center (2 sites), prospective, open-label, randomized, parallel, interventional, superiority trial | 244 | 57 | 6.6 (±1.3) | CPAP/no intervention | Assessed using home cardiorespiratory polygraphy (Embletta PDS) with AHI ≥15/h; PSG in hospital for confirmation |
| de-la-Torre et al. [16] | Multicentre, open-label, parallel-group, randomised controlled trial | 1255 | 40.2 | 2.78 (±2.73) | CPAP plus usual care/usual care alone | Respiratory polygraphy (Embletta, ResMed, Bella Vista, NSW, Australia) |
| Traaen et al. [42] | Parallel-group, open-label randomised controlled trial | 108 | 5 | 4.7 (±1.8) | Autotitrating CPAP plus usual care/usual care alone | Respiratory polygraphy |
| Gupta et al. [43] | Single blind randomized control trial | 70 | 12 | 4.2 (±1.32) | Posttitration nightly CPAP/best medical treatment | Polysomnography |
CPAP = continuous positive airway pressure; nCPAP = nasal continuous positive airway pressure.
Information is reported for only CPAP and NSO groups.
Data are presented as mean (SD), median (25th, 75th percentiles).
The weighted mean age was 60.44 years (range: 51.8–71.3 years), and 81.6 % of participants were male. Obesity was common, with weighted mean BMI of 29.72 ranging from 24.85 to 34.7 kg/m2. The weighted mean neck circumference was 41.29 cm, ranging from 36.3 cm to 44.0 cm. Baseline AHI and ESS values for each study are presented in Table 2.
Table 2.
Baseline clinical characteristics in CPAP versus. Control group.
| Study ID | Group | Mean Age, years | Male N (%) | Mean BMI | Mean neck circumference (cm) | Mean AHI (events/h) | Mean ESS score | HTN | DM | Smoker | Previous stroke | CAD |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Parra et al. [35] | CPAP | 63.7 (±9.1) | 41 (72 %) | 30.2 (±4.6) | 41.9 (±3.8) | 38.4 (±12.6) | 8.3 (±3.3) | 33 (60 %) | 21 (38.2 %) | 25 (45.5 %) | 57 (100 %) | 7 (12.7 %) |
| Control | 65.6 (±9.1) | 48 (69 %) | 28.8 (±4.0) | 42.3 (±42) | 38.4 (±14.6) | 7.3 (±4.1) | 43 (63.2 %) | 25 (36.8 %) | 22 (32.4 %) | 69 (100 %) | 12 (17.6 %) | |
| Barbe et al. [36] | CPAP | 52.0 (±10.90) | 313 (87.7 %) | 31.3 (±4.86) | 42.4 (±3.64) | 43.4 (±22.3) | 6.5 (±2.27) | 190 (53.2 %) | 113 (31.7 %) | |||
| Control | 51.8 (±11.01) | 306 (83.6 %) | 31.1(±4.98) | 42.0 (±3.70) | 36.7 (±17.1) | 6.5 (±2.24) | 183 (50 %) | 94 (25.7 %) | ||||
| Craig et al. [37] | CPAP | 57.9 (±7.2) | 153 (78.5 %) | 32.2 (±5.6) | 42.5 (±3.9) | 7.9 (±4.4) | 151 (77.4 %) | 23 (11.8 %) | 119 (61 %) | 4 (2.1 %) | ||
| Control | 57.6 (±7.5) | 152 (77.6 %) | 32.5 (±5.6) | 43.0 (±4.0) | 8.0 (±4.2) | 149 (76 %) | 40 (20.4 %) | 125 (63.8 %) | 1 (0.5 %) | |||
| McMillan et al. [38] | CPAP | 70.9 (±4.7) | 120 (86 %) | 33.9 (±5.7) | 44.0 (±4.4) | 28.1 (16.3, 47.7) | 11.6 (±3.4) | 98 (70 %) | 40 (29 %) | 98 (70 %) | 16 (11 %) | 42 (30 %) |
| Control | 71.3 (±4.6) | 109 (79 %) | 33.6 (±6.4) | 42.6 (±4.0) | 29.4 (18.9, 46.0) | 11.6 (±3.9) | 104 (75 %) | 43 (31 %) | 94 (67 %) | 19 (14 %) | 49 (36 %) | |
| Gottlieb et al.a [39] | CPAP | 63.5 (±7.0) | 68 (76 %) | 33 (±5) | 25.4 (±8.7) | 8 (±3.8) | 76 (84 %) | 42 (47 %) | 56 (62 %) | 46 (51 %) | ||
| Control | 62.9 (±7.3) | 65 (69 %) | 34.7 (±5.7) | 24 (±8.1) | 9.6 (±3.6) | 82 (88 %) | 40 (43 %) | 55 (59 %) | 51 (54 %) | |||
| Huang et al. [40] | CPAP | 62.0 (±6.8) | 28 (77.8 %) | 27.9 (±3.6) | 41.2 (±4.0) | 28.3 (±13.0) | 9.3 (±3.1) | 12 (33.3 %) | 19 (52.8 %) | 11 (30.6 %) | ||
| Control | 62.7 (±6.7) | 32 (86.5 %) | 27.5 (±2.6) | 40.9 (±2.0) | 28.7 (±12.4) | 8.3 (±3.4) | 14 (37.8 %) | 23 (62.2 %) | 14 (37.8 %) | |||
| McEvoy et al. [15] | CPAP | 61.3 (±7.7) | 1092 (81.1 %) | 28.8 (±4.6) | 40.8 (±4.0) | 29.0 (±15.9) | 7.3 (±3.6) | 1057 (78.7 %) | 405 (30.2 %) | 213 (15.9 %) | 589 (43.9 %) | 682 (50.7 %) |
| Control | 61.2 (±7.91) | 1082 (80.7 %) | 28.5 (±4.4) | 40.6 (±4.2) | 29.6 (±16.4) | 7.5 (±3.6) | 1046 (78.2 %) | 393 (29.4 %) | 194 (14.5 %) | 594 (44.4 %) | 681 (50.8 %) | |
| Peker et al. [41] | CPAP | 65.5 (±8.5) | 100 (82 %) | 28.4 (±3.8) | 28.3 (±12.7) | 5.5 (±2.4) | 84 (68.9 %) | 34 (27.9 %) | 22 (18 %) | 122 (100 %) | ||
| Control | 66.5 (±8.2) | 106 (87 %) | 28.5 (±3.5) | 29.3 (±14.0) | 5.5 (±2.2) | 72 (59 %) | 25 (20.5 %) | 17 (13.9 %) | 122 (100 %) | |||
| de-la-Torre et al. [16] | CPAP | 59.9 (±10) | 528 (84 %) | 29.6 (±4.66) | 41.0 (±3.80) | 36.4 (±18.6) | 5.36 (±2.5) | 350 (56 %) | 172 (27 %) | 476 (75 %) | 17 (3 %) | 536 (85 %) |
| Control | 60.7 (±10) | 530 (85 %) | 29.4 (±4.29) | 41.1 (±3.60) | 35.5 (±18.3) | 5.28 (±2.5) | 357 (57 %) | 157 (25 %) | 472 (76 %) | 19 (3 %) | 532 (85 %) | |
| Traaen et al. [42] | CPAP | 63.0 (±7.4) | 39 (72 %) | 29.5 (±4.5) | 39.2 (±3.4) | 23.1 (18.3, 33.4) | 8.2 (±3.1) | 21 (39 %) | 4 (7 %) | 0 (0 %) | 4 (7 %) | 4 (7 %) |
| Control | 62.1 (±7.8) | 43 (80 %) | 29.4 (±4.0) | 49.9 (±3.4) | 20.7 (17.0, 32.0) | 7.5 (±3.3) | 23 (43 %) | 4 (7 %) | 5 (9.6 %) | 2 (4 %) | 5 (9 %) | |
| Gupta et al. [43] | CPAP | 53.41 (±9.85) | 24 (80 %) | 24.85 (±4.98) | 36.33 (±2.24) | 38.7 (±28) | 6.5 (0, 22) | 21 (70 %) | 8 (26.67 %) | 10 (33.33 %) | 30 (100 %) | 3 (10 %) |
| Control | 52.69 (±13.23) | 33 (82.5 %) | 25.57 (±3.26) | 37.2 (±3.22) | 25.03 (±14.7) | 6.0 (0, 14.5) | 33 (82.5 %) | 8 (20 %) | 19 (47.50 %) | 40 (100 %) | 5 (12.5 %) |
Data are presented as mean (±SD), median (25th, 75th percentiles) or number of patients (%).
CPAP = Continuous positive airway pressure; BMI = body mass index; AHI = apnea-hypopnea index; ESS = Epworth Sleepiness Scale; HTN = hypertension; DM = diabetes mellites; CAD = coronary artery disease.
Information is reported for only CPAP and NSO groups.
All studies included patients with known cardiovascular disease, except for the studies by Barbe et al. and Traaen et al. (within 3 months prior to the study), which excluded patients with prior cardiovascular events.
Pooled analyses showed no statistically significant differences between CPAP and control groups in baseline demographics or anthropometric measures. Mean age was similar between groups (MD = −0.11 years; 95 % CI: −0.51 to 0.29; P = 0.59; I2 = 0 %), as was the proportion of male participants (RR = 1.01; 95 % CI: 0.99 to 1.03; P = 0.48; I2 = 0 %), BMI (MD = 0.18 kg/m2; 95 % CI: −0.04 to 0.41; P = 0.11; I2 = 5 %), and neck circumference (MD = −0.15 cm; 95 % CI: −0.35 to 0.06; P = 0.16; I2 = 97 %). For detailed baseline characteristics of the included patients, refer to Table 2.
3.3. Primary outcomes
The primary outcome of MACE was reported across nine randomized controlled trials (N = 5719). Overall, there was no significant difference in MACE between patients treated with CPAP and those in the control group (RR = 1.00, 95 % CI: 0.87 to 1.14; P = 0.98) (Fig. 2A). Heterogeneity among the studies was low and not statistically significant (P = 0.21, I2 = 26 %).
Fig. 2.
(A) Forest plot for MACE in CPAP versus control groups. (B) Forest plot for MACE according to CPAP adherence. CI = confidence interval; M– H = Mantel-Haenszelmace.
A subgroup analysis based on CPAP adherence revealed a significant reduction in MACE among patients who were adherent to CPAP therapy (defined as ≥4 hours per night). In this group, CPAP was associated with a 29 % relative risk reduction in MACE compared to control (RR = 0.71, 95 % CI: 0.52 to 0.97; P = 0.03; I2 = 25 %) (Fig. 2B). In contrast, no significant benefit was observed in the non-adherent subgroup (RR = 1.08, 95 % CI: 0.93 to 1.26; P = 0.30; I2 = 0 %).
The test for subgroup differences was statistically significant (P = 0.02), indicating that CPAP adherence may influence the treatment effect.
Nine studies reported all-cause mortality, with no observed difference between the CPAP and control groups (RR = 0.93; 95 % CI: 0.71 to 1.23; P = 0.62; I2 = 0 %). Cardiovascular mortality was reported in eight studies and also showed no statistically significant difference (RR = 0.84; 95 % CI: 0.56 to 1.26; P = 0.40; I2 = 7 %). However, a subgroup analysis based on adequate CPAP adherence (≥4 hours per night) demonstrated a statistically significant reduction in cardiovascular mortality (RR = 0.36; 95 % CI: 0.14 to 0.91; P = 0.03) (Figs. 3A, B, 4).
Fig. 3.
(A) Forest plot for cardiovascular mortality in CPAP versus control groups. (B) Forest plot for cardiovascular mortality according to CPAP adherence. CI = confidence interval; M – H = Mantel-Haenszel.
Fig. 4.
Forest plot for cardiovascular mortality in CPAP versus control groups. CI = confidence interval; M – H = Mantel-Haenszel.
3.4. Secondary outcomes
Myocardial infarction was reported in nine studies and revealed no significant difference between groups (RR = 1.04; 95 % CI: 0.79 to 1.38; P = 0.76; I2 = 13 %). Similarly, acute stroke was reported across nine trials, with no difference between CPAP and control (RR = 0.91; 95 % CI: 0.69 to 1.22; P = 0.54; I2 = 0 %). Angina was evaluated in seven studies and showed no significant effect of CPAP (RR = 0.99; 95 % CI: 0.80 to 1.23; P = 0.93; I2 = 0 %). There was also no statistically significant difference in the incidence of new-onset atrial fibrillation (RR = 0.92; 95 % CI: 0.62 to 1.38; P = 0.69; I2 = 25 %) or in the occurrence or worsening of heart failure (RR = 0.91; 95 % CI: 0.61 to 1.37; P = 0.67; I2 = 0 %) (Fig. 5A–E).
Fig. 5.
Forest plot for (A) acute myocardial infarction, (B) atrial fibrillation, (C) acute stroke, (D) heart failure and (E) angina in CPAP versus control groups. CI = confidence interval; M – H = Mantel-Haenszel.
Across all secondary outcomes, heterogeneity was generally low (I2 = 0–25 %). Subgroup analyses based on CPAP adherence were conducted for all secondary outcomes, no statistically significant subgroup effects were observed for any of the outcomes.
3.5. Quality assessment
Most studies were judged to have low risk of bias in random sequence generation and allocation concealment. However, all included trials were open-label and did not use sham CPAP devices, making blinding of participants and personnel infeasible. As a result, all studies were judged to have some concerns. Despite this, blinding of outcome assessment was implemented in most trials.
The risk of attrition and reporting bias was low in most studies. Overall, the methodological quality of the included randomized controlled trials was considered moderate, with the primary limitation being the high risk of performance bias. A summary of the risk of bias assessment is shown in Fig. 6.
Fig. 6.
Risk of bias assessment. (A) Risk of bias graph: review authors’ judgements about each risk of bias item presented as percentages across all included studies. (B) Risk of bias summary: review authors’ judgements about each risk of bias item for each included study. Green: Low risk of bias; Yellow: some concerns and Red: High risk of bias.
3.6. Sensitivity analyses
Leave-one-out analyses were performed to evaluate the influence of individual studies on the pooled effect estimates. For cardiovascular mortality, the pooled effect in the main analysis (RR = 0.84; 95 % CI: 0.56 to 1.26; P = 0.40; I2 = 7 %) became statistically significant after exclusion of McEvoy et al. in combination with either Barbé et al. (RR = 0.54; 95 % CI: 0.30 to 0.98; P = 0.04; I2 = 0 %) or Sánchez-de-la-Torre et al. (RR = 0.36; 95 % CI: 0.14 to 0.91; P = 0.03; I2 = 0 %). For myocardial infarction, in the CPAP-adherent subgroup, the effect was not statistically significant in the primary analysis (RR = 0.81; 95 % CI: 0.42 to 1.56; P = 0.52; I2 = 42 %) but became statistically significant after exclusion of Parra et al. and Peker et al. (RR = 0.24; 95 % CI: 0.06 to 0.96; I2 = 0 %). For acute stroke, the pooled effect was not statistically significant (RR = 0.91; 95 % CI: 0.69 to 1.22; P = 0.54; I2 = 0 %) but became statistically significant after exclusion of Barbé et al., McEvoy et al., and Sánchez-de-la-Torre et al. (RR = 0.42; 95 % CI: 0.18 to 0.95; P = 0.04; I2 = 0 %).
4. Discussion
This systematic review and meta-analysis synthesized evidence from 11 RCTs, comprising 6139 participants with OSA, to evaluate the impact of CPAP therapy on cardiovascular outcomes. The pooled analysis demonstrated no statistically significant reduction in MACE, all-cause mortality, or most secondary cardiovascular outcomes when considering the overall study population. However, subgroup analyses revealed that adherence to CPAP therapy, defined as ≥4 hours per night, was associated with a 29 % relative risk reduction in MACE and a significant decrease in cardiovascular mortality. These findings emphasize that adherence is the critical determinant of CPAP’s cardiovascular efficacy, reframing CPAP not as universally ineffective, but as conditionally effective depending on patient adherence to treatment. To our knowledge, the present meta-analysis is the most updated and includes more RCTs than previous studies, making it more powerful and reliable.
4.1. Interpretation of findings
The absence of significant benefit in the general population mirrors the findings of landmark RCTs, particularly the SAVE trial [15] and the ISAACC trial [16], which reported no reduction in cardiovascular outcomes in patients with moderate-to-severe OSA and established cardiovascular disease. A major explanation is suboptimal adherence, with many patients in these studies averaging less than the therapeutic threshold of 4 hours per night. This degree of non-adherence is insufficient to reverse the pathophysiological mechanisms linking OSA with cardiovascular disease.
Conversely, our subgroup findings highlight that when patients are adherent, CPAP therapy confers cardiovascular protection, with a reduction in both MACE and cardiovascular mortality. This is biologically plausible given the well-established pathophysiological consequences of OSA: recurrent upper-airway collapse produces intermittent hypoxemia, surges in sympathetic activity, oxidative stress, systemic inflammation, and endothelial dysfunction [17,18]. These factors contribute directly to hypertension, atherosclerosis, arrhythmias, and heart failure. CPAP effectively abolishes obstructive apneas, stabilizes oxygenation, reduces sympathetic tone, and improves vascular function. However, these physiological benefits depend on consistent nightly application, explaining why partial or inconsistent use yields attenuated cardiovascular effects.
4.2. Comparison with previous evidence
Our findings are largely consistent with previous systematic reviews and meta-analyses evaluating the impact of CPAP therapy on cardiovascular outcomes in patients with OSA, particularly those restricted to RCTs.
In our analysis of nine RCTs involving 5719 participants, CPAP therapy was not associated with a significant reduction in MACE in the overall population. This finding aligns closely with the results reported by Li et al. [19] and Labarca et al. [20], both of whom demonstrated no statistically significant reduction in composite cardiovascular events with CPAP in pooled RCT analyses. Specifically, Li et al. reported a non-significant reduction in major adverse cardiac or cerebral events (MACCEs) (OR = 0.94), while Labarca et al. similarly observed no significant effect (RR = 0.87).
Importantly, our adherence-based subgroup analysis demonstrated a statistically significant reduction in MACE among patients using CPAP for ≥4 hours per night. While Labarca et al. reported a trend toward benefit with adequate adherence that did not reach statistical significance, Li et al. did not observe a significant adherence-related effect. These differences may reflect variations in trial inclusion, statistical power, and adherence definitions. In contrast, Javaid et al. [21] reported a significant reduction in MACE. However, this analysis included both randomized and observational studies, which may partly explain the stronger observed effect compared with RCT-only analyses such as ours.
Consistent with Li et al. and Labarca et al., our study found no significant reduction in all-cause mortality with CPAP therapy. Li et al. similarly reported no association between CPAP and all-cause death, and Labarca et al. demonstrated non-significant pooled estimates across RCTs. Javaid et al. did not report a statistically significant effect of CPAP on all-cause mortality when analyzed, further supporting the overall neutrality of CPAP on this outcome in randomized evidence.
Our pooled analysis showed no significant reduction in cardiovascular mortality in the overall population, in agreement with both Li et al. and Labarca et al., who also reported non-significant pooled estimates for cardiovascular death in RCT-based analyses. However, in our adherence-based subgroup, CPAP use ≥4 hours per night was associated with a significant reduction in cardiovascular mortality. This finding is consistent with Li et al., who similarly demonstrated a marked reduction in cardiovascular death among patients with adequate CPAP adherence. Labarca et al. observed a directionally favorable but non-significant effect in adherent patients, suggesting limited power rather than absence of effect. In contrast, Javaid et al. reported a significant overall reduction in cardiovascular mortality. However, inclusion of observational data may have amplified treatment effects relative to RCT-only estimates.
Our findings of no significant effect of CPAP on myocardial infarction and stroke are highly consistent across prior reviews. Li et al., Labarca et al., and Javaid et al. all reported neutral effects of CPAP on myocardial infarction and stroke in pooled analyses. While Li et al. identified a significant reduction in stroke among adherent CPAP users, this was not replicated in our adherence-based subgroup analysis, potentially reflecting differences in sample size. Notably, our analysis was based on a larger and more comprehensive dataset, including 11 RCTs with 6139 participants, compared with 6 trials and 4493 participants in Li et al., potentially providing more robust effect estimates.
We observed no significant associations between CPAP therapy and new-onset atrial fibrillation, heart failure, or angina, findings that are consistent with all three prior meta-analyses. Li et al. and Labarca et al. consistently reported neutral effects across these outcomes, while Javaid et al. similarly found no benefit for atrial fibrillation, heart failure hospitalization, or angina. These consistent null findings across multiple high-quality analyses suggest that CPAP does not substantially modify these specific cardiovascular outcomes in unselected OSA populations.
Our findings align with prior meta-analyses. Yu et al. [22] reported that CPAP had no effect on cardiovascular outcomes regardless of adherence to CPAP. However, that analysis was not exclusive to OSA and included patients with central sleep apnea as well. The distinction is critical because patients with central sleep apnea often have severe left ventricular dysfunction or prior stroke, placing them at intrinsically higher cardiovascular risk independent of CPAP therapy. Including both conditions in earlier analyses may have diluted the true cardiovascular benefits of CPAP in OSA populations [23,24]. In contrast, other meta-analyses more consistent with our results have suggested a benefit of CPAP in adherent patients. Abuzaid et al. [10], in a meta-analysis of four RCTs, found that CPAP did not significantly improve cardiac outcomes compared with medical therapy alone, except among patients adherent to therapy (>4 hours/night). Similarly, Khan et al. [9] demonstrated that cardiovascular benefit was confined to adherent patients. More recent registry-based studies, such as Elbadawi et al. [25], further corroborate that CPAP may reduce cardiovascular risk in adherent populations, though trial-level evidence remains mixed.
A systematic review and meta-analysis by Wang et al. [26] investigated patients with both coronary artery disease (CAD) and OSA. In observational cohorts, CPAP treatment was associated with a 39 % lower risk of MACE and significantly reduced all-cause and cardiovascular mortality. However, RCTs within the same population failed to replicate these benefits, again underscoring the discrepancy between observational and randomized data. This discrepancy reflects both the challenge of enforcing adherence in RCTs and the “healthy adherer effect” observed in real-world studies. Moreover, Wang et al. suggested that the widespread use of contemporary cardioprotective therapies such as statins, antiplatelets, and revascularization may attenuate the incremental benefit of CPAP in modern CAD cohorts.
The ISAACC trial provided further nuance by focusing on non-sleepy acute coronary syndrome (ACS) patients with OSA. After a median follow-up of 3.35 years, there was no significant difference in cardiovascular events between patients treated with CPAP and those receiving usual care (HR = 0.89, p = 0.40). Crucially, average adherence was only 2.78 hours per night, far below the therapeutic threshold [16]. These results highlight how insufficient adherence undermines CPAP’s potential cardiovascular benefits.
By contrast, observational studies have consistently reported stronger associations between CPAP use and reduced cardiovascular morbidity and mortality [27–29]. These findings may reflect confounding and selection biases, including the healthy adherer effect. Nonetheless, the consistency of subgroup analyses across multiple RCTs lends credibility to the hypothesis that CPAP exerts genuine cardiovascular protection when adherence is adequate.
It is important to emphasize that negative RCT results, such as SAVE [15], should not be interpreted as definitive evidence of futility. Sensitivity analyses in our review demonstrated that when large trials with poor adherence were excluded, CPAP showed more favourable outcomes for myocardial infarction, stroke, and cardiovascular mortality. Taken together, the evidence supports a conditional but real cardiovascular benefit of CPAP, dependent on treatment adherence.
4.3. Clinical implications
CPAP should not be prescribed indiscriminately for cardiovascular risk reduction in all patients with OSA. Instead, treatment should be targeted toward patients most likely to adhere and to derive both symptomatic and cardiovascular benefit, including those with excessive daytime sleepiness, resistant hypertension, atrial fibrillation, or established cardiovascular disease.
Our findings also emphasize that adherence is not merely a behavioral factor but a central therapeutic determinant. Interventions to improve adherence—such as early patient education, personalized mask fitting, proactive troubleshooting of side effects, behavioral therapy, and telemonitoring with real-time feedback—should be integrated into routine practice. Notably, randomized studies have demonstrated that telemonitoring interventions can increase average nightly CPAP use by up to 60 minutes, which may translate into measurable cardiovascular benefits [30–32].
Even in the absence of robust cardiovascular protection at the population level, CPAP consistently improves daytime somnolence, quality of life, neurocognitive function, and blood pressure control [33]. These benefits continue to justify its role as first-line therapy for moderate-to-severe OSA, with cardiovascular advantages potentially realized in adherent subgroups.
Finally, the health economics of CPAP use warrant consideration. The therapy entails substantial costs related to devices, supplies, follow-up, and adherence support programs. Payers may therefore hesitate to fund CPAP solely for cardiovascular prevention. However, cost-effectiveness analyses suggest that CPAP is economically favourable in moderate-to-severe OSA, particularly when adherence is optimized and long-term health benefits are considered [34]. Accordingly, investment in structured adherence programs is likely to yield not only health benefits but also long-term cost savings.
4.4. Strengths and limitations
This systematic review has several strengths. By restricting inclusion to RCTs, we minimized confounding and enhanced internal validity. The pooled sample size exceeded 6000 patients, providing robust statistical power. Importantly, our adherence-based subgroup analyses deliver clinically actionable insights often neglected in prior reviews. Heterogeneity was mostly low across most outcomes, which further reinforce the robustness of the findings.
However, limitations must be acknowledged. First, all included trials were open-label, as sham CPAP remains technically and ethically challenging, leading to performance bias. Second, adherence reporting was inconsistent, and some trials failed to provide objective device usage data. Third, trial populations were predominantly older males with established cardiovascular disease, limiting generalizability to women, younger patients, or those with milder OSA. Fourth, follow-up durations were heterogeneous, with some trials potentially too short to capture long-term cardiovascular effects. Finally, the absence of patient-level data restricted our ability to perform stratified analyses by age, sex, OSA severity, or comorbid conditions. Additionally, although multiple major databases were searched, future systematic reviews may further strengthen comprehensiveness by expanding database coverage and updating searches prospectively as new randomized trials become available.
5. Conclusion
CPAP therapy did not significantly reduce overall MACE, mortality, or most cardiovascular outcomes in OSA patients, except among those with good adherence (≥4 hours/night), who showed reduced MACE and cardiovascular mortality. These findings highlight adherence as a key factor in determining potential cardiovascular benefits. Further investigations are needed to investigate the effect of CPAP in lowering cardiovascular events in patients with OSA depending on adherence.
Abbreviation list
- ACS
Acute Coronary Syndrome
- AHI
Apnea–Hypopnea Index
- BMI
Body Mass Index
- CAD
Coronary Artery Disease
- CI
Confidence Interval
- CPAP
Continuous Positive Airway Pressure
- DM
Diabetes Mellitus
- ESS
Epworth Sleepiness Scale
- HR
Hazard Ratio
- MACE
Major Adverse Cardiovascular Events
- MeSH
Medical Subject Headings
- OSA
Obstructive Sleep Apnea
- PRISMA
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
- RCT
Randomized Controlled Trial
- ROB
Risk of Bias
- RR
Risk Ratio
Footnotes
Ethical approval: As this systematic review does not involve primary data collection from human participants, ethical approval was not required. The review adheres to the guidelines and principles of evidence synthesis and analysis.
Author contributions: Conception and design of Study: S. Alm. Literature review: S. Alm., ML. Acquisition of data: S. Alm., M. Alt., M. Alm., S. Als. Analysis and interpretation of data: S. Alm., ML. Research investigation and analysis: S. Alm., ML. Data collection: S. Alm., RA, ML, AA, M. Alm. Drafting of manuscript: S. Alm., ML, AA, M. Alt., S. Als. Revising and editing the manuscript critically for important intellectual contents: S. Alm., RA, ML, MD. Data preparation and presentation: S. Alm., RA, AA, M. Alt., M. Alm. Supervision of the research: MD, S. Alm. Research coordination and management: S. Alm.
Funding: This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.
Conflict of interest: The authors of this study declare no conflict of interest.
Artificial Intelligence (AI) or Large Language Model (LLM) Use Declaration: No Artificial intelligence (AI) or large language model (LLM) tools were not used.
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