Abstract
Background
Despite the considerable knowledge of Obstructive Sleep Apnea (OSA) implications for cardiac diseases, the evidence regarding cardiovascular complications across OSA phenotypes including Rapid Eye Movement OSA (REM-OSA) and Positional OSA (POSA) is limited. In this study, we aimed to evaluate the risk of cardiovascular diseases development and progression among patients with REM-OSA and POSA.
Methods
Based on a retrospective cohort analysis, we included polysomnography studies done in the sleep lab at the Jordan University Hospital. Regarding cardiovascular diseases, primary outcomes were Heart Failure, and 1-years Major Adverse Cardiac Events while secondary outcomes were atrial fibrillation, pulmonary hypertension, other arrhythmia, metabolic profile, and echocardiographic measurements of the heart.
Results
The total number of the included patients was 1,026 patients. POSA group had significantly lower percentage of patients with hypertension (P-value = 0.004). Additionally, systolic blood pressure and HbA1c were significantly lower among patients with POSA compared to the NPOSA group (P-value<0.050). Left ventricular end diastolic dimension was significantly higher among patients with POSA while ejection fraction was significantly lower (P-value<0.050). Patients with diabetes and mean HbA1c were significantly lower among patients with REM-OSA compared to patients with NREM-OSA (P-value = 0.015, P-value = 0.046). Multivariate regression analysis revealed that after adjusting for age, gender and preexisting comorbidities, POSA was significantly associated with lower ejection fraction and higher left ventricular diastolic diameter.
Conclusion
In conclusion, our findings indicate that POSA might be associated with huge and clinically significant heart strain and poor cardiac functions, yet it might not have a clinically significant atherogenic effect. This study should guide clinicians to identify OSA phenotypes to imply the best treatment plan to reduce its detrimental impact on cardiac muscle.
Keywords: Human, Sleep, OSA, Cardiovascular diseases, Heart failure
Highlights
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The evidence regarding cardiovascular diseases across OSA phenotypes is limited.
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A lower percentage of hypertension and HbA1c were found among patients with POSA.
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Left ventricular end diastolic dimension and EF were higher among POSA patients.
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A lower percentage of diabetes and mean of HbA1c were found among REM-OSA patients.
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Our findings indicate the REM-OSA and POSA might be associated with heart strain.
1. Introduction
Obstructive sleep apnea (OSA) is an increasingly common health concern. It is the most prevalent sleep-related breathing disorder that is characterized by recurrent episodes of upper airway collapse in which airflow significantly decreases (hypopnea) or completely ceases (apnea) resulting in intermittent hypoxemia, autonomic fluctuation, and sleep fragmentation [1,2].
OSA can be classified as Positional OSA (POSA) or Non-Positional OSA (NPOSA) according to whether the occurrence of respiratory events is associated with the body position during sleep, in which the number, and duration of apneas and hypopneas differ significantly with the changes in body position between these two phenotypes of OSA [3]. Moreover, OSA can be defined according to in which sleep stage the majority of apneas/hypopneas occur into Rapid Eye Movement OSA (REM-OSA) and Non-Rapid Eye Movement OSA (NREM-OSA). OSA patients are classified to have REM-OSA phenotype when the majority of the apneas/hypopneas occur in the REM stage of sleeping [4].
OSA has been associated with an increased incidence of development and progression of cardiovascular diseases [5]. OSA prevalence is as high as 40%–80% in patients with hypertension, heart failure, coronary artery disease, pulmonary hypertension, atrial fibrillation, and stroke [6]. The pathogenesis of cardiovascular disease in OSA includes sympathetic activation, fibrinolytic imbalance, vascular endothelial dysfunction, coagulation, oxidative stress, inflammation, and metabolic dysregulation [5]. Patients with OSA develop several physiological changes in the autonomic nervous system that have been implicated in the pathogenesis of cardiovascular disease development including an increased resting heart rate, decreased cardiac rhythm activity, and increased blood pressure variability [7]. These changes have also been linked to increased cardiovascular risk, elevated blood pressure, and impaired glucose metabolism [8]. Accordingly, OSA should be ruled out in patients with cardiovascular disease and be regarded as an important independent modifiable and treatable risk factor [9].
Despite the considerable knowledge of OSA implications for cardiac and vascular diseases, the evidence regarding cardiovascular complications across OSA phenotypes including REM-OSA and POSA is limited and much less understood. In this study, we aimed to evaluate the risk of cardiovascular diseases development and progression among patients with REM-OSA and POSA.
2. Methods
2.1. Data selection
Based on a retrospective cohort analysis, 1,092 polysomnography studies were done in the sleep lab at the Jordan University Hospital (JUH) between June 2016 and March 2022. Referral to the sleep study was based on the clinical suspicion of OSA (snoring, increased daytime sleepiness, witnessed apnea, and early morning headache) and preoperative evaluation of surgical patients. Patients with Apnea Hypopnea Index (AHI) > 5 were considered to have OSA and were subsequently included in our study. Consequently, 55 patients were excluded.
2.2. Polysomnography and sleep data
The overnight study consisted of continuous recordings of an electrocardiographic lead, right and left electrooculographic leads, submental, and two electroencephalographic leads. Respiration was monitored throughout the night using thermocouples at the nose and mouth in addition to thoracic and abdominal strain gauges. Recordings of the oxyhaemoglobin saturation (SaO2) and duration of saturation below 90% SpO2 (minutes) were obtained. The biophysiological changes on the polysomnography (PSG) device were evaluated using the 2015 version of the American Academy of Sleep Medicine (AASM) manual for the scoring of sleep and associated events for studies performed before 2018 while all the studies done on and after 2018 were analyzed using the 2018 AASM manual. Obstructive apnea was defined as a reduction in the airflow greater than 90% with respiratory effort lasting at least 10 s. Hypopnea was defined as a reduction of more than 30% in the airflow associated with an electroencephalographic arousal or a drop of at least 3% in the SaO2. The AHI was calculated as the total number of apneas and hypopneas per hour of total sleep time. Sleep state-dependent indices (i.e., Non-Rapid Eye Movement AHI (NREM-AHI) and Rapid Eye Movement AHI (REM-AHI)) were also determined by dividing the number of events in NREM and REM sleep by the amount of NREM and REM time, respectively. The position during sleep was determined using position sensors. The Arabic version of the Epworth Sleepiness Scale (ESS), which was validated by Ahmed et al., was used to assess patient sleepiness [10]. Positional obstructive sleep apnea (POSA) was defined as the overall AHI>5, the overall AHI severity of at least 1.4 times the non-supine severity (Overall/NS-AHI) and a minimum amount of time (i.e., 20 min) in the supine and non-supine positions [11]. We chose this definition as it demonstrated the best consistency in detecting patients who were most likely to have reductions in sleep disordered breathing severity if supine sleep was avoided [11]. In addition, a previous study conducted in Jordan among OSA patients demonstrated that the Overall/NS-AHI criterion was valid, sensitive, specific and accurate in diagnosing OSA. Also, it showed superiority in terms of diagnostic measures over other criteria [12]. Moreover, we retested the differences between POSA and NPOSA while using Cartwright Criteria which defines POSA as a difference of 50% or more in AHI between supine and non-supine positions [12]. REM predominant OSA was defined as an overall AHI of ≥5 and a ratio of the AHI during REM sleep to the AHI during NREM sleep of ≥2 [13].
2.3. Clinical data and cardiovascular outcomes
Data about patients' demographics and comorbidities were collected including age, gender, Body Mass Index (BMI), diabetes, and chronic kidney disease. Clinical data from the patients follow up in the clinics including systolic and diastolic blood pressure were also obtained. Laboratory data including urea (mg/dl), creatinine (mg/dl), and Brain Natriuretic Peptide (BNP) (mg/dl) were also collected. Regarding cardiovascular diseases, primary outcomes were Heart Failure (HF), and 1-years Major Adverse Cardiac Events (1-year MACE) while secondary outcomes were atrial fibrillation, pulmonary hypertension, other arrhythmia, metabolic profile, and echocardiographic measurements of the heart. Heart failure was defined as clinical symptoms or signs suggestive of heart failure and elevation of BNP or echocardiographic evidence of pulmonary cardiac congestion. One year MACE was defined as the occurrence of myocardial infarction, cardiac death, congestive heart failure, percutaneous coronary intervention or coronary artery bypass surgery. Atrial fibrillation and arrhythmias were diagnosed based on Electrocardiography while pulmonary artery hypertension defined as pulmonary artery pressure higher than 20 mm Hg diagnosed using right sided heart catheterization. Metabolic profile included High Density Lipoprotein (mg/dl), Low Density Lipoprotein (mg/dl), and Glycated hemoglobin (HbA1c). Echocardiography measures included left atrial pressure, left ventricular end diastolic dimension in millimeters, ejection fraction, and pulmonary artery pressure were reviewed. All the data regarding patients’ clinical data and cardiovascular outcomes were collected 1 year after the OSA diagnosis.
2.4. Data analysis
The patients’ data was entered in Microsoft Office Excel 2019, then imported into IBM SPSS v.25 software to conduct the analysis. Continuous variables were summarized as mean and standard deviation while categorical variables were summarized as counts and percentages. The comparisons in categorical variables across the phenotypes of OSA were done using the chi-square test. Whereas the differences in continuous variables between the groups were examined using T-test. A P-value less than 0.050 was considered statistically significant across all the tests. The association between OSA Phenotypes and Left Ventricular End Diastolic Diameter as well as Ejection Fraction, when it was significant in the univariate analysis, was investigated using linear regression analysis while adjusting for age, gender and preexisting comorbidities.
3. Results
3.1. The characteristics of the included patients
The total number of the included patients was 1,026 patients. Of them 51.2% were males. The mean age of the patients was 59.78 ± 14.01. Around 60.0% of the patients had hypertension while 42.9% of the patients had diabetes. Moreover, 29.0% and 13.0% of the patients had hyperlipidemia and heart failure, respectively. Additionally, 4.7% of the patients had atrial fibrillation and 23.6% of them had MACE within 1 year after the diagnosis of OSA. The most frequent medications used by the patients were beta blockers (23.4%), insulin (23.9%), and angiotensin receptor blocker (19.4%). The mean systolic and diastolic blood pressure were 141.83 ± 13.84 and 83.24 ± 8.46, respectively. Furthermore, the mean HDL and LDL were 45.33 ± 20.9 and 113.44 ± 39.4, respectively. The mean BNP was 53.67 ± 246.85 while the mean LVEDD was 29.63 ± 30.23 mm. In addition, the mean ejection fraction and pulmonary artery pressure were 53.43 ± 8.27 and 47.89 ± 14.06, respectively. Table 1 describes the characteristics, comorbidities, and cardiovascular echocardiography measurements.
Table 1.
The general demographics of the participants.
| Variable | Response | Frequency | Percentage (%) |
|---|---|---|---|
| Sex | Male | 525 | 51.2 |
| Female | 501 | 48.8 | |
| Hypertension | No | 412 | 40.0 |
| Yes | 617 | 60.0 | |
| Diabetes Mellitus | No | 588 | 57.1 |
| Yes | 442 | 42.9 | |
| Hyperlipidemia | No | 731 | 71.0 |
| Yes | 299 | 29.0 | |
| Heart Failure | No | 889 | 87.0 |
| Yes | 133 | 13.0 | |
| Chronic Kidney Disease | No | 466 | 48.4 |
| Yes | 49 | 5.1 | |
| Atrial Fibrillation | No | 982 | 95.3 |
| Yes | 48 | 4.7 | |
| Other Arrhythmias | No | 506 | 70.6 |
| Yes | 211 | 29.4 | |
| MACE | No | 787 | 76.4 |
| Yes | 243 | 23.6 | |
| Medications | Metformin | 157 | 15.3 |
| Angiotensin Converting Enzyme Inhibitor | 147 | 14.3 | |
| Angiotensin Receptor Blocker | 200 | 19.4 | |
| Diuretics | 143 | 13.9 | |
| Insulin | 245 | 23.8 | |
| Beta Blockers | 241 | 23.4 | |
| Anti-platelet | 131 | 12.6 | |
| Anti-coagulants | 157 | 15.2 | |
| Calcium Channel Blockers | 116 | 11.3 | |
| Alpha Blockers | 22 | 2.1 | |
| Type of Positional OSA | NPOSA | 599 | 57.8 |
| POSA | 431 | 41.6 | |
| Type of REM OSA | REM-OSA | 211 | 26.1 |
| NREM-OSA | 596 | 73.9 |
| Variable | Mean | SD | Range |
|---|---|---|---|
| Age (years) | 59.78 | 14.01 | 18–101 |
| Creatinine (mg/dl) | 1.43 | 0.72 | 0.34–5.21 |
| Hb1AC | 6.64 | 1.56 | 0.86–13.00 |
| Systolic Blood Pressure | 141.83 | 13.84 | 60–211 |
| Diastolic Blood Pressure | 83.24 | 8.46 | 30–140 |
| High Density Lipoprotein | 45.33 | 20.9 | 3–449 |
| Low Density Lipoprotein | 113.44 | 39.4 | 9–258 |
| Triglyceride | 165.48 | 89.25 | 31–738 |
| Urea | 122.75 | 437.60 | 2.23–616.52 |
| Brain Natriuretic Peptide | 53.67 | 246.85 | 0–3449.25 |
| Left Atrial Pressure | 4.48 | 0.86 | 2.6–9.0 |
| Left Ventricular End Diastolic Diameter (millimeters) | 29.63 | 30.23 | 4.00–503.00 |
| Ejection Fraction | 53.43 | 8.27 | 16–89 |
| Pulmonary Artery Pressure | 47.89 | 14.06 | 19–90 |
3.2. Difference between POSA and NPOSA
Our analysis that investigated the differences between POSA and NPOSA patients showed that female patients were significantly higher among patients with POSA (54.8%) compared to their counterparts (45.2%) (P-value = 0.006). The mean age of the patients with POSA was significantly lower compared to the NPOSA group (P-value = 0.040). Moreover, the percentage of patients with hypertension was significantly lower among patients with POSA (54.8%) compared to patients with NPOSA (63.7%) (P-value = 0.004). Additionally, systolic blood pressure and HbA1c were significantly lower among patients with POSA compared to the other group (P-value = 0.026, P-value = 0.010). Left ventricular end diastolic dimension was significantly higher among patients with POSA (9.32 ± 6.99 mm) compared to patients with NPOSA (5.64 ± 2.43 mm) (P-value = 0.036). Patients with POSA had significantly lower ejection fraction (52.65 ± 8.57) compared to their counterparts (54.73 ± 7.61) (P-value = 0.014) (Table 2). The comparison between POSA and NPOSA groups while using the Cartwright Criteria showed similar findings (Table 3). Multivariate regression analysis revealed that after adjusting for age, gender and preexisting comorbidities, POSA was significantly associated with lower ejection fraction (Table 4; AB = −1.966; 95%CI: −3.706 to −0.226) and higher left ventricular diastolic diameter (Table 4; AB = 5.289; 95%CI: 0.711–9.868).
Table 2.
Differences in the demographics between POSA and NPOSA according to overall/non-supine criteria.
| Variable | NPOSA (n = 602) | POSA (n = 431) | P-value | |
|---|---|---|---|---|
| Gender | Male | 327 (54.8) | 198 (46.2) | 0.006* |
| Female | 270 (45.2) | 327 (54.8) | ||
| Age | 60.57 ± 13.46 | 58.69 ± 14.69 | 0.040* | |
| Hypertension | Yes | 381 (63.7) | 236 (54.8) | 0.004* |
| No | 217 (36.3) | 195 (45.2) | ||
| Diabetes | No | 333 (55.6) | 255 (59.2) | 0.253 |
| Yes | 266 (44.4) | 176 (40.8) | ||
| Heart Failure | No | 515 (86.4) | 374 (87.8) | 0.517 |
| Yes | 81 (13.6) | 52 (12.2) | ||
| Hyperlipidemia | No | 425 (71.0) | 306 (71.0) | 0.987 |
| Yes | 174 (29.0) | 125 (29.0) | ||
| Chronic Kidney Disease | No | 280 (50.0) | 34 (6.1) | 0.475 |
| Yes | 65 (19.4) | 15 (3.7) | ||
| Atrial Fibrillation | No | 569 (95.0) | 413 (95.8) | 0.532 |
| Yes | 30 (5.0) | 18(4.2) | ||
| Other Arrhythmias | No | 307 (71.7) | 199 (68.9) | 0.408 |
| Yes | 121 (28.3) | 90 (31.1) | ||
| MACE |
No | 453 (75.6) | 334 (77.5) | 0.486 |
| Yes |
146 (24.4) |
97 (22.5) |
||
| Creatinine (mg/dl) | 0.31 ± 0.30 | 0.31 ± 0.28 | 0.785 | |
| Hb1AC | 6.75 ± 1.58 | 6.49 ± 1.52 | 0.026* | |
| Systolic Blood Pressure | 142.95 ± 12.56 | 140.23 ± 15.38 | 0.010* | |
| Diastolic Blood Pressure | 83.53 ± 8.32 | 82.83 ± 8.67 | 0.259 | |
| High Density Lipoprotein | 44.80 ± 23.67 | 46.00 ± 14.16 | 0.429 | |
| Low Density Lipoprotein | 111.75 ± 38.92 | 115.62 ± 39.99 | 0.193 | |
| Triglyceride | 168.41 ± 89.75 | 161.71 ± 88.59 | 0.319 | |
| Urea | 23.66 ± 4.5 | 21.50 ± 4.1 | 0.952 | |
| Brain Natriuretic Peptide | 64.30 ± 271.62 | 39.15 ± 207.88 | 0.171 | |
| Left Atrial Pressure | 4.46 ± 0.82 | 4.50 ± 0.90 | 0.599 | |
| Left Ventricular End Diastolic Diameter (millimeters) | 5.64 ± 2.43 | 9.32 ± 6.99 | 0.036* | |
| Ejection Fraction | 54.73 ± 7.61 | 52.65 ± 8.57 | 0.014* | |
| Pulmonary Artery Pressure | 48.33 ± 15.68 | 47.22 ± 11.59 | 0.786 | |
Table 3.
Differences in the demographics between POSA and NPOSA according to cartwright criteria.
| Variable | NPOSA (n = 758) | POSA (n = 275) | P-value | |
|---|---|---|---|---|
| Gender | Male | 475 (62.7) | 50 (18.2) | 0.008* |
| Female | 283 (37.3) | 225 (81.8) | ||
| Age | 63.43 ± 12.34 | 60.69 ± 13.12 | 0.032* | |
| Hypertension | Yes | 494 (65.2) | 123 (44.7) | 0.021* |
| No | 264 (34.8) | 152 (55.3) | ||
| Diabetes | No | 405 (53.4) | 186 (67.7) | 0.109 |
| Yes | 353 (46.6) | 89 (32.3) | ||
| Heart Failure | No | 652 (86.0) | 248 (90.2) | 0.317 |
| Yes | 106 (14.0) | 27 (9.8) | ||
| Hyperlipidemia | No | 542 (71.5) | 192 (70.0) | 0.975 |
| Yes | 216 (28.5) | 83 (30.0) | ||
| Chronic Kidney Disease | No | 603 (79.5) | 250 (90.8) | 0.239 |
| Yes | 155 (20.5) | 25 (9.2) | ||
| Atrial Fibrillation | No | 719 (94.9) | 266 (96.8) | 0.279 |
| Yes | 39 (5.1) | 9 (3.2) | ||
| Other Arrhythmias | No | 434 (75.0) | 208 (75.6) | 0.918 |
| Yes | 144 (25.0) | 67 (24.4) | ||
| MACE |
No | 401 (69.4) | 209 (75.9) | 0.751 |
| Yes |
177 (30.6) |
66 (24.1) |
||
| Creatinine (mg/dl) | 0.32 ± 0.29 | 0.32 ± 0.28 | 0.832 | |
| Hb1AC | 6.81 ± 1.52 | 6.51 ± 1.51 | 0.021* | |
| Systolic Blood Pressure | 144.21 ± 13.12 | 141.23 ± 14.23 | 0.007* | |
| Diastolic Blood Pressure | 81.23 ± 8.12 | 82.12 ± 8.23 | 0.467 | |
| High Density Lipoprotein | 45.12 ± 21.43 | 45.98 ± 20.59 | 0.518 | |
| Low Density Lipoprotein | 109.89 ± 37.87 | 112.32 ± 38.35 | 0.287 | |
| Triglyceride | 169.12 ± 88.65 | 162.32 ± 87.34 | 0.523 | |
| Urea | 22.87 ± 4.0 | 22.50 ± 4.0 | 0.981 | |
| Brain Natriuretic Peptide | 65.12 ± 272.89 | 42.13 ± 209.23 | 0.271 | |
| Left Atrial Pressure | 4.43 ± 0.76 | 4.42 ± 0.213 | 0.765 | |
| Left Ventricular End Diastolic Diameter (millimeters) | 4.89 ± 2.32 | 8.81 ± 6.87 | 0.046* | |
| Ejection Fraction | 55.12 ± 7.23 | 52.76 ± 8.13 | 0.024* | |
| Pulmonary Artery Pressure | 48.32 ± 15.23 | 47.56 ± 11.98 | 0.817 | |
Table 4.
Multivariate Linear Regression Analysis for the Association between POSA and Left Ventricular End Diastolic Diameter as well as Ejection Fraction Adjusted for Age, Gender and Preexisting Comorbidities.
| Outcome | Exposure | AB (95% CI) | P-value |
|---|---|---|---|
| Left Ventricular End Diastolic Diameter (millimeters) | POSA | −1.966 (−3.706 to −0.226) | 0.027a |
| Ejection Fraction | POSA | 5.289 (0.711–9.868) | 0.024a |
| Ejection Fraction | REM-OSA | 1,612 (−3.411-6.636) | 0.529 |
P-value<0.050, AB: Adjusted B Coefficient.
3.3. Difference between REM predominant and NREM predominant OSA
Our results showed that male patients were significantly higher among REM-OSA group (71.8%) compared to NREM (38.3%) (P-value = 0.000). The mean age was significantly lower among REM-OSA compared to the other group (P-value = 0.000). The percentage of patients with diabetes was significantly lower among patients with REM-OSA (32.7%) compared to patients with NREM-OSA (42.3%) (P-value = 0.015). Mean HbA1c was significantly lower among patients with REM-OSA (6.24 ± 1.39) compared to their counterparts (6.72 ± 1.58) (P-value = 0.001). HDL and LDL levels were significantly higher among patients with REM-OSA compared to patients with NREM-OSA (P-value = 0.025, P-value = 0.000). Urea levels were significantly lower among patients with REM-OSA (P-value = 0.003). Moreover, ejection fraction was significantly lower among patients with REM-OSA (31.06 ± 24.63) compared to patients with NREM-OSA (54.09 ± 24.22) (P-value = 0.046) (Table 5). Multivariate regression analysis demonstrated that after adjusting for age, gender and preexisting comorbidities, REM-OSA was not associated with ejection fraction (Table 4; AB = 1,612; 95%CI: −3.411-6.636).
Table 5.
Differences between REM-OSA and NREM-OSA patients.
| Variable | NREM-OSA (n = 595) | REM-OSA (n = 209) | P-value | |
|---|---|---|---|---|
| Gender | Male | 228 (38.3) | 150 (71.8) | 0.000* |
| Female | 367 (61.7) | 59 (28.2) | ||
| Age | 60.11 ± 13.33 | 54.99 ± 14.47 | 0.000* | |
| Hypertension | Yes | 353 (59.2) | 113 (53.8) | 0.172 |
| No | 243 (40.8) | 97 (46.2) | ||
| Diabetes | No | 344 (57.7) | 142 (67.3) | 0.015* |
| Yes | 252 (42.3) | 69 (32.7) | ||
| Heart Failure | No | 527 (89.3) | 191 (91.0) | 0.504 |
| Yes | 63 (10.7) | 19 (9.0) | ||
| Hyperlipidemia | No | 432 (72.5) | 149 (70.6) | 0.604 |
| Yes | 164 (27.5) | 62 (29.4) | ||
| Chronic Kidney Disease | No | 262 (47.5) | 28 (5.1) | 0.148 |
| Yes | 65 (19.4) | 7 (3.5) | ||
| Atrial Fibrillation | No | 568 (95.3) | 205 (97.2) | 0.249 |
| Yes | 28 (4.7) | 6 (2.8) | ||
| Other Arrhythmias | No | 286 (68.9) | 98 (73.7) | 0.296 |
| Yes | 129 (31.1) | 35 (26.3) | ||
| MACE |
No | 457 (76.7) | 165 (78.2) | 0.651 |
| Yes |
139 (23.3) |
46 (21.8) |
||
| Creatinine (mg/dl) | 0.34 ± 0.27 | 0.34 ± 0.25 | 0.657 | |
| Hb1AC | 6.72 ± 1.58 | 6.24 ± 1.39 | 0.001* | |
| Systolic Blood Pressure | 141.80 ± 13.71 | 140.90 ± 12.54 | 0.470 | |
| Diastolic Blood Pressure | 83.29 ± 8.26 | 83.13 ± 7.56 | 0.826 | |
| High Density Lipoprotein | 44.43 ± 23.83 | 48.99 ± 14.23 | 0.025* | |
| Low Density Lipoprotein | 111.16 ± 37.65 | 125.21 ± 37.77 | 0.000* | |
| Triglyceride | 168.78 ± 93.18 | 156.34 ± 85.00 | 0.145 | |
| Urea | 25.05 ± 4.19 | 5.26 ± 0.98 | 0.003* | |
| Brain Natriuretic Peptide | 38.47 ± 183.50 | 22.81 ± 97.55 | 0.346 | |
| Left Atrial Pressure | 4.49 ± 0.87 | 4.41 ± 0.82 | 0.327 | |
| Left Ventricular End Diastolic Diameter (millimeters) | 6.93 ± 2.42 | 9.05 ± 2.46 | 0.383 | |
| Ejection Fraction | 54.09 ± 24.22 | 31.06 ± 24.63 | 0.046* | |
| Pulmonary Artery Pressure | 47.72 ± 13.22 | 52.83 ± 21.82 | 0.461 | |
4. Discussion
OSA is a common sleep disorder with long-term major neurocognitive and cardiovascular sequalae [14]. Studies have characterized the heterogeneity of OSA into well-defined phenotypes based on the predominance of the disorder [15]. The importance of this classification stems from the basis of applying different treatment disorders to minimize the morbidity of the disease [16]. The treatment of OSA mainly depends on CPAP however, positional therapy has been implied in the treatment of POSA [16]. OSA is associated with several adverse cardiovascular outcomes including coronary artery disease, heart failure, hypertension, and cardiac arrhythmias [17]. The aim of this study was to investigate the differences between OSA phenotypes in cardiovascular diseases.
Our study showed that patients with REM-OSA tended to be of younger age and to have lower percentage of diabetes. Previous studies have demonstrated that REM-OSA patients are of younger age group [18,19]. On the other hand, other studies showed that age was not significantly different between REM and NREM OSA groups [20]. Moreover, studies showed that type 2 diabetes is more prevalent among REM-OSA than NREM-OSA patients [21]. Additionally, HbA1c was significantly lower among REM-OSA patients while HDL and LDL were significantly lower. Studies showed that low REM latency was associated with higher HbA1c and fasting plasma glucose indicating that REM OSA phenotype has a high impact of glucose levels and control [22,23]. The plausible mechanism for the impact of REM-OSA on glucose levels was suggested by several studies. REM-OSA was associated with an increase in sympathetic activity and IL-1b which are both associated with increase in insulin resistance [24]. These differences between our findings and the aforementioned studies might be because of including patients without diabetes as studies showed that REM-OSA is associated with poor glycemic control measures only among patients with diabetes. Furthermore, studies showed that lifestyle modifications and weight loss was associated with reduction in HbA1c and improvement in diabetes control regardless of AHI reduction questioning the relationship between REM-OSA and diabetes and suggesting a huge impact of BMI on this relationship [25]. Previous studies showed that REM-OSA was associated with an increase in triglyceride and LDL but not HDL [22]. Another study demonstrated that the association between REM sleep disorder and metabolic parameters are poor and might be clinically negligible [26]. On the other hand, a recent study showed that REM-OSA was associated with higher HDL and TG but not LDL [27]. The contradictions regarding these associations in the literature might be due to the differences in these studies in the criteria used to diagnose REM-OSA and the ethnic as well as genetic background [26]. However, studies showed controlling BMI as a confounding factor eliminated the impact of REM-OSA on lipid profile parameters [28]. In addition, our findings that showed increase in LDL and HDL among REM-OSA patients indicates that REM-OSA might not affect atheroma formation which is also evident by absence of association between REM-OSA and acute MACE events demonstrated by our study [29]. However, it is important to demonstrate that the rate of 1-year MACE among OSA patients was high in our study (24.6%). The role of the OSA in increasing cardiac events is well established in the literature [30]. In addition, managing OSA through upper airway surgery or CPAP was shown to reduce acute coronary syndrome while intolerance to CPAP increased the risk of mortality among patients with stroke [31,32]. Nevertheless, no randomized trials were able to demonstrate the efficacy of CPAP in reducing cardiovascular and cerebrovascular events [33,34].
Our results demonstrated that patients with POSA tended to be females and of younger age compared to NPOSA which is similar to previous studies in the literature [35,36]. Patients with POSA had significantly lower prevalence of hypertension and lower mean systolic blood pressure. Since POSA is considered a low OSA severity phenotype in terms of AHI, it is expected that patients with POSA exhibit lower sympathetic activity and thus lower blood pressure readings and prevalence of hypertension [37]. These findings were also demonstrated in previous studies [37,38]. In addition, patients with POSA had significantly lower HbA1c levels which is similar to previous studies. This relationship was implicated by the low BMI associated with patients with POSA, hence they are expected to have lower insulin resistance [39]. Moreover, patients with POSA had significantly higher left ventricular end diastolic dimension compared to patients with NPOSA. Previous studies showed that patients with heart failure have high prevalence of POSA [40] and studies has demonstrated that left ventricular end diastolic dimension is an indicator for impending heart failure [41]. In addition, studies showed that lateral sleeping position among those patients improve their heart failure condition [41]. Also, ejection fraction was significantly lower among patients with POSA The improvement of ejection fraction due to improvement in sympathetic tone among patients with heart failure was concluded by previous studies indicating the importance of using CPAP and positional therapy to improve OSA [42].
Although this is one of the first studies in the literature to explore the association, several limitations should be acknowledged. First, the retrospective nature of our study limits our conclusions to associations instead of causal relationships. Second, this study was conducted in a single center which limits the generalizability of our findings. Thus, future large multicentric well-conducted studies are needed. Furthermore, despite the fact that we used the most consistent definitions of POSA and REM-OSA and the ones that identifies patients with higher probability to benefit from therapy, several definitions were proposed to identify OSA phenotypes. Finally, the diagnosis of POSA and REM-OSA was made based on single night PSG and it is unknown if OSA phenotypes are stable night to night phenotype or not.
In conclusion, REM-OSA patients had lower HbA1c but slightly higher and might be clinically negligible HDL and LDL levels indicating that REM-OSA is not associated with clinically significant atherogenic effect. Moreover, Patients with POSA had higher prevalence of hypertension and systolic blood pressure. Also, POSA was significantly associated with lower ejection fraction and poor cardiac functions. Our findings indicate that POSA might be associated with huge and clinically significant heart strain and poor cardiac functions. This study should guide clinicians to identify OSA phenotypes to imply the best treatment plan to reduce its detrimental impact on cardiac muscle.
Data sharing
The data associated with this manuscript are available from the corresponding author upon reasonable request.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Ethical approval
This study was approved by the institutional review board (IRB) of the Jordan University Hospital (JUH) (IRB#) and the IRB waived the need for consent from the participants. This study was conducted in accordance with the declaration of Helsinki.
CRediT authorship contribution statement
Khaled Al Oweidat: were involved in conceptualization, were involved in supervision and reviewing & editing the manuscript. Ahmad A. Toubasi: were involved in conceptualization. Thuraya N. Al-Sayegh: were involved in data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, and writing the original draft. Rima A. Sinan: were involved in data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft. Sara H. Mansour: were involved in data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft. Hanna K. Makhamreh: were involved in data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, were involved in supervision and reviewing & editing the manuscript.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
None.
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