European Journal of Cardiovascular Medicine

Obstructive sleep apnea (OSA) is the most commonly diagnosed sleep disorder.[1]It is a chronic condition that is characterized by repetitive upper airway obstructions resulting in intermittent hypoxia and sleep fragmentation caused by arousals[2]. Obstructive sleep apnea syndrome has been associated with an increased incidence of hypertension, stroke, and cardiovascular disease[3].

An AHI of equal to or greater than 5 events/h is commonly used to define OSA, with obstructive or mixed (rather than central) events comprising more than 50% of the total [5]. OSA is often classified as mild, moderate and severe according to the AHI. A common scheme is 5 to 15 (mild), 15 to 30 (moderate), >30 events/h (severe) [5]

Metabolic syndrome (MS) includes a cluster of metabolic abnormalities, with insulin resistance, hypertension, abdominal obesity, elevated triglycerides and blood glucose and reduced HDL cholesterol it was given name as “Syndrome X [1].It is associated with a high risk for the development of type 2 diabetes mellitus and cardiovascular disease [4]. Syndrome Z is defined as co-existence of OSA and metabolic syndrome.

DIAGNOSIS OF METABOLIC SYNDROME

According to new IDF criteria for a person to be defined as having the metabolic syndrome they must have Central obesity – defined as waist circumference greater than equal to 90cm for men and greater than equal to 80 cm for women (Indian population). Plus any two of the following four factors

1. Raised TG level greater than equal to 150mg/dl or specific treatment for this lipid abnormality.
2. Reduced HDL cholesterol <40mg/dl or specific treatment for this lipid abnormality.
3. Raised B.P systolic greater than equal to130 diastolic greater than equal to 85 or treatment for previously diagnosed hypertension.
4. Raised FBG greater than equal to 100mg/dl or previously diagnosed type 2 diabetes. 

Study Design and Duration

This was a Prospective analytical study conducted at the Department of Pulmonary Medicine, Maharajah Institute of Medical sciences, Vizianagaram. from December 2016 To August 2018.

Study Population and Sample Size

The study included 30 patients having metabolic syndrome with symptoms suggestive of obstructive sleep apnoea during the study period.

Inclusion Criteria

Patient having symptoms of OSA like excessive snoring day time sleepiness, headaches in morning, forgetfulness ,dry mouth on waking up. Patients with metabolic syndrome.

Exclusion Criteria

• Patient refusal
• Critically ill patients.
• Pregnant females.
• Patients below age of 18.
• Patient with organ dysfunction or malignancy.
• Patients with central sleep apnea.

Ethical Considerations

This study was approved by the Institutional Ethics Committee of      Maharajah Institute of Medical Sciences (Ref No: IEC/MIMS/2016/1376, dated 2/12/2016). Informed consent was obtained from all participants before enrollment into the study.

Methodology

As the study was to find out the prevalence of OSA in patients with metabolic syndrome, patients admitted for polysomnography to our hospital were evaluated. Patients were identified and was categorized according to inclusion and exclusion criteria. Polysomnography is considered as gold standard in diagnosing OSA .We conducted type 1 polysomnography to diagnose OSA in patients having metabolic syndrome.

Equipment: The study was conducted by the polysomnography machine “Rem logic (Res Med)” which was used to perform sleep studies in hospital under our supervision.

1. 21 channel Polysomnography [ Rem logic (Res Med)]
2. Measures of body habitus recorded by standard anthropometric methods.

PSG consisted of continuous polygraphic recording from surface leads for the following parameters.

PROCEDURE:

1. All patients attended Chest OPD with complaints of sleep disordered breathing (SDB)  like Snoring, excessive day time sleepiness, witnessed breathing pause, nocturnal choking, as well as patients referred from other departments for evaluation of SDB were taken up for further screening.
2. A. History given both by the patient and the bed partner, and clinical              examination of such patients were recorded as per a proforma given below.

1. Their Epworth Sleepiness Scores (ESS) was calculated. Based, on ESS, three groups were identified- those with mild sleepiness (ESS≤ 10), moderate sleepiness (ESS 11-16) and severe sleepiness (ESS >16).
2. Based on the BMI, subjects were divided into three groups, those with BMI ≤ 24.9 kg/m², >25Kg/m² to ≤ 30 Kg/m² and >30 Kg/m² (as per the WHO definition of obesity for Indian and the western population).
3. Neck circumference was measured at the superior border of the cricothyroid membrane with the subjects in the upright position.

E.Nocturia, a symptom, was used to mean that the patient was waking to pass urine more frequently than normal, ie more than once per night²⁰⁹.

1. History and Vital parameters are noted before and after PSG. The presence or absence of comorbidities and the treatment history recorded based on history and review of patient’s medical documents.
2. Chest X-ray, ECG, and baseline SpO₂ recordings were done for all patients.
3. All these patients were subjected to PSG and monitored whole night in the sleep lab.
4. Interpretation of PSG Data was scored according to the standard criteria. An abnormal breathing event during objectively measured sleep was defined according to the commonly used clinical criteria i.e. drop in the peak thermal sensor excursion by ≥ 90% of baseline, the duration of the event lasts at least 10sec (apnea) and the nasal pressure excursions drop by ≥30% of base line, duration of this drop occurs for a period lasting at least 10 sec with ≥ 4% desaturation from pre-event baseline (hypopnea). The average number of episodes of apnea and hypopnea per hour of sleep (the apnea-hypopnea index [AHI]) was calculated as the summary measurement of SDB. Arousals were identified according to established criteria. Respiratory effort related arousal (RERA) was defined as flattening in the airflow signal ≥ 10sec followed by an arousal and an abrupt reversal in flow to a round shape, that does not qualify as hypopnea.
5. Patients with AHI > 5 were taken up for further analysis.
6. ESS scores and AHI scores were recorded and tabulated with other findings in the clinical profile of patients.
7. Data was collected at the end of study will be analysed to compare the ESS scores, AHI scores, the various predisposing conditions for sleep disordered breathing

Image 1: Image showing patient with polysomnography connections.

Image 2: Image showing obstructive sleep apnea on polysomnography.

Statistical Analysis: All statistical analysis was done by using SPSS trial version-21 and in MS-Excel 2007. Qualitative variables were expressed as frequencies and percentages where as quantitative variables were expressed as mean and standard deviations. Student independent sample ‘t’ test was used for group comparisons. Chi-square test was used for examining the categorical data. For all statistical analysis p<0.05 is considered as statistically significant. 

After obtaining the informed consent from the patients, a total of 30 participants were enrolled in the study.

The study population included 20 male and 10 female patients. The gender ratio of the study population was 2:1.

Figure - Male constitute 66.6% and female constitute 33.3% of study population

The minimum, maximum, mean and stardard deviation of study population with respect to age, height, weight, body mass index, Epworth sleepiness scale, systolic blood pressure, diastolic blood pressure, fasting blood sugar, post prandial blood pressure, high density lipoprotein, low density lipoprotein, triglycerides, apneic hyapneic index are shown in the following table

Table 1: Table showing the minimum, maximum, mean, standard deviation of quantitative parameters of the study population.

Image 3: Pie Diagram showing the incidence of OSA in people with metabolic syndrome.

Table 2 : Table showing OSA was found in 63.3 % of study population.

The prevalence of OSA in patients with metabolic syndrome was 63.3%  .

Image 4: Bar Diagram depicting OSA among male and female study population.

Gender prevalence was male(70%), female(50%).

Image 5– Histogram showing grading of study population in to normal, mild, moderate and severe OSA based on AHI

Severe OSA was found in 40%, Moderate OSA was found in 13.3%, mild OSA was found in 10% of study population.

In the present study, the prevalence of OSA in patients with metabolic syndrome was 63.3%  . Gender prevalence was male(70%), female(50%). Severe OSA was found in 40%, Moderate OSA was found in 13.3%, mild OSA was found in 10%.

Our study was comparable with studies done by , Dubey AP et al [6] , Chin et al [7] ,Coughlin et al [8]

In study performed by Dubey AP et al [6],out of 50 patients with metabolic syndrome, 3 were normal, 5 patients had mild OSA, 20 patients were found to have moderate AHI (AHI 15-30) whereas 22 were found to have severe AHI.

Chin et al [7] performed a Retrospective analysis on the association between metabolic syndrome and severity of OSA. Severe OSA was 7.8 times as likely to be present in subjects with metabolic syndrome.

In a study performed by Coughlin et al [8] Metabolic syndrome was 9.1 (95% confidence interval 2.6, 31.2: p<0.05) times more likely to be present in subjects with OSA.

LIMITATIONS - This study had the limitation of not including the control group. We also did not evaluate the ongoing medications/ treatment in these patients. The selection bias could be present due to hospital based patient selection.Our study has small sample size of 30. It was because of lack of awareness among rural people about Sleep Disorderd Breathing.

MERITS- This study had a merit of  evaluating  OSA in people with metabolic syndrome  in north eastern district of Andhrapradesh as there were no studies till now and  this  study has  increased awareness about syndrome Z ( OSA plus syndrome X ) .

Overall, polysomnography is an effective tool for diagnosis of  sleep disordered breathing (SDP) and should be carried out in patients with metabolic syndrome and in patients with symptoms suggestive of SDBs and also in patients having other co morbidities which are known to be associated with SDB.

The present study showed a high prevalence of OSA in people with Metabolic Syndrome (63.3%). So this study proved the necessity of evaluating all patients with metabolic syndrome for OSA with polysomnography.

This is possible if awareness for SDBs is increased among general population and physicians, including its effects on individuals’ physical, mental and social health and also needs to be emphasized that it is amenable to cure.

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