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\begin{document}

\title{Obstructive Sleep Apnea Syndrome does not increase the cardiovascular
risk in a na\selectlanguage{ngerman}ïve population of southern Italy\selectlanguage{english}}



\author[1]{Pierluigi Carratù}%
\author[2]{Agostino di Ciaula}%
\author[3]{Silvano Dragonieri}%
\author[3]{Teresa Ranieri}%
\author[4]{Marco Ciccone}%
\author[2]{Piero Portincasa}%
\author[3]{Onofrio Resta}%
\affil[1]{Division of Internal Medicine "A. Murri" }%
\affil[2]{Division of Internal Medicine "A. Murri" , Department of Biomedical Sciences and Human Oncology, University of Bari ‘”Aldo Moro’’, Bari, Italy Piazza G. Cesare 12, Bari, Italy Bari, IT 70124}%
\affil[3]{Institute of Respiratory Diseases, University of Medicine, Bari, Italy}%
\affil[4]{Institute of Cardiovascular Diseases, University of Medicine, Bari, Italy}%


\vspace{-1em}



  
  \date{May 19, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Background Obstructive Sleep Apnea (OSA) is a worldwide increasing
syndrome, which, by promoting endothelial dysfunction, contributes to
extend the cardiovascular risk. We evaluated the cardiovascular risk in
a group of OSA patients. Methods A total of 185 OSA subjects (19 normal
weight, 57 overweight, 109 obeses), seen at the Ambulatory of Sleep
Disorders, during one year, entered the study. We assessed
anthropometric features, polysomnographic findings, cardiovascular risk
factors, smoking habit, Pulmonary Function Test, Arterial Blood Gas
Analysis, Epworth Questionnaire, and Charlson Co-morbidities Index
(CCI). Subjects were divided into three groups, according to their BMI:
individuals with BMI [?]30 Kg/m2 (Group 1 n=109, mean age 61 \selectlanguage{ngerman}± 1; 74.3 \%
males), individuals with BMI ranging from 25.0 to 29.9 Kg/m2 defined as
overweight subjects (Group 2 n=57, mean age 58.8 ± 1.4; 77\% males) and
subjects with a BMI ranging from 18.5 to 24.9 Kg/m2 defined normal
weight subjects (Group 3 n=19, mean age 54.2 ± 2.3; 64,2\% males).
Results In the whole population, the percentage cardiovascular risk was
weakly related with BMI (r=0.33; P\textless{}0.001), but not with AHI.
The cardiovascular risk was strictly related to the obesity
(p\textless{}0.00002), while the Epworth Questionnaire score and the
Charlson Co-morbidity Index were respectively statistically higher in
the group of obese individuals (p=0.006, p=0.00002) than in the other 2
Groups. When AHI values were stratified in tertiles, the percentage
cardiovascular risk did not vary with increasing AHI values (Figure 2).
Conclusions Further studies are required to investigate the pivotal role
of inflammation due to obesity, and underlying increased cardiovascular
risk in OSA patients.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


\selectlanguage{ngerman}\textbf{Obstructive Sleep Apnea Syndrome does not increase the
cardiovascular risk in a naïve population of southern Italy}

\textbf{Pierluigi Carratù, Agostino Di Ciaula, Silvano Dragonieri*,
Teresa Ranieri*, Marco Matteo Ciccone°, Piero Portincasa, Onofrio
Resta*.}

\textbf{Division of Internal Medicine, Clinica Medica ``A. Murri'',
Department of Biomedical Sciences and Human Oncology, University of Bari
`''Aldo Moro'', Bari, Italy}

\textbf{*Institute of Respiratory Disease, University of Medicine ``Aldo
Moro'', Bari, Italy}

\textbf{°Institute of Cardiovascular Disease, University of Medicine,
``Aldo Moro'', Bari, Italy}

Corresponding Author: Pierluigi Carratù, Division of Internal Medicine,
Clinica Medica ``A. Murri'', Department of Biomedical Sciences and Human
Oncology, University of Bari `''Aldo Moro'', Bari, Italy. Piazza G.
Cesare 12, 70122, Bari, Italy.

e-mail:\emph{pierluigi.carratu@uniba.it}/ Fax number 080 5592907.

Abstract

\textbf{Background} Obstructive Sleep Apnea (OSA) is a worldwide
increasing syndrome, which, by promoting endothelial dysfunction,
contributes to extend the cardiovascular risk. We evaluated the
cardiovascular risk in a group of OSA patients.

\textbf{Methods} A total of 185 OSA subjects (19 normal weight, 57
overweight, 109 obeses), seen at the Ambulatory of Sleep Disorders,
during one year, entered the study. We assessed anthropometric features,
polysomnographic findings, cardiovascular risk factors, smoking habit,
Pulmonary Function Test, Arterial Blood Gas Analysis, Epworth
Questionnaire, and Charlson Co-morbidities Index (CCI). Subjects were
divided into three groups, according to their BMI: individuals with BMI
\selectlanguage{english}[?]30 Kg/m\textsuperscript{2} (Group 1 n=109, mean age 61 +- 1; 74.3 \%
males), individuals with BMI ranging from 25.0 to 29.9
Kg/m\textsuperscript{2} defined as overweight subjects (Group 2 n=57,
mean age 58.8 +- 1.4; 77\% males) and subjects with a BMI ranging from
18.5 to 24.9 Kg/m\textsuperscript{2} defined normal weight subjects
(Group 3 n=19, mean age 54.2 +- 2.3; 64,2\% males).

\textbf{Results} In the whole population, the percentage cardiovascular
risk was weakly related with BMI (r=0.33; P\textless{}0.001), but not
with AHI. The cardiovascular risk was strictly related to the obesity
(p\textless{}0.00002), while the Epworth Questionnaire score and the
Charlson Co-morbidity Index were respectively statistically higher in
the group of obese individuals (p=0.006, p=0.00002) than in the other 2
Groups. When AHI values were stratified in tertiles, the percentage
cardiovascular risk did not vary with increasing AHI values (Figure 2).

\textbf{Conclusions} Further studies are required to investigate the
pivotal role of inflammation due to obesity, and underlying increased
cardiovascular risk in OSA patients.

Keywords: Obstructive Sleep Apnea, Obesity, BMI, Cardiovascular Risk,
Polysomnography, Continuous Positive Airway Pressure.

Introduction

The cardiovascular risk is defined by WHO/ISH by risk prediction charts,
which indicate 10-year risk of a fatal or nonfatal major cardiovascular
event (myocardial infarction or stroke), according to age, sex, blood
pressure, smoking status, total and HDL blood cholesterol, presence or
absence of diabetes mellitus, and anti-hypertensive treatment (1)

Obstructive Sleep Apnea (OSA) is a worldwide increasing syndrome and is
a persistent long term risk factor for several cardio-pulmonary diseases
(2). In particular, in patients with OSA, chronic upper airways
inflammation constantly promotes a systemic endothelial dysfunction
(3,4) worsens the cardio-pulmonary activity, thus, affecting the left
and the right heart performance (5) increases risk of cardiovascular
events, over time (6).

Obesity plays a well established pivotal role in the evolution of the
cardiovascular risk in patients with OSA (7). Indeed, in obese
individuals, the eccentric ventricular hypertrophy and the diastolic
heart failure are responsible for developing cardio-myopathy, a
well-recognized complication in severe obese patients (8). The augmented
left ventricular filling pressure, transmitted into the pulmonary venous
system, improves pulmonary venous pressures leading to increased
pulmonary vascular resistance (9). Obesity is also linked with elevated
serum hs-CRP levels in patients with sleep-disordered breathing (10),
further contributing to chronic systemic inflammation. Thus, the complex
interplays among OSA, insulin resistance, hypercholesterolemia, obesity,
chronic systemic inflammation and elevated left ventricular filling is
responsible for endothelial dysfunction, with Pulmonary Hypertension
(PH) and finally increasing cardiovascular risk in affected subjects
(11,12,13). However, besides the combined role of these factors, it is
still under debate if the severity of OSA can act per se, as an
independent factor in determining the extent of the cardiovascular risk
in obese patients (14).

In the present study, we depicted the cardiovascular risk of a
consecutive population of OSA patients enrolled at the Sleep Ambulatory,
and studied for anthropometric features, cardiovascular risk, and
Polysomnographic findings.

Subjects and Methods

\emph{Patients}

OSA patients entering, during the year 2016, the Ambulatory of Sleep
Disorders of the Institute of Respiratory Diseases of the University of
Bari were retrospectively evaluated. In enrolled subjects, we recorded
anthropometric features, smoking habits, Pulmonary Function Test,
polysomnographic findings, data from Arterial Blood Gas Analysis.

Daytime sleepiness was measured by the Epworth Questionnaire, and the
death risk linked with comorbidities was assessed by the Charlson
Co-morbidities Index (CCI). The 10-year risk of heart disease or stroke
was calculated using the ASCVD algorithm (15).

We measured body weight (kg), height (m) and calculated BMI, i.e.,
Quetelet's index as kilograms divided by meter squared (kg/m2). BMI
ranging from 18.5 to 24.9 kg/m2 defined normal weight subjects. A BMI
ranging from 25.0 to 29.9 kg/m2 defined overweight subjects, while a BMI
\selectlanguage{english}[?]30 kg/m2 defined patients with obesity.

\emph{Pulmonary Function Test}

Pulmonary function tests were performed by spirometry (PK Morgan Ltd;
Gillingham, UK). The equipment was calibrated daily using a 3-l syringe,
and the analysis was performed in accordance to the guidelines of the
American Thoracic Society (16). The best of three reproducible values
was expressed as a percentage of the predicted normal value.

\emph{Sleep Study}

In the sleep laboratory of the Institutes of Respiratory Diseases of the
University of Bari, all patients were evaluated for sleep disordered
breathing during one night. They were monitored continuously for about 8
h using a portable cardiorespiratory monitoring (POLYMESAM(r), MAP,
Martinsried, Germany). The POLYMESAM(r) (PM) device consists of a
recorder, to which multiple sensors are linked for the detection of the
following signals: oxy-hemoglobin saturation (by a finger sensor), heart
rate (derived from three electrocardiogram (ECG) electrodes placed on
the chest), snoring sound (by a microphone placed on the thyroid
cartilage), body posture oro-nasal airflow (by a threefold thermocouple
sensor for both nostrils and mouth), and thoracic and abdominal
movements (by stretch belts). Apnea was identified if the airflow was
absent or nearly absent for at least 10 s. Hypopnea, was considered when
there was a decrease of airflow for at least 10 seconds in respirations,
a 30-percent reduction in ventilation, and a decrease in oxygen
saturation.

Statistics

Data are presented as mean +- standard error (SEM) or as percentages.
One-way analysis of variance (ANOVA) assessed inter-group differences.
Differences between two groups were tested by Student's t-test for
unpaired data. The Chi-square test was used to compare proportions. The
Pearson correlation coefficient was used for correlations. Results were
considered significant at the 5\% critical level (P\textless{}0.05).
Statistical analyses were performed with NCSS10 Statistical Software
(NCSS, LLC. Kaysville, Utah, USA).

Study Approval

Since the study was retrospective, the patients did not sign any
informed consent, while the Local Ethic Committee approved the study
number 1089, July the31\textsuperscript{st} 2009, with note prot n.
24961/DS 03/26/2009, and approved the study number prot. N. 44696/DS
06-03-2009 n.527/DG/2004modified by the protocol n. 828/DG/2007.

Table 1\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
& Normal weight & Overweight & Obese & P\tabularnewline
\midrule
\endhead
n. & 19 & 57 & 109 &\tabularnewline
Males & 12 & 44 & 81 &\tabularnewline
Age (year) & 54.2\selectlanguage{ngerman}±2.3 & 58.8\selectlanguage{ngerman}±1.4 & 61\selectlanguage{ngerman}±1.0* & 0.02\tabularnewline
BMI (Kg/m2) & 23.1\selectlanguage{ngerman}±1.0 & 27.6\selectlanguage{ngerman}±0.6* & 35.9\selectlanguage{ngerman}±0.4*° & 0.0000\tabularnewline
Smokers (\%) & 15.8\% & 15.8\% & 74.3\% & \textless{}0.05\tabularnewline
Systemic Hypertension (\%) & 31.6\% & 35\% & 59.6\% &
\textless{}0.05\tabularnewline
Type 2 Diabetes (\%) & 5.3\% & 3.5\% & 27.5\% &
\textless{}0.05\tabularnewline
Total cholesterol (mg/dL) & 200.6\selectlanguage{ngerman}±3.0 & 202.4\selectlanguage{ngerman}±1.7 & 218.1\selectlanguage{ngerman}±1.2*° &
0.00001\tabularnewline
HDL cholesterol (mg/dL) & 61.3\selectlanguage{ngerman}±1.8 & 60.0\selectlanguage{ngerman}±1.0 & 53.9\selectlanguage{ngerman}±0.8*° &
0.0001\tabularnewline
AHI & 34.8\selectlanguage{ngerman}±3.1 & 35.5\selectlanguage{ngerman}±1.8 & 43.3\selectlanguage{ngerman}±1.3*° & 0.0006\tabularnewline
Cardiovascular risk (\%) & 10.2\selectlanguage{ngerman}±3.1 & 13.7\selectlanguage{ngerman}±1.8 & 22.3\selectlanguage{ngerman}±1.3*° &
0.00002\tabularnewline
Epworth score & 8.3\selectlanguage{ngerman}±3.7 & 14,1\selectlanguage{ngerman}±5.6 & 18.6\selectlanguage{ngerman}±5.2 & 0.006\tabularnewline
Charlson Co-morbidities Index & 2.4\selectlanguage{ngerman}±1.2 & 3.5\selectlanguage{ngerman}±1.7 & 4.8\selectlanguage{ngerman}±2.0 &
0.0002\tabularnewline
\bottomrule
\end{longtable}

*P\textless{}0.05 vs normal weight; \selectlanguage{ngerman}°P\textless{}0.05 vs overweight

RESULTS

A total of 185 OSA subjects (19 normal weight, 57 overweight, 109,
obese) entered the study. Anthropometric data and sleep study from
normal weight, overweight and obese subjects are depicted in Table1.

AHI values were higher in obese (43.3±1.3) than in lean (34.8±3.1) and
overweight subjects (35.5±1.8, P\textless{}0.01 ANOVA). Overall, a
direct relationship was evident between AHI and BMI (Figure1). Smokers
were higher in obese group (p\textless{}0.05); Systemic Hypertension was
statistically more significant among obese than in leans and overweight
patients (p\textless{}0.005). Type 2 diabetes was more represented among
obese patients (p\textless{}0.05). Blood total and HDL cholesterol were,
respectively, statistically significant higher and lower in obese
patients (p\textless{}0.00001; p\textless{}0.0001).

The cardiovascular risk was strictly related to the obesity
(p\textless{}0.00002), while the Epworth Questionnaire score and the
Charlson Co-morbidity Index were respectively statistically higher in
the group of obese individuals (p=0.006, p=0.00002) than in the other 2
Groups.

In the whole population, the percentage cardiovascular risk was weakly
related with BMI (r=0.33; P\textless{}0.001), but not with AHI.

Figure 1 shows the percentage of cardiovascular risk in the whole
population which was weakly related with BMI (r=0.33;
P\textless{}0.001), but not with AHI.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

When AHI values were stratified in tertiles, the percentage
cardiovascular risk did not vary with increasing AHI values
(\textbf{Figure2} ).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Discussion

Obstructive sleep apnoea (OSA) consists of repeated episodes of
extrathoracic upper airway obstruction associated with intra-arterial
hypoxaemia and hypercapnia (17). OSA, as a chronic condition is also
responsible for endothelial dysfunction, with early atherosclerosis
plaque evidence, and rapid increase of cardiovascular risk (6). Since,
even very recently, several studies have pointed out the role of the
degree of OSA, as factor likely responsible for increasing
cardiovascular risk (18), on the other hand, by the contrast, recent
evidences, derived by the results of an observational 1 year study, did
not establish any correlation between severe obstructive sleep apnea
syndrome and increased cardiovascular risk, as well as augmented
cardiovascular co-morbidities (19). This debate has involved, over time,
several investigators, who hypothesized both possible scenarios. Thus,
it remains under discussion the primary role of OSA for developing
increased cardiovascular risk in these subjects (20).

A validate assessment established that the metabolic syndrome commonly
coexist with OSA, and obesity is perhaps the strongest predictor of OSA
with 40--60\% of obese subjects suffering from sleep disorders breathing
(21). The burden of obesity is worrisome; the obesity prevalence is
globally increasing, affecting 10 to 25 \% of the world population and
is associated with a wide range of abnormalities, including elevated
systemic as well as elevated pulmonary artery pressures (22), both
sustained by systemic inflammation (7,10). Furthermore, obesity is
characterized by increased production and secretion of a wide range of
inflammatory molecules, including TNF-alpha and interleukin-6, which
have both, local effects on adipose tissue physiology, and systemic
effects on other organs, such as the cardiovascular system (12). Thus,
contributing to activate various inflammatory cells, such as lymphocytes
and monocytes, leading to over-expression of pro-inflammatory mediators,
that may establish irreversible endothelial dysfunction. The latter
observation has been recently demonstrated in a rabbit model (23).

In the present study, we found In the whole OSA population, the
percentage of cardiovascular risk was weakly related with BMI (r=0.33;
P\textless{}0.001) but not with AHI.

AHI values were higher in obese (43.3\selectlanguage{ngerman}±1.3) than in lean (34.8±3.1) and
overweight subjects (35.5±1.8, P\textless{}0.01 ANOVA). Overall, a
direct relationship was evident between AHI and BMI. When AHI values
were stratified in tertiles, the percentage cardiovascular risk did not
vary with increasing AHI values.

Then, we assumed that the degree of OSA per se does not significantly
increase the cardiovascular risk, while the coexistence with a higher
BMI, might be likely responsible for the worsen of the prognosis.

In two recent studies (24,~25), endothelial peripheral dysfunction in
OSA patients has been significantly found in mild OSA and in minimally
symptomatic OSA. The endothelial dysfunction decreased by 3 months of
C-PAP treatment. Indeed, in our study, we demonstrated that moderate or
severe OSA patients show a progressive brachial endothelial dysfunction,
established by flow-mediated dilation (FMD) assay. The most evident
finding was the significant reversibility of FMD in the group of
patients treated with C-PAP therapy, for at least 3~months (24).

In addition, OSA-associated chronic intermittent hypoxia (CIH), in
obesity, may complicate adipose tissue hypoxia with over-production of
adipose tissue inflammation, by increasing macrophage infiltration and
activating redox-sensitive transcription factors, as well as, ER stress
signaling proteins (26). In a very recent study, it has been evaluated
the effect of OSA and C-PAP on changes in adipose tissue
inflammatory/hypoxia markers, there assessed by testing mRNA levels of
genes related to macrophage infiltration, hypoxia, and ER stress (27).
In this investigation, authors performed abdominal subcutaneous adipose
tissue biopsies from OSA and non-OSA obese (BMI \textgreater{} 35)
individuals, at baseline and after 24 weeks (T1) of weight-loss
intervention plus continuous positive airway pressure (C-PAP), or
weight-loss intervention alone, respectively. In obese individuals with
OSA, the reduction of CIH, by a correct C-PAP therapy, associated with a
weight-loss intervention strategy, decreased mRNA expression of markers
related to tissue hypoxia, reduced plasma levels of some
pro-inflammatory cytokines and growth factors, ER stress, inflammation,
and, finally, macrophage infiltration (27),

The endothelial, as well as, the adipose tissue dysfunction, with the
consequent increased cardiovascular risk, are an early phenomenon in OSA
patients, and, according to our results, show-up more severe in subjects
with a BMI higher than 30, while did not appear statistically
significant as compared to the degree of OSA. Thus, the current study
demonstrates that newly diagnosed subjects with OSA are already at risk
for cardiovascular events, and patients with higher levels of BMI, as
well as with higher levels of AHI, experience also the presence of more
elevated number of co-morbidities, as seen by the results of Charlson
Co-morbidities Index (Table 1). In order to avoid this condition, OSA
should be diagnosed as soon as possible, in patients with elevated BMI,
who likely improve their endothelial dysfunction, and subsequently their
cardiovascular risk with C-PAP therapy. This treatment has been shown to
significantly decrease the cardiovascular risk and the development of
several co-morbidities, often responsible for fatal events (24).

This study has several limitations. First, the newly diagnosed
population of OSA was evaluated retrospectively. It is unknown whether
these subjects had a benefit or not by using C-PAP, in terms of
cardiovascular risk, as compared to them who refused or were intolerant.
Second, smoking habit was highly in obese patients, which could play a
significative role for increasing the cardiovascular risk. Third, the
weak association between BMI and AHI and the lack of correlation between
degree of OSA and increased cardiovascular risk was not well
established.

In conclusion, further studies must investigate the pivotal role of
systemic inflammation due to obesity, which appears to be able to
provoke increased cardiovascular risk and augmented co-morbidities, in
OSA patients.

\textbf{Compliance with Ethical Standards: This study received no
funding.}

\textbf{Pierluigi Carratù declares that he has no conflict of interest}

\textbf{Agostino Di Ciaula declares that he has no conflict of interest}

\textbf{Silvano Dragonieri declares that he has no conflict of interest}

\textbf{Teresa Ranieri declares that she has no conflict of interest}

\textbf{Marco Matteo Ciccone declares that he has no conflict of
interest}

\textbf{Piero Portincasa declares that he has no conflict of interest}

\textbf{Onofrio Resta declares that he has no conflict of interest}

\textbf{Ethical Approval: All procedures performed in the study
involving human participants were in accordance with the ethical
standards of the institutional and/or national research committee with
the 1964 Helsinki declaration, and its later amendments or comparable
ethical standards.}

\textbf{Informed consent was obtained from all individuals participants
included in the study.}

\textbf{Authors' contribution}

\textbf{Pierluigi Carratù conceived the study, made data interpretation
and wrote the manuscript.}

\textbf{Agostino Di Ciaula edited the manuscript, made statistical
analysis, and approved the final revision of the manuscript.}

\textbf{Silvano Dragonieri designed the study, approved the final form
of the manuscript.}

\textbf{Teresa Ranieri collected data, approved the final form of the
manuscript.}

\textbf{Marco Matteo Ciccone participated to the study and approved the
final revision of the manuscript.}

\textbf{Piero Portincasa participated to the study design, edited the
manuscript, approved the final form of the manuscript.}

\textbf{Onofrio Resta participated to the study, approved the final
revision of the manuscript.}

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