European Journal of Cardiovascular Medicine

The term dyslipidemia is used to denote the presence of any of the following abnormalities, occurring alone or in combination-increased concentration of TC or LDL-Cor serum TG or a decreased concentration of HDL-C. [1] Although it is difficult to compare observations from different studies due to different cut-offs taken to define dyslipidemia, different sampling procedures and different methodologies used for estimations of lipoproteins, dyslipidemia appears to be widely prevalent in India. [2]

The prevalence of hypercholesterolemia (TC 200 mg/dl) alone, as reported in numerous studies across India, has varied from about 20% to 35%. However, what is more important is the pattern of dyslipidemia. [3] When compared with the western populations, Indians and migrant Asian Indians tend to have higher triglyceride levels and lower HDL-C levels. [4] In contrast, mean serum cholesterol levels among Asian Indians have been shown to be similar to that of the general population in the US and lower than the levels in the UK. [5] The low HDL-C levels and hypertriglyceridemia are metabolically interlinked and their combination has been termed as “atherogenic

dyslipidemia”, which is also characterized by increased levels of small-dense LDL particles with relatively normal total LDL-C and insulin resistance. [6] Atherogenic dyslipidemia is particularly common in South Asians and has been shown to have a strong association with type 2 diabetes mellitus, metabolic syndrome and CVD. [7]

Lipoprotein(a) [Lp(a)] has been known as an independent risk factor that cause atherosclerotic cardiovascular disease. Lp(a) contains apoB100, which is the protein component of lipoprotein having low density, associated with apolipoprotein (a. It has around 80% similarity with plasminogen. [8] The concentration and size of Lp(a) are mostly identified by apo(a) polymorphism genetically and remain stable all through life. The biological function of Lp(a) is still not known, but it is not neceassary for the mammals, because it is not present in monkeys of new world. But the Lp(a) structure reveals an associative function between coagulation and lipid  system. [9]

Lp(a) shows interaction with endothelial cells because of bond with the plasminogen receptor, thus changing the fibrinolytic system. Additionally, Lp(a) shows migration via endothelial cells into the vessel wall and is able to bind with macrophages and is seen in atherosclerotic plaques. [10] For atherosclerosis one of the main targets of risk factors is the endothelium. Changes in integrity of endothelium happen in the existence of risk factors for coronary artery disease. This is the main contributor to the pathogenesis of myocardial ischemia, leading to the coronary artery disease. [11] Endothelial dysfunction is a premature characteristic of atherogenesis. Disturbed endothelium-based coronary vasomotor reactions signify a significant marker of early damage to vascularity, being influenced by risk factors for causing coronary artery disease. [12]

Particularly hypercholesterolemia, the raised low density lipoprotein (LDL) levels are linked with a endothelium-mediated vasodilator capability of coronary microcirculation and epicardial arteries. [13]

A cross-sectional study was conducted among patients from Tertiary Care Teaching Centre. Two hundred students were invited to participate in a health survey. Two Hundred (n = 200) patients were involved. The attendance rate was higher in men than in women (131 men, 69 women).

The following eligibility criteria were used for inclusion in the study: consent of the participant for participation in the study, an age of ≥18 years, and health status allowing for the examinations to be carried out.

The body weight and height of the participants were measured using the standard protocol and equipment that was calibrated before and during the data collection period. Body height was measured upright, barefoot, to the nearest 0.1 cm using a portable stadiometer. Body mass was assessed with an accuracy of 0.01 kg using a body composition analyzer. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared (kg/m2).

BP was measured using the current protocol guidelines for BP measurement after the participant had rested for 10 min. Three measurements were taken with an automated oscillometric sphygmomanometer, along with a set of cuffs of various widths. Hypertension was defined according to the recent Guideline for High Blood Pressure in adults, as systolic blood pressure (SBP) ≥ 140 mmHg and/or diastolic blood pressure (DBP) ≥ 90 mmHg, or treatment for hypertension.

Blood lipids were analyzed from a fasting blood sample received by finger prick. Participants were advised to fast for 10–12 h before the test. Blood was analyzed immediately using a Cholestech LDX Analyzer (Cholestech Corporation). The results obtained using this device were well correlated with the measures obtained by other means. The device was calibrated each day prior to use. TC, HDL, LDL, and TG levels were determined. To define an abnormal level of lipid/lipoproteins, we used cut-off points suggested in the 2020 Guidelines of the Polish Society of Laboratory Diagnostics and the Polish Lipid Association on Laboratory Diagnostics of lipid metabolism disorders: TC (≥190 mg/dL), HDL (≤45 mg/dL in women; ≤40 mg/dL in men), LDL (≥115 mg/dL), and TG (≥150 mg/dL).

Statistical Analysis

Statistical analysis was performed using SPSS 25 software (IBM). Statistics are presented as mean (SD) and n (%).The prevalence of blood pressure status and abnormal blood lipid values was calculated using the independence test χ2. The level of statistical significance was adopted at p < 0.05.

Table 1.  Gender distribution of patients

We observed gender distribution in our studied population as 65% as male and 35% as female population. In our study, we observed mean age as 37.23 years. (Table 1 and fig. 1)

Table 2.  Tabulation of PTCA

Table 3.  HTN ptca1, r col exact chi2

Fisher's exact test, p value= 0.315

There was no significant correlation of PTCA among non-hypertensive and hypertensive patients in this study seen.

Table 4. DYSDM ptca1, r col exact chi2

Fisher's exact Test, p value = 0.003

There was significant correlation of PTCA among dyslipidemia with diabetes and non dyslipidemia with non diabetic patients in this study seen.

Table 5. Thyriod ptca1, r col exact chi2

Fisher's exact test, p value = 0.53

There was no significant correlation of PTCA among hypothyroid and euthyroid patients in this study seen.

Table 6. Endothelial dysfunction ptca1, r col exact chi2

Fisher's exact test, p value = < 0.0001

There was significant correlation of PTCA among patients with and without endothelial dysfunction in this study seen.

Table 7. ECG Changes ptca1, r col exact chi2

Fisher's exact Test, p value = < 0.0001

There was significant correlation of PTCA among patients with and without significant ECG changes in this study seen.

Table 8. CVS findings ptca1, r col exact chi2

Fisher's exact Test, p value= < 0.0001

There was significant correlation of PTCA among patients with and without significant cardiovascular findings in this study seen.

Dyslipidaemia alone or along with associated comorbidities, mainly diabetes and hypertension, poses a significant risk of premature atherosclerotic CVDs and therefore early diagnosis and appropriate management have become a fundamental step in alleviating morbidity and mortality. Current evidence highlights the grave status quo of the alarming rise in the prevalence of lipid abnormalities in the Indian population aged ≤45 years. [14]

There was no significant correlation of significant coronary angiographic findings or PTCA among patients in terms of gender as causative factor in this study. This pattern was unlike other population-based studies worldwide that show this pattern, although admission and mortality rates due to myocardial infarction in hospital-based studies are higher in males. [15]

A systematic review of studies from India also showed little increase in prevalence rates of ECG-diagnosed CHD among men while finding significant increases in women. [16] A study in urban Delhi, which followed the same methodology as the current study from Vellore, also showed increase in CHD prevalence in women but not in men, [17] with higher rates for CHD in urban Delhi as compared to urban Vellore, probably reflecting the differences in socio-economic status in the two populations.

Family history was an independent risk factor for CHD in our study, as has been seen in the INTERHEART study. [18] While traditionally women have been considered less likely to develop heart disease in the pre-menopausal age, with alarming rise in body mass indices as seen in this population over the last 20 years, [19] the advantage of being a premenopausal woman seems to be disappearing. The rates of CHD in this population were higher in women compared to men, irrespective of menopause, although previously known disease was least among pre-menopausal women. [20]

As the rates of both ECG abnormalities as well as symptoms were higher in females, it is unlikely that these findings are merely due to different perceptions of heart disease and its symptoms between the genders, although such factors could explain some of the differences in symptom rate between populations. [21] Awareness regarding chest pain, chest pain as part of somatization, and muscle weakness due to vitamin D deficiency could be other reasons why Indian women report chest pain on exertion more than males, which could be explored in future research. [22] Occurrence of CHD in females at a later age than males may be one reason why women are less likely to be hospitalized for CHD, as it may be causing deaths among elderly women, before hospitalization. [23]

There was significant correlation of PTCA among diabetic patients (higher HBA1C and blood sugars) in this study seen. There was significant correlation of PTCA among patients with and without adequate sleep as causative factor in this study.

Overall observations indicate high prevalence of comorbidities, hypertriglyceridemia, high LDL-C, low HDL-C and endothelial dysfunction along with significant prevalence of statin resistance, rising incidence of CAD in young Indian cohort; family history of diabetes mellitus, dyslipidemia and HbA1c ≥6.5% were the predominant risk factors attributable to dyslipidaemia. Hence, accurate assessment of lipid parameters as a part of global risk assessment among the young Indian adults will aid in alleviating the long-term risk of premature atherosclerotic CVD and associated morbidity and mortality.

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