Abstract
Objective
To systematically analyze the studies that have examined the effect of continuous positive airway pressure (CPAP) on blood pressure (BP) in patients with resistant hypertension and obstructive sleep apnea (OSA).
Methods
Design – meta-analysis of observational studies and randomized controlled trials (RCTs) indexed in PubMed and Ovid (All Journals@Ovid). participants: individuals with resistant hypertension and OSA; interventions – CPAP treatment.
Results
A total of six studies met the inclusion criteria for preintervention to postintervention analyses. The pooled estimates of mean changes after CPAP treatment for the ambulatory (24-h) SBP and DBP from six studies were −7.21 mmHg [95% confidence interval (CI): −9.04 to −5.38; P <0.001; I2 58%) and −4.99 mmHg (95% CI: −6.01 to −3.96; P <0.001; I2 31%), respectively. The pooled estimate of the ambulatory SBP and DBP from the four RCTs showed a mean net change of −6.74 mmHg [95% CI: −9.98 to −3.49; P <0.001; I2 61%] and −5.94 mmHg (95% CI: −9.40 to −2.47; P =0.001; I2 76%), respectively, in favor of the CPAP group.
Conclusion
The pooled estimate shows a favorable reduction of BP with CPAP treatment in patients with resistant hypertension and OSA. The effects sizes are larger than those previously reported in patients with OSA without resistant hypertension.
Keywords: blood pressure, continuous positive airway pressure, meta-analysis, obstructive sleep apnea, resistant hypertension
INTRODUCTION
Obstructive sleep apnea (OSA) is a common disorder that is associated with increased risk of hypertension [1–3]. Treatment of OSA with continuous positive airway pressure (CPAP) is associated with a lower risk of incident hypertension [4]. Randomized controlled trials (RCTs) show that the reduction in blood pressure (BP) with CPAP therapy is significant, but modest with an average decrease in SBP of 2.6 mmHg and an average decrease in DBP of 2.0 mmHg [5].
Resistant hypertension, defined as BP that remains above the normal despite the concurrent use of three different antihypertensive medications including a diuretic or controlled BP that requires four or more medications [6], occurs in 9–13% of the general hypertensive population [7]. As hypertension affects about 77.9 million (one out of every three adults) in the United States, those with resistant hypertension represent a significant proportion of the population [8]. Resistant hypertension is a major public health burden because these individuals are at an increased risk for target organ damage and adverse cardiovascular outcomes including stroke, myocardial infarction, and congestive heart failure compared with those with more easily controlled hypertension [9,10].
The most common cause of resistant hypertension is OSA [11]. Among patients with resistant hypertension, the prevalence of OSA is reported to be 70–83% [12]. Several meta-analyses have shown consistently that CPAP treatment reduces BP in patients with OSA [5,13,14]. It has been suggested that CPAP treatment of OSA may have a more robust response in those with difficult-to-control hypertension [14]. However, the effects of CPAP on BP in patients with resistant hypertension have not been systematically examined. We therefore planned a systematic review and meta-analysis to assess whether CPAP reduces BP in patients with OSA and resistant hypertension.
METHODS
The investigators of this study are members of the Hypertension Working Group of the Sleep Apnea Genetics International Consortium (SAGIC).
Data sources
We searched in the databases of PubMed and Ovid (All Journals@Ovid) from inception to 30 July 2013 for observational studies and RCTs that specifically included participants with resistant hypertension and OSA. We also searched through the meeting abstracts of Associated Professional Societies of Sleep, American Thoracic Society and American College of Chest Physicians. Only one abstract was found relevant to our inclusion criteria. However, as the authors, the data, and the study population were the same as one of the published papers identified in our search from PubMed, we decided to include the published paper only [15].
Search strategy and selection criteria
We used the search terms, ‘sleep apnea’, ‘hypertension’, ‘blood pressure’ and ‘continuous positive airway pressure’ in both Ovid and PubMed. Figure 1 depicts a summary of our study selection process. Search terms used in PubMed are provided in the Supplementary data, http://links.lww.com/HJH/A406. We adhered to the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) and Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) guidelines for all stages of the design, implementation, and reporting of this meta-analysis [16,17]. Altogether, 157 articles were found. We shortlisted the 57 studies from this initial search, as most were unrelated to our meta-analysis (such as case reports, letters, review articles or multiseries case reports). Full manuscripts of these 57 studies were obtained. These were divided among the investigators for review using the inclusion criteria below. All excluded studies were then reviewed for a second time by one of the investigators (I.H.I.). A total of 50 studies included participants who did not have resistant hypertension and these were excluded. One study that did include participants with resistant hypertension was excluded because of its retrospective design [18]. A total of six studies were finally included in our meta-analysis and the full manuscripts of these studies were reviewed by all investigators. There were no disagreements between the authors on the inclusion or exclusion of a study. We used the following inclusion criteria:
FIGURE 1.
Flow diagram of articles identified and evaluated during the study selection process.
A study involving only adult human participants (age 18 years and older).
A study investigating the preintervention and post-intervention effect of CPAP on SBP and DBP.
A study comprising of participants with resistant hypertension and OSA.
We considered only prospective cohort studies either observational or RCTs. We did not include any case reports, retrospective studies or case-series reports.
We considered resistant hypertension in study participants if the participants were described to have BP above the goal in spite of the concurrent use of three antihypertensive agents of different classes (including a diuretic) at adequate doses [6].
Data abstraction
For this study, we extracted from each paper, the first author’s name, year of publication, number of participants, preintervention and postintervention SBP and DBP measurements with SDs, country of origin, study design, demographics [including mean age, BMI, sex distribution, presence of comorbidities and the apnea–hypopnea index (AHI)], and the method of BP measurement (ambulatory BP monitoring, or office BP). For the four RCTs, pre-CPAP and post-CPAP intervention data were extracted in a similar fashion [15,19–21]. Our primary outcome, defined a priori, was the 24-h SBP and DBP as recorded by the ambulatory blood pressure monitoring (ABPM). This measurement was given preference, because several studies have shown that ABPM is superior in predicting the target organ damage and cardiovascular events compared with office BP [22]. We abstracted the 24-h ABPM data for all included studies. Our secondary outcomes were the daytime and nocturnal SBP and DBP, for which separate analyses were performed. For the studies in which the SEM was reported, we calculated the SD based on the number of participants in the study and the reported SEM. All data were entered in mmHg. A study selected for inclusion in our meta-analysis did not report separate data for the 25 out of 44 study participants who met the criteria for resistant hypertension in the published manuscript. However, the data on these 25 patients were requested by us from the corresponding authors of the study and included in our analyses [19].
Quantitative data synthesis
The effect of CPAP was quantified by estimating the mean difference of outcomes (24-h ABPM and nocturnal mean SBP and DBP) before and after CPAP intervention. Data from the four RCTs on the effect of CPAP on SBP and DBP were also separately analyzed. This was analyzed by estimating and comparing the pooled means and SDs of the BP variables between control and intervention groups. The method by Follmann et al. [23] that assumes a correlation of 0.5 between preintervention and postintervention BP levels was adopted. Effect sizes and 95% confidence intervals (CIs) were estimated by pooling the available data using the Comprehensive Meta-Analysis (CMA) V2 software.
The CMA software was used which generates both random effects methods to account for variance between the studies as well as within the studies [24] and fixed effects methods to account for variance within the studies. We decided, a priori, to report all analyses in random effects model, as the study population to be analyzed in our meta-analysis was heterogenous. The heterogeneity was separately assessed by I2 statistics.
Heterogeneity was assessed with I2 statistics [25]. For analyses with statistically significant results, but with moderate-to-high heterogeneity, prestated subgroup analyses were conducted to assess the effect of baseline Epworth Sleepiness Score (ESS), duration of CPAP intervention, method of BP measurement, trial design, geographical locations where studies were conducted and SBP/DBP of the participants at entry. To assess the risk of publication bias, a funnel plot of standard error and difference in means [26] was constructed for the pre-CPAP to post-CPAP analysis of 24-h SBP. We selected this analysis for conducting the assessment of publication bias, as this analysis incorporated all six studies that we included in our meta-analysis.
We also conducted meta-regression for the association of prestated variables of interest; ESS, AHI, BMI, and age at baseline. We used the mixed effects method (unrestricted maximum likelihood).
For the available data from studies (where such data was reported), we sought to conduct a meta-analysis of correlation and sample size for hours of CPAP use and change in BP. Sensitivity analyses were conducted for all analyses to evaluate the effects of each selected study on the overall results of the meta-analysis.
Publication bias was assessed with the construction of a funnel plot, and further assessed by Eggers test of the intercept and the Begg and Mazumdar rank correlation test [27]. A P value of less than 0.05 on these tests was considered statistically significant for the evidence of publication bias.
RESULTS
A total of seven studies [15,19–21,28–30] were initially shortlisted for the meta-analysis. However, one study [30] was excluded as BP was not measured by the ABPM methods. Figure 1 outlines our search strategy and selection process for including the six studies in our meta-analysis. The total number of study participants was 329, but the number included with each analysis varied because of different study designs. A total of 196, 193, and 171 study participants were analyzed for pre-CPAP to post-CPAP intervention analyses of ambulatory, daytime, and nocturnal BP, respectively. A total of 224 study participants for the RCT analyses of ambulatory and daytime BP and 174 for the RCT analyses of nocturnal BP were included. Characteristics of the study population in each trial are outlined in Table 1. Participants in all of the studies had a mean age of 55 and older, and had a mean BMI of 30 kg/m2 or greater. The included studies enrolled participants who had OSA and resistant hypertension. Although the majority of the study participants were obese, those with other comorbidities were excluded. The duration of CPAP intervention ranged from 3 weeks to 6 months. There were two observational studies [28,29] and four RCTs [15,19–21]. We used the ABPM data for 24-h SBP and DBP analyses from the six studies in which these data were available [15,19–21,28,29]. A total of six studies [15,20,21,28–30] reported the nocturnal BP measurements, of which three were RCTS [15,20,21]. Three of the studies were from Spain [20,21,29], one from Russia [19], one from Brazil [15] and one from Canada [28]. Table 2 outlines the baseline AHI, ESS and CPAP compliance of study participants in different studies.
TABLE 1.
Characteristics of the studies
| Author | Year | Type of study | Number of participants | Age (SD) | Sex (male) | BMI (SD) | Duration of intervention (used in this meta-analysis) | Method of BP measurement |
|---|---|---|---|---|---|---|---|---|
| Logan et al. [28] | 2003 | Observational | 11 | 57 (2) | 90% | 34.4 (2.4) | 2 months | ABPM |
| Martinez-Garcia et al. [29] | 2007 | Observational | 23a | 68.1 (7.8) | 52.2% | 35.1 | 3 months | ABPM |
| Lozano et al. [20] | 2010 | RCT | 20 (CPAP) | 59.2 (8.7) | 75.9% | 30 (4.3) | 3 months | ABPM |
| 21 (Control) | ||||||||
| Pedrosa et al. [15] | 2013 | RCT | 19 (CPAP) | 57 (2)b | 74%b | 36 (31–41)c | 6 months | ABPM |
| 16 (Control) | ||||||||
| Litvin et al. [19] | 2013 | RCT (cross-over design) | 25 (CPAP) | 55.5 (9.6) | 77.27% | 37.7 (7.8) | 3 weeks | Office |
| 25 (Control) | ||||||||
| Martinez-Garcia et al. [21] | 2013 | RCT | 98 (CPAP) | 56.0 (9.5) | 68.6% | 34.1 (5.4) | 3 months | ABPM |
| 96 (Control) |
ABPM, ambulatory blood pressure monitoring; CPAP, continuous positive airway pressure; RCT, randomized controlled trial.
Out of 39 participants, 33 completed study and out of these 23 showed good CPAP tolerance.
Data expressed as mean and standard error of mean.
Data expressed as median and interquartile range.
TABLE 2.
Baseline AHI, ESS and CPAP compliance
| Author | AHI | ESS | CPAP compliance |
|---|---|---|---|
| Logan et al. [28] | 45.3 ± 10.1 | – | – |
| Martinez-Garcia et al. [29] | 40 ± 9.7a | 7.4 ± 5.1a | ≥4 ha |
| Lozano et al. [20] | 52.67 ± 21.5 | 6.2 ± 3.34 | 5.6 ± 1.5 h |
| Pedrosa et al. [15] | 36 (24–51)b | 12 ± 1 | 6:01 ± 0:20 h |
| Litvin et al. [19] | 63.4 ± 26.3 | – | 5.1 ± 1.6 h |
| Martinez-Garcia et al. [21] | 41.3 (18.7) | 8.9 (4.0) | 5 ± 1.9 h |
AHI, apnea–hypopnea index; CPAP, continuous positive airway pressure; ESS, Epworth Sleepiness Score.
Data represents the 23 study participants included from this study.
Data shown in median and interquartile range.
Effect on ambulatory blood pressure after continuous positive airway pressure intervention
The pooled estimate of the mean changes and the corresponding 95% CIs for ambulatory (24-h or office) SBP and DBP from six studies [15,19–21,28,29] were −7.21 (95% CIs: −9.04 to −5.38; P <0.001; I2 58%) and −4.99 (95% CIs: −6.01 to −3.96; P <0.001; I2 31%), respectively (Figs 2 and 3).
FIGURE 2.
Forest plot for the mean change in 24-h SBP with the corresponding 95% confidence interval (CI).
FIGURE 3.
Forest plot for the mean change in 24-h DBP with the corresponding 95% confidence interval (CI).
Effect on nocturnal blood pressure after continuous positive airway pressure intervention
The pooled estimate of mean changes and the corresponding 95% CIs for nocturnal SBP and DBP from five studies [15,20,21,28,29] were −6.79 mmHg [95% confidence interval (CI): −13.86 to 0.26; P =0.05; I2 96%] and −3.67 mmHg (95% CI: −8.05 to 0.71; P =0.10; I2 94%), respectively (Table 3).
TABLE 3.
Nocturnal blood pressure data
| No. of studies | Mean change (mmHg) | 95% CI, P value | |
|---|---|---|---|
| Mean difference in SBP after CPAP | 5 | −6.79 | −13.86 to 0.26, P =0.05 |
| Mean difference in DBP after CPAP | 5 | −3.67 | −8.05 to 0.71, P =0.10 |
| Mean net change in SBP between CPAP and control | 3 | −2.08 | −4.33 to 0.16, P =0.06 |
| Mean net change in DBP between CPAP and control | 3 | −1.47 | −3.22 to 0.28, P =0.10 |
CIs, confidence intervals; CPAP, continuous positive airway pressure.
Comparison of mean change in the ambulatory blood pressure between continuous positive airway pressure and control groups
The pooled estimate of the data from the four RCTs [15,19–21] showed a mean net change of −6.74 mmHg (95% CI: −9.98 to −3.49; P <0.001; I2 61%) and −5.94 mmHg (95% CI: −9.40 to −2.47; P =0.001; I2 76%) in the ambulatory SBP and DBP, respectively, in favor of the CPAP groups (Figs 4 and 5).
FIGURE 4.
Forest plot for the mean change in 24-h SBP from the randomized controlled trials with the corresponding 95% confidence interval (CI).
FIGURE 5.
Forest plot for the mean change in 24-h DBP from randomized controlled trials with the corresponding 95% confidence interval (CI).
Comparison of mean change in nocturnal blood pressure between continuous positive airway pressure and control groups
The pooled estimate of the data from three RCTs [15,20,21] showed a mean net change of −2.08 mmHg (95% CI: −4.33 to 0.16; P =0.06; I2 0.0%) and −1.47 mmHg (95% CI: −3.22 to 0.28; P =0.10; I2 0.0%) in nocturnal SBP and DBP, respectively (Table 3). The results on SBP show a trend favoring the CPAP groups.
Separate analyses of daytime BP (pre-CPAP to post-CPAP intervention, based on six studies) showed statistically significant reductions in both SBP [Δ −10.16 mmHg (95% CI: −10.16 to −4.81); P <0.001] and DBP [Δ −5.16 mmHg (95% CI: −7.61 to −2.71); P <0.001]. Comparison of the mean change in daytime BP (between CPAP and control groups, based on four RCTs) also showed statistically significant reductions in both SBP [Δ −5.32 mmHg (95% CI: −9.96 to −0.68); P =0.02] and DBP [Δ −4.80 mmHg (95% CI: −7.51 to −2.10); P <0.001]. Supplementary figures S5–S8, http://links.lww.com/HJH/A406 depict the results in forest plots for daytime BP analyses.
Exploring heterogeneity
To explore for the potential sources of heterogeneity, subgroup analyses was done based on the predefined variables. Heterogeneity in the analyses of pre-CPAP to post-CPAP 24-h SBP and DBP mean difference was found not to be associated with ESS less than 10, CPAP duration (<2 or >2 months), sample size greater than 20, pre-CPAP BP greater than 145/85 mmHg or studies including European participants (Table 4). Subgroup analyses based on the design (RCT versus non-RCT) of studies did not lead to heterogeneity in most of the subgroup analyses (Table 5). However, when the 24-h SBP and DBP data from RCTs were further analyzed based on their design, significant heterogeneity was noticed in the noncross-over trials (Table 5). The SBP and DBP subgroup analyses based on ESS, CPAP duration (<2 months), study sample size, geographical location and pre-CPAP BP did not reveal the heterogeneity (Table 5).
TABLE 4.
Subgroup analyses of 24-h blood pressure data (preintervention to postintervention)
| Subgroup
|
SBP
|
DBP
|
|||||
|---|---|---|---|---|---|---|---|
| No. of studies | Mean net change | 95% CI, P value | No. of studies | Mean net change | 95% CI, P value | ||
| ESS | <10 | 3 | −5.29 | −7.36 to −3.22, P ≤ 0.001; I2 0% | 3 | −4.10 | −5.95 to −2.25, P <0.001; I2 0% |
|
| |||||||
| >10 | 1 | −6.50 | −7.98 to −5.01, P <0.001; I2 0% | 1 | −4.50 | −5.35 to −3.64, P <0.001; I2 0% | |
|
| |||||||
| CPAP duration | <2 months | 2 | −9.47 | −11.88 to −7.06, P ≤ 0.001; I2 30% | 2 | −6.08 | −7.57 to −4.59, P ≤ 0.001; I2 8% |
|
| |||||||
| >2 months | 4 | −6.04 | −7.28 to −4.79, P <0.001; I2 0% | 4 | −4.36 | −5.14 to −3.57, P <0.001; I2 0% | |
|
| |||||||
| Study sample size | <20 | 2 | −8.37 | −12.28 to −4.45, P <0.001; I2 86% | 2 | −4.94 | −6.07 to −3.80, P <0.001; I2 76% |
|
| |||||||
| >20 | 4 | −6.07 | −7.81 to −4.33, P ≤ 0.001; I2 0% | 4 | −5.14 | −7.47 to −2.82, P ≤ 0.001; I2 43% | |
|
| |||||||
| Study design | Non-RCT | 2 | −9.62 | −12.86 to −6.39, P <0.001; I2 23%. | 2 | −4.75 | −7.67 to −1.83, P =0.001; I2 46% |
|
| |||||||
| RCT | 4 | −6.31 | −7.46 to −5.16, P ≤ 0.001; I2 0% | 4 | −4.98 | −6.36 to −3.59, P ≤ 0.001; I2 35% | |
|
| |||||||
| Geographical location | Asia | 1 | −8.00 | −11.24 to −4.75, P <0.001; I2 0% | 1 | −7.60 | −10.84 to −4.36, P <0.001; I2 0% |
|
| |||||||
| Europe | 3 | −5.29 | −7.36 to −3.22, P ≤ 0.001; I2 0% | 3 | −4.10 | −5.95 to −2.25, P ≤ 0.001; I2 0% | |
|
| |||||||
| America | 2 | −8.37 | −12.83 to −4.45, P ≤ 0.001; I2 86% | 2 | −4.94 | −6.07 to −3.80, P ≤ 0.001; I2 47% | |
|
| |||||||
| Baseline SBP/DBP | <145/<85 | 2 | −9.62 | −12.86 to −6.39, P <0.001; I2 23% | 2 | −4.60 | −9.09 to −0.12, P =0.04; I2 46% |
|
| |||||||
| >145/>85 | 4 | −6.31 | −7.46 to −5.16, P <0.001; I2 0% | 4 | −5.04 | −6.16 to −3.93, P <0.001; I2 44% | |
ABPM, ambulatory blood pressure monitoring; CI, confidence interval; CPAP, continuous positive airway pressure; ESS, Epworth Sleepiness Score; I2, heterogeneity analysis; RCT, randomized controlled trial. America groups one study from Canada and one from Brazil.
TABLE 5.
Subgroup analyses of 24-h ABPM blood pressure data from the RCTs
| Subgroup
|
SBP
|
DBP
|
|||||
|---|---|---|---|---|---|---|---|
| No. of studies | Mean net change | 95% CI, P value | No. of studies | Mean net change | 95% CI, P value | ||
| ESS | <10 | 2 | −4.10 | −7.59 to −0.62, P =0.02; I2 0% | 2 | −3.50 | −6.36 to −0.64, P =0.01; I2 0% |
|
| |||||||
| >10 | 2 | −9.60 | −11.79 to −7.40, P ≤ 0.001; I2 0% | 2 | −8.26 | −10.84 to −5.68, P ≤ 0.001; I2 38% | |
|
| |||||||
| CPAP duration | <2 months | 1 | −6.30 | −10.67 to −1.92, P ≤ 0.01; I2 0% | 1 | −5.90 | −10.49 to −1.31, P =0.01; I2 0% |
|
| |||||||
| >2 months | 3 | −6.72 | −11.22 to −2.23, P ≤ 0.01; I2 72% | 3 | −5.83 | −10.31 to −1.36, P =0.01; I2 83% | |
|
| |||||||
| ABPM | 3 | −6.72 | −11.22 to −2.23, P ≤ 0.01; I2 72% | 3 | −5.83 | −10.31 to −1.36, P =0.01; I2 83% | |
|
| |||||||
| Study sample size | <20 | 1 | −9.60 | −11.79 to −7.40, P ≤ 0.001; I2 0% | 1 | −9.00 | −10.26 to −7.73, P ≤ 0.001; I2 0% |
|
| |||||||
| >20 | 3 | −4.95 | −7.68 to −2.23, P ≤ 0.001; I2 0% | 3 | −4.17 | −6.60 to −1.74, P ≤ 0.01; I2 0% | |
|
| |||||||
| Study design | Cross-over | 1 | −6.30 | −10.67 to −1.92, P ≤ 0.01; I2 0% | 1 | −5.90 | −10.49 to −1.31, P =0.01; I2 0% |
|
| |||||||
| Noncross-over | 3 | −6.72 | −11.22 to −2.23, P ≤ 0.01; I2 72% | 3 | −5.83 | −10.31 to −1.36, P =0.01; I2 83% | |
|
| |||||||
| Geographical location | Asia | 1 | −6.30 | −10.67 to −1.92, P ≤ 0.01; I2 0% | 1 | −5.90 | −10.49 to −1.31, P =0.01; I2 0% |
|
| |||||||
| Europe | 2 | −4.10 | −7.59 to −0.62, p 0.02; I2 0% | 2 | −3.50 | −6.36 to −0.64, P =0.01; I2 0% | |
|
| |||||||
| America | 1 | −9.60 | −11.79 to −7.40, P ≤ 0.001; I2 0% | 1 | −9.00 | −10.26 to −7.73, P ≤ 0.001; I2 0% | |
|
| |||||||
| Baseline SBP/DBP | <145/<85 | 2 | −4.10 | −7.59 to −0.62, P =0.02; I2 0% | 2 | −3.50 | −6.36 to −0.64, P =0.01; I2 0% |
|
| |||||||
| >145/>85 | 2 | −8.51 | −11.55 to −5.47, P ≤ 0.001; I2 42% | 2 | −8.26 | −10.84 to −5.68, P ≤ 0.001; I2 38% | |
ABPM, ambulatory blood pressure; CI, confidence interval; CPAP, continuous positive airway pressure; ESS, Epworth Sleepiness Score; I2, heterogeneity analysis; RCT, randomized controlled trial. America groups one study from Canada and one from Brazil.
Meta-regression
Predefined meta-regression analyses was performed for pooled mean net change in SBP and DBP (both 24 h and nocturnal) based on pre to post CPAP analyses (Table 6). Meta-regression showed no relationship with either baseline age, BMI or ESS. However, significant relationship was observed between baseline AHI and pooled mean net change in 24-h DBP.
TABLE 6.
Meta-regression of pre-CPAP to post-CPAP blood pressure data using mixed effects regression (unrestricted maximum likelihood)
| Explanatory variable (baseline) | SBP
|
DBP
|
||
|---|---|---|---|---|
| No. of studies | P value | No. of trials | P value | |
| AHI | 6 | 0.47 | 6 | 0.02a |
|
| ||||
| ESS | 4 | 0.57 | 4 | 0.80 |
|
| ||||
| Age | 6 | 0.65 | 6 | 0.20 |
|
| ||||
| BMI | 6 | 0.78 | 6 | 0.85 |
AHI, apnea–hypopnea index; CPAP, continuous positive airway pressure; ESS, Epworth Sleepiness Score.
Indicates statistical significance.
Correlational analysis
Meta-analysis of correlation and sample size showed statistically significant correlation between hours of CPAP use and DBP response, with a pooled correlation of 0.26, with a P value of 0.003. This was based on the two studies with a total of 121 study participants in the CPAP arms [21,24].
Publication bias
The funnel plot showed visual evidence of the publication bias (Fig. 6).
FIGURE 6.
Funnel plot for the assessment of publication bias.
Sensitivity analysis
In the sensitivity analyses, the exclusion of any study from the analyses did not change the pooled estimates of CPAP intervention on 24-h SBP, 24-h DBP, and the pooled estimates of mean net change between CPAP and control for 24-h SBP, 24-h DBP and nocturnal DBP. One study [15] appeared to be an outlier for the mean net change in nocturnal SBP between CPAP and control.
DISCUSSION
To the best of our knowledge, this is the first meta-analysis that examined specifically the effects of CPAP treatment for OSA on BP in patients with resistant hypertension. The preintervention to postintervention analyses showed a significant mean reduction by −7.2 and −4.99 mmHg in the ambulatory SBP and DBP, respectively, whereas separate analyses from the RCTs showed a reduction in SBP and DBP by −6.74 and −5.94 mmHg, respectively. These effect sizes are greater than the reduction in BP reported with CPAP treatment in hypertensive OSA patients without resistant hypertension [5]. However, the nocturnal preintervention to postintervention analysis and the BP analysis from RCTs (in which such data were available) failed to reach statistical significance, although there were only three RCTs that reported this data.
Several prior meta-analyses have studied the effects of CPAP on BP in patients with OSA [5,13,14]. Most of these studies showed modest reductions in SBP and DBP in the 2–3 mmHg range. Studies included in these meta-analyses enrolled participants with OSA, who were either normotensive or hypertensive. In the most recent meta-analysis by Montesi et al. [31], however, a subgroup analysis showed that the effect of CPAP on BP is also in the same modest range (2–3 mmHg) even in hypertensive OSA patients. Therefore, the effect of CPAP on BP in patients with resistant hypertension appears to be greater. This is clinically important because patients with resistant hypertension are at an increased risk for target-organ damage and cardiovascular complications compared with those hypertensive patients with easy to control BP [6,9]. In our meta-analysis, we included only those trials that studied participants with resistant hypertension and our pooled estimates, more specifically the preintervention to postintervention analyses, showed a reduction in not just the ambulatory BP, but also the nocturnal BP measurements. Therefore, our findings provide additional rationale for a more aggressive screening for OSA in those with resistant hypertension as well as ensuring treatment compliance with nasal CPAP in those found to have OSA.
Two prior meta-analyses [5,13] of the studies that enrolled either normotensive or hypertensive participants showed conflicting findings in the effect of CPAP on nocturnal SBP. The results from our meta-analysis do show comparable reductions in nocturnal SBP in terms of the magnitude of change, statistical significance was not achieved. This is explained by our sensitivity analysis, which identified the study by Pedrosa et al. [15] as an outlier. This is because their study did not show a significant reduction in nocturnal SBP and DBP, a finding the authors themselves acknowledged was against their initial hypothesis and unexplained. This is an important finding as it has been previously suggested that nocturnal SBP may predict the future vascular events better than the diurnal measurements [32]. Similarly, in a separate study, Logan et al. [12] showed that resistant hypertension in patients with OSA is predominantly systolic and more pronounced at night. Excluding for the study by Pedrosa et al. [15], which did not show a decrease in nocturnal BP, the two studies by Martinez-Garcia et al. [21,29], and the ones by Lozano et al. [20] and Logan et al. [28] reported an increase in the number of study participants who recovered the normal nocturnal dipper BP pattern.
Our meta-analysis included patients who have or do not have subjective daytime sleepiness based on the ESSs (Table 2). Two previous studies by Barbe et al. [33] and Robinson et al. [34] suggest that CPAP treatment may not result in a significant BP reduction in those without daytime hypersomnolence. However, the study participants in both of these studies did not have resistant hypertension. At present, there is no clear evidence from the studies to suggest a similar association between daytime hypersomnolence and BP response to CPAP in patients with resistant hypertension. However, the results from our subgroup analyses (Tables 4 and 5) indicate that the participants with ESS less than 10, showed a similar statistically significant reduction in 24-h BP outcomes.
The data on correlation of BP change and hours of CPAP use was not universally available from all studies. On the basis of the two studies by Martinez-Garcia et al. [21,29], with a total of 121 participants, results of our meta-analysis show good correlation between hours of CPAP use and decrease in DBP. The latter study by Martinez-Garcia et al. also reported positive linear correlation between hours of CPAP use and decrease in 24-h SBP (r =0.29; P =0.02). However, the results are in contrast to that reported by Pedrosa et al. [15], who did not observe such a correlation in 19 study participants, a much smaller sample size.
The high prevalence of OSA among patients with resistant hypertension seems to be multifactorial, but the exact reasons are unclear. It is possible that both OSA and resistant hypertension share common mechanistic links. It has been postulated that overnight rostral fluid shift with fluid volume displacement from the legs to the neck plays an important role in the genesis of upper airway obstruction [35]. The phenomenon of overnight rostral fluid shift is more pronounced in patients with resistant hypertension than in those with controlled hypertension [35]. It is known that hyperaldosteronism and the associated fluid retention play a major mechanistic role in the development of resistant hypertension [36]. Similarly, although based on the preliminary evidence, aldosterone has also been implicated in the increased severity of OSA seen in patients with resistant hypertension [37,38]. Thus, it is possible that a common pathway between OSA and resistant hypertension could be the fluid retention.
Additionally, OSA alone can cause poorly controlled BP through several different mechanisms. Increased sympathetic tone [39], endothelial dysfunction [40], and salt and water dysregulation [6] have all been implicated as potential mechanisms for the increase in BP in OSA. Finally, another common link may be obesity, as this is a risk factor for both conditions [6].
Our meta-analysis has several strengths. First, we analyzed ambulatory and nocturnal BP data separately and also included separate analyses of these outcomes based on the RCTs. Second, our meta-analysis had enough power to detect a BP-lowering effect of CPAP in the included studies. Third, our meta-analysis included studies involving different geographic locations and ethnicities, allowing some degree of generalizability for our findings. Fourth, we performed sensitivity analyses to identify studies that could have caused a significant shift in the results. As expected in the nocturnal SBP and DBP analysis, the study by Pedrosa et al. [15] was the outlier, predominantly responsible for the statistical nonsignificance of results.
There are limitations to our study. It is possible that potential confounding factors in addition to CPAP treatment could have affected our findings. Most important of these include concomitant use of the antihypertensive medications, obesity and other life-style factors such as the use of alcohol and smoking. The small sample size and the short duration of follow-up for most included studies are other important limitations of our meta-analysis. Finally, visual assessment of the funnel plot revealed publication bias. However, this is because of the fact that we excluded the study by Zhang and Li [30], as it did not provide 24-h BP data. This was clearly evident, as including the office BP data from this study clearly did not reveal the publication bias.
Despite these limitations, the results of our meta-analysis argue strongly that OSA contributes to the resistance to medication treatment in patients with resistant hypertension because of the large effect size of CPAP treatment on BP reduction. This is important from an epidemiological standpoint at a population level. Even modest reductions in BP (especially DBP) of 2 mmHg [41] or 5 mmHg [42] have been associated with a significant decrease in the risk for stroke and coronary heart disease.
In conclusion, among patients with OSA and resistant hypertension, the pooled estimate shows a relatively large effect size on BP reduction with CPAP treatment. This supports the idea of more aggressive screening for OSA in those with resistant hypertension as well as ensuring treatment compliance in those found to have OSA. Our findings also support the notion that patients with OSA and resistant hypertension represent an extreme and unique phenotype compared with those OSA patients who do not develop hypertension. This may be the result of less common gene variants with large effect. Further research and RCTs involving a larger number of study participants, followed over a longer period of time, are warranted to confirm our findings.
Supplementary Material
Acknowledgments
The authors greatly appreciate the assistance of Alexander Y. Litvin (from the Russian Cardiology Research and Production Complex, Moscow, Russian Federation) in providing the specific data from their study in the participants with resistant hypertension.
Financial support: This study was supported by the NHLBI award P01 HL094307 (A.I.P.), HL093463 (U.J.M.) and UL1TR000090 of the Ohio State University Center for Clinical and Translational Science.
Abbreviations
- ABPM
ambulatory blood pressure monitoring
- AHI
apnea–hypopnea index
- BP
blood pressure
- CI
confidence interval
- CPAP
continuous positive airway pressure
- ESS
Epworth Sleepiness Score
- I2
marker for statistical heterogeneity
- mmHg
millimeters of mercury
- OSA
obstructive sleep apnea
- RCT
randomized controlled trial
Footnotes
Conflicts of interest
None of the authors have conflicts of interest with respect to this article.
This was not an industry-sponsored study.
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