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Risk for stroke and chronic kidney disease in patients with sleep apnea syndrome and heart failure with different ejection fractions


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Introduction

Breathing disorders occurring during the night are more commonly associated with cardiovascular diseases (1).

Obstructive sleep apnea syndrome (SAS) has many phenotypes, and efforts are made for better understanding of this particular aspect (2).

It is well known that both obstructive and central SAS are more common in patients with heart failure (HF) than general population and can contribute to progression of HF due to intermittent hypoxia, endothelial dysfunction, increasing preload and afterload and activation of the sympathetic nervous system (SNS) (3).

HF is a common disease with a severe prognosis. In Europe, more than 14 million of patients are estimated and 3 million new cases are diagnosed annually (4). The mortality at 5 years for these patients is 40%–60% (5).

The purpose of this study was to observe the differences between patients with SAS and heart failure with reduced ejection fraction (HFrEF) and those with SAS and heart failure with preserved ejection fraction (HFpEF).

Methods

We enrolled consecutive patients evaluated for SAS at the “Victor Babes” Timisoara Hospital between 2011 and 2016 and for HF at the Timisoara Institute for Cardiovascular Diseases. In this study were included patients >40 years old who were diagnosed with HF and SAS based on polygraphy, echocardiography and blood test evaluation. Patients with incomplete evaluation and those with no SAS were excluded. Research protocols were approved by the ethical committee of institution, and a signed informed consent was obtained from all the patients. For sleep study, we followed the European standards for diagnostic of Sleep apnea syndrome (6).

Fifty-eight patients were screened, and 51 met the inclusion criteria. Patients were initially evaluated through a standard datasheet with the following parameters: age; gender; height; weight; body mass index (BMI; weight in kilogram/squared height in meter); neck, abdominal and hips circumference; presence and duration of hypertension; maximum and current value of blood pressure; medication; reported apneas; snoring; sleepiness; Epworth Scale; morning headache; restless sleep; nicturia; nocturnal awakenings; Chronic Obstructive Pulmonary Disease; diabetes; dyslipidemia; coronary artery disease; HF; arrhythmias; stroke; nasal septum deviation; polyposis; hypertrophic uvula; smoking status and SAS score. The somnographic recording was done with Stardust Respironics and Porti. Several parameters were measured: the number of central, obstructive, mixed apnea and hypopnea; both the total number of events and the number of events per hour; the apnea–hypopnea index (AHI); the desaturation index; the mean saturation; the lowest saturation; and the longest desaturation period. The somnographic recording was performed and scored manually according to American Academy of Sleep Medicine standards and European Sleep Research Society recommendation (6,7).

The laboratory test was performed in Romanian Accreditation Association-RENAR certified medical laboratories: erythrocyte sedimentation rate (ESR; mm/h), uric acid (mg/dl), creatinine (mg/dl), erythrocyte count (*106/μ1), total cholesterol (mg/dl), LDL-Low-Density Lipoprotein, HDL- High-Density Lipoprotein cholesterol (mg/dl), HDL-cholesterol (mg/dl) and triglycerides (mg/dl).

The cardiological evaluation was performed for all patients at the Institute of Cardiovascular Diseases in Timisoara using the same diagnostic algorithm.

HF was categorised according to the left ventricle ejection fraction (LVEF), with HF with LVEF 350% referred to as HFpEF and HF with LVEF <50% referred to as HFrEF (1). Recently, according to ESC- European Society of Cardiology Guidelines for the diagnosis and treatment of acute and chronic HF published in 2016, HFrEF has been subdivided into mid-range (LVEF 40%–49%) and reduced ejection fraction (LVEF<40%). Because we enrolled patients between 2011 and 2016, we did not include this subdivision.

The echocardiographic method for measurement of ejection fraction (EF) was the apical biplane method of discs (the modified Simpson’s rule) and was performed by a highly specialized cardiologist with the same equipment.

The morphological aspect, the area (cm), degree of regurgitation and stenosis and transvalvular presionale gradients were determined for the mitral, aortic, tricuspid and pulmonary valves (8).

Statistical analysis

The statistical analysis was performed using Microsoft Excel 2013. The results are expressed as mean ± standard deviation. The differences in the characteristics of the subjects were evaluated after they were divided into two groups, depending on the EF. For comparing the groups, the “t-test” for the continuous variables was used.

The standard significance level was set at 0.05; so if the calculated probability was below this threshold, the differences were considered to be significant.

Results

The initial patient lot was divided into two study groups according to the EF. Thus, 25 patients (49%) had HFrEF and 26 patients (51%) had HFpEF.

Anthropometrics

Regarding anthropometric parameters, the analysis revealed that the statistical differences between the two groups of patients were not significant, with similar age, gender, BMI and neck and abdominal circumferences (Table 1).

Anthropometric values in the groups with HFrEF versus HFpEF.

HFrEF (25 patients) HFpEF (26 patients)
Mean value ± standard deviationMean value ± standard deviationp value
Age (years)63.6±8.861.54±9.10.39
Gender7 females (28%)7 females (27%)
18 males (72%)19 males (73)
BMI (kg/m2)37.9±7.537±6.40.65
Neck circumference (cm)46±4.445.4±3.60.57
Abdominal circumference (cm)127.2±13.9126.6±12.90.87
Sleep measurements

Comparative analysis of cardiorespiratory polygraphic parameters in the two groups of patients (AHI; central, obstructive and mixed apnea; mean, lowest, longest <88% and desaturation index; Epworth scale and SAS score) shows no statistically significant differences (Table 2).

The values of the polygraphic parameters in the groups with HFrEF and HFpEF.

HFrEF HFpEF
Polygraphic parametersMean value ± standard deviationMean value ± standard deviationp value
AHI (n/h)46.4±21.748.3±22.60.75
Central apnea (n/h)4.6±8.35.6±11.40.7
Obstructive apnea (n/h)25.9±18.525.7±18.70.97
Mixed apnea (n/h)4.6±7.66.2±10.70.44
Desaturation index (n/h)44.8±27.141.2±21.20.59
Mean saturation (%)90.2±6.389.8±5.30.84
Lowest SpO2 (%)70.6±12.172.1±140.69
Longest SpO2 <88% (min)3±5.810.5±33.50.29
Epworth scale14±613.3±5.60.69
SAS score4.6±0.84.5±0.70.71
Comorbidities

Regarding comorbidities, there was a statistically significant difference between the two groups only in the incidence of stroke and there was no significant differences for COPD, diabetes mellitus, dyslipidemia, coronary artery disease, arrhythmias and smoking status (Table 3).

The number of patients with different comorbidities in the groups with HFrEF and HFpEF and p value.

ComorbiditiesHFrEF (n, %)HFpEF (n, %)p value
COPD8 patients32%3 patients11.5%0.07
Diabetes7 patients28%14 patients53.8%0.06
Dyslipidemia15 patients60%18 patients69.2%0.5
Coronary artery disease20 patients80%18 patients69.2%0.38
Arrhythmias18 patients72%13 patients50%0.11
Stroke1 patient4%6 patients23%0.04
Smoking status11 patients44%11 patients42.3%0.9
Laboratory parameters

Patients with HFrEF had a significantly higher serum creatinine level than patients with HFpEF (1.4±0.7 vs. 1.1±0.2, respectively; p=0.049).

For the other laboratory parameters such as ESR, uric acid, erythrocyte count, total cholesterol, LDL-cholesterol, HDL-cholesterol and triglycerides, it can be seen that patients with HFrEF have higher values than patients with HFpEF, but no statistically significant differences were observed in the analysis (Table 4).

Laboratory parameter values in groups with HFrEF and HFpEF and p value.

HFrEF HFpEF
Laboratory parametersMean value±standard deviationMean value±standard deviationp value
ESR (mg/dl)21.5±24.314.4±90.21
Uric acid (mg/dl)7.4±2.86.6±1.80.36
Creatinine (mg/dl)1.4±0.71.1±0.20.049
Erythrocyte count (*106/ml)4.9±0.94.8±0.50.8
Cholesterol (mg/dl)164.7±38.4164.7±54.20.9
LDL-cholesterol (mg/dl)94.1±2979.1±25.30.15
HDL-cholesterol (mg/dl)42.4±10.741.9±10.40.88
Triglycerides (mg/dl)133.5±81.6191.4±105.60.06
Echocardiography

Echocardiographic evaluation shows that the number of patients with aortic impairment (p=0.004) and tricuspid insufficiency (p=0.01) is significantly higher in the HFrEF group (Table 5).

The number of patients with valvular pathology in the groups with HFrEF and HFpEF and p value.

Valve alterationHFrEF (n, %)HFpEF (n, %)p value
Mitral insufficiency24 patients96%21 patients80.7%0.09
Aortic insufficiency9 patients36%3 patients11.5%0.04
Tricuspid insufficiency20 patients80%12 patients46.1%0.01
Pulmonary insufficiency1 patient4%3 patients11.5%0.32
Discussion

Analysis of anthropometric and somnographic parameters did not reveal statistically significant differences between the two groups, including respiratory events, oxygen desaturation measurements, Epworth somnolence scale and SAS prediction score. Somnolence evaluated with the Epworth scale has a better prediction value when it is included in a validated prediction score (9).

In comparison with the existing algorithm, SAS score is a more appropriate screening tool for monitoring large populations, due to its improved specificity, but probably because of a small number of patients, it fails to show a significant difference between the two groups of our population (10).

Obesity is an important comorbidity associated with SAS and HF, but in our cohort, both groups show a similar level 2 BMI of obesity (11). Central events are more frequent in HF, but in our population, differences were not significant (12).

Cardiovascular disease patients show a high sleep-disordered breathing prevalence and poor outcome but only a systematic screening based on measures of respiration-related parameters (i.e., respiratory flow, blood oxygen saturation, etc.) allows a reliable assessment (13).

We observed that there are no significant differences between certain comorbidities in the group of patients with reduced EF and preserved EF (COPD, diabetes, dyslipidemia, coronary artery disease, arrhythmias, smoking status). However, a statistically significant higher number of patients presented with stroke in the group with preserved EF.

HF has been recognized as a risk factor for stroke (14). Left ventricular dysfunction, even mild (EF 41%–50%), was associated with an increased risk of ischemic stroke (15,16). Moreover, the risk of stroke was at least as great for patients with mild dysfunction (EF 41%–50%) as for patients with moderate dysfunction to severe dysfunction (EF ≤40%) (17,18). Our data regarding the prevalence of stroke in HFpEF are different from those of other trials. However, limited information is available about comorbidities and risk factors for incident HFpEF, and the fact that there is a lack of therapies that improve the prognosis of this condition reflects an incomplete understanding of its pathogenesis. More studies are needed to focus on HFpEF. SAS is associated with multiple comorbidities and may play a role in increasing the cardiovascular risk (19).

Significantly higher values of creatinine were found in the group with reduced EF. Patients with early chronic kidney disease (CKD) are more likely to die of cardiovascular disease than to progress to terminal stages of the disease, due to well-known risk factors (hypertension, diabetes and coronary artery disease) and novel factors (subclinical ischemia, arteriosclerosis, arterial stiffening, hemodynamic insults) (20,21,22).

CKD prevalence in a population of 7700 subjects from a large European Sleep Apnea Database was 8.7% or 6.1%, according to the Modification of Diet in Renal Disease or the Chronic Kidney Disease Epidemiology Collaboration equations. In SAS, CKD is largely predicted by comorbidities and anthropometric characteristics. In addition, severe nocturnal hypoxemia, even for only a small part of the night, may play an important role as a risk factor for kidney dysfunction (23).

In patients with SAS, the identification, diagnosis and treatment of sleep disorders is complicated by the overlapping presentation with CKD and other commonly comorbid conditions. In patients with CKD, sleep disorders are more prevalent, with an additional morbidity and mortality burden. The complex and dynamic relationship between sleep disorders and CKD remains relatively little investigated (24).

The cause of renal dysfunction is multifactorial, but reduced renal perfusion and venous congestion are prominent factors, which are probably mediated and modified by a multitude of cardiorenal connectors like activation of rennin–angiotensin–aldosterone system (RAAS) and SNS, endothelial dysfunction, inflammation and anemia. Through the progression of heart failure, which can be caused by (re)hospitalizations, patients enter a vicious circle of mutual organ dysfunction, resulting in end-stage renal disease, end-stage heart failure, or a combination of both (25).

In the studied population, the differences were significantly higher for HFrEF regarding aortic insufficiency and tricuspid insufficiency. In the first phases of chronic aortic insufficiency, LVEF is normal or even increased; patients may remain asymptomatic during this period. Through the progression of aortic insufficiency, EF starts to decrease. The increase in left ventricular systolic volume is a sensitive indicator of progressive myocardial dysfunction (26).

Patients with moderate or severe tricuspid insufficiency have a lower survival rate than those with mild tricuspid insufficiency, irrespective of pulmonary artery pressure or EF. Thus, tricuspid insufficiency should be considered as an additional risk factor for mortality (27).

In the studied population, even if EF was decreased, valvular dysfunction was mild and moderate. It remained unclear if valvular disease was the underlying cause of HF or it was a consequence of HF; thus, some studies demonstrated that EF decreased through the progression of valvular insufficiency.

If SAS is a truly established independent cardiometabolic risk factor and if SAS should be included in integrated cardiometabolic risk reduction management are questions still waiting for definitive answers (28).

Conclusions

Patients with SAS and HFpEF have been shown to be at a higher risk for stroke. CKD and aortic and tricuspid insufficiency are higher in the group with reduced EF compared to those with SAS associated with preserved EF.

These results may suggest pathogenic links between SAS comorbidities considering that many of the pathophysiological consequences of SAS (activation of RAAS and SNS, endothelial dysfunction, inflammation) are precursors for these comorbidities and the mortality is higher when this association is present.

Ethics approval and consent to participate are not applicable as this is a retrospective observational study.

The authors declare that they have no competing interests.

eISSN:
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Language:
English
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Volume Open
Journal Subjects:
Medicine, Clinical Medicine, other, Internal Medicine, Pneumology