COMPARATIVE STUDY OF LIPID PROFILE IN PATIENTS OF NON-DIABETIC CHRONIC KIDNEY DISEASE IN RELATION TO ITS SEVERITY

Results: Out of 262 patients, 64.50% (169) were male and 35.50% (93) were females with M: F of 1.8:1. The age range was from 20 to 95. The average age of the patients in the study was 56.66+12.22 y. 45.04 % (118) of the patients were between 46 and 60 y of age. 68.70% of the patients had dyslipidemia. The comparison between lipid profiles of cases and controls showed a significant increase in total cholesterol, triglyceride, LDL and decrease in HDL.


INTRODUCTION
Chronic kidney disease (CKD) encompasses a spectrum of different pathophysiologic processes associated with abnormal kidney function and a progressive decline in glomerular filtration rate (GFR) [1]. CKD is a clinical syndrome due to irreversible kidney dysfunction leading to excretory, metabolic and synthetic failure culminating into the accumulation of non-protein nitrogenous substances and presenting with various clinical manifestations [2].
Chronic Kidney Disease (CKD) is a silent epidemic of the 21st century. Its occurrence is universal, not confined to the developed countries only. Globally, CKD is the 12th cause of death and the 17th cause of disability, respectively [3]. Estimated from population data, about 6% of the adult populations in the US have CKD stage 1 and 2, and 4.5% have CKD stage 3 and 4 [1].
It has been estimated that the age-adjusted incidence rate of End-Stage Renal Disease (ESRD) in India is around 229 per million population1, and more than one lakh new patients enter renal replacement programs annually in India [4]. It is estimated that the number of cases of kidney failure will increase disproportionately in developing countries, such as China and India, where the number of elderly people is increasing [5]. "Screening and Early Evaluation of Kidney Disease" (SEEK), a community-based voluntary health screening program started in India in 2006 with tests serum creatinine and urine analysis, reported a very high prevalence of 17.4% of CKD using an abbreviated modified diet in renal disease (MDRD) formula, a glomerular filtration (GFR) estimation formula [3]. As per the database of CKD registry of India, the yearly incidence of ESRD in India is approximately 150-200 pmp and DM is an important cause of CKD in approximately 30-40% of the patients [6]. The prevalence of ESRD and patients on RRT has increased over the last two decades [7].
It is well acknowledged that cardiovascular disease (CVD) is a major cause of morbidity and mortality among patients with CKD [1,8]. Major outcomes of CKD include the progression of CKD to end-stage renal disease with increased risk for development of cardiovascular disease [9]. Most of the patients with CKD die from cardiovascular system complications before ever reaching Stage 5 CKD [1].
Even mild chronic renal dysfunction contributes actively to the development of CVD, so the American Heart Association has recommended that these patients should be classified in the highest risk group for developing cardiovascular events.
Patients with CKD are subjected to accelerated atherosclerosis leading to increased cardiovascular complications. Patients with CKD have a reduction in the activity of lipoprotein lipase and hepatic triglyceride lipase. This interferes with the uptake of triglyceriderich, apolipoprotein B containing lipoproteins by the liver and in peripheral tissue, yielding increased circulation of these atherogenic lipoproteins [10]. Disturbances in lipoprotein metabolism are evident even in the early stages of CKD and usually follow a downhill course that parallels the deterioration in renal function [11]. Severe lipid metabolism disorders arise in patients with kidney failure and the lipid metabolism disorder peculiar to this patient group is known as uremic dyslipidemia [11], which may accelerate its progression [12]. Abnormal lipid profile in CKD includes hypertriglyceridemia, increase in triglyceride remnant Lp (a), increase in very-low-density lipoprotein (VLDL), decrease in high density lipoprotein (HDL), total cholesterol (TC) and low-density lipoprotein (LDL) usually within normal limits except in nephrotic syndrome patients [13]. Dyslipidemia is a major risk factor for coronary heart disease [14,15]; it has prompted interest in the identification and management of abnormalities in plasma lipids and lipoproteins.
Experimental studies suggest that hyperlipidemia accelerates renal damage due to progressive glomerulosclerosis and tubulointerstitial disease [16]. There is also growing evidence that abnormalities in lipid metabolism may contribute to renal disease progression [17]. Lipid-lowering treatment can reduce renal damage and preserve renal function [18]. The triglyceride-rich apoB containing lipoproteins are found to be associated with accelerated deterioration of renal function [15]; however, the pathophysiological mechanism is not fully understood. Use of lipidlowering agents may be helpful in correcting the lipid abnormalities, but a proper clinical trial is needed to establish the efficacy of hypolipidemic drugs on the attenuation of lipid abnormalities and to prevent the progression of renal disease [19].
We encounter a large number of patients with CKD with abnormal serum lipid profiles in our institution of Pandit Raghunath Murmu Medical College and Hospital, Baripada. As these being unpublished data we want to conduct a study, first of this type in our new college, to evaluate the type of dyslipidemia in CKD patients and correlates with the severity of renal dysfunction in CKD patients; which may have a future prognostic and management implication in patients with CKD.

MATERIALS AND METHODS
The observational study was conducted in the Department of General Medicine, PRM MCH, Baripada. The patients of CKD who had attended to department of general medicine OPD and who were admitted to department of general medicine, PRM MCH, Baripada between May 2018 and January 2019 were taken in our study.

Inclusion criteria
 All patients of CKD above 15 y of age satisfying the following criteria were included in the study. Criteria for diagnosis of CKD were as given by-National Kidney Foundation: K/DOQI clinical practice guidelines for Chronic Kidney Disease: Evaluation, Classification and Stratification [20].
CKD is defined as the presence, for at least 3 mo, of evidence of kidney damage with an abnormal GFR or alternatively, by a GFR<60 ml/min/1.73m 2 BSA [20].

Kidney damage is evidenced by-
 Proteinuria>300 mg/day OR  Pathological abnormality found in histopathological study OR  Renal imaging study (USG) showing bilateral contracted kidneys<9 cm with thinned parenchyma and reduced corticomedullary differentiation.

Exclusion criteria
• Patients aged below 15 y of age

• Patients on haemodialysis
• Patients with diabetes mellitus, hypothyroid, liver disease, Coronary heart disease • Patients on lipid-lowering drugs • Kidney transplanted patients 262 CKD patients were included in the study. All patients diagnosed with moderate to severe CKD, e-GFR was calculated according to the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation, 2009 and divided into two groups. e-GFR was graded G1, G2, G3a, G3b, G4 and G5 as per the KDIGO 2012 guidelines [1]. 20 healthy persons were taken as controls (Group A). Group B  Patients with e-GFR>30 ml/min was considered as moderate CKD (Stage 3) (n=55)). Group C  Patients with e-GFR<30 ml/min was considered as severe CKD (Stage 4 and 5) (n=207)).

Investigations
All patients had undergone thorough clinical examination and laboratory investigations like complete blood counts, serum urea and creatinine, blood sugar and lipid profile. Ultrasound of the abdomen was done on every patient. A fasting serum lipid profile included serum cholesterol, triglyceride, HDL and LDL cholesterol on a Fully Automated analyzer (Erba EM360).

Statistical analysis
The statistical analysis was done using the Statistical Package for Social Sciences (SPSS) version 21.0. Univariate analysis was used in the description of demographic characteristics of the study population. Discrete variables were presented as frequency and percentages. Continuous variables were presented as means and standard deviation (SD) for unpaired data; the Student t-test was used to compare mean values (for two groups). Pearson's correlation was used to determine the association between eGFR and other variables. Fisher's exact test was used to determine the significant associations between categorical variables. P-value<0.05 was considered statistically significant* and<0.001 was considered as statistically extremely significant**.

RESULTS
During the study period, 262 patients with CKD attended to MOPD and admitted in the medicine ward of PRM MCH, Baripada, fulfill inclusion and exclusion criteria. All the cases were studied for the clinical presentation, risk factors and laboratory parameters.
In our study, 262 patients with CKD were included; which constitutes 64.50% (169) of male and 35.50% (93) of females with M: F of 1.8:1; with age ranging from 20 to 95. The average age of the patients in the study was 56.66+12.22 y. The average age of the male and female patients in the study was 56.16+12.63 and 57.57+11.46 y, respectively. Fig. 1 shows 45.04 % (118) of the patients were between 46 and 60 y of age, followed by 27.86 % (73) of the patients were between 61 and 75 y of age; the majority (66.41%) being below 60 y age group. 79.01% (207 cases) of the patients in our study group belong to stage 4 and stage 5 chronic kidney diseases. All the cases in 15-30 y of age group are severe CKD (stage 4 and 5).
In our study, we found that 32.82% CKD cases had hypertension. 30  The prevalence of dyslipidemia among CKD patients with relation to the severity is statistically significant (p = 0.033*) The mean value of serum cholesterol was 164.04±47.85 mg/dl range from 44 mg/dl to 323 mg/dl. 19.61% of the cases were having hypercholesterolemia [ fig. 2].

Int J Pharm Pharm Sci, Vol 12, Issue
Age distribution of the CKD patients according to the stages of CKD as per e The prevalence of dyslipidemia among CKD patients with relation to the severity is statistically significant (p = 0.033*)
On comparing various parameters between cases and controls, there is a significant rise in blood Urea (p<0.001) and serum Creatinine (p<0.001).  Values are expressed as Mean+SD. Significant rise in total cholesterol, triglycerides, LDL and fall in HDL in group B and group C comparing to group A. There is an extremely significant fall in HDL when comparing group B and group C. Table 5 shows there is a significant rise in total cholesterol, triglycerides, LDL and fall in HDL in group B and group C comparing to control (group A) with decreasing e-GFR. There is an extremely significant fall in HDL (p<0.001**) when comparing group B and group C signifies increasing dyslipidemia with decreasing e-GFR, with increasing severity of CKD.

DISCUSSION
The current study was a cross-sectional study done to find out the derangement in lipid profile found in different stages of CKD, to find out its relationship with the severity of the disease in this part of the world.
In our study group, 64.50% of patients were male and 35.50% of patients were female with M: F of 1.8:1. In CKD Registry of India 2007 [21], the male cases were 68.9% and female cases were 31.1%. Similar results to the current study were seen in studies by Abraham et al. [22] and Ganta et al. [23]. Mean age of cases was 56.66±12.22 y and control was 41.05±17.75 y. This was similar to that of CKD Registry of India 2007 [21] where the mean age of cases was 48.3±16.6 y and in the studies by Patel and Sirajwala et al. [24] and by Mohanty et al. [25].
As depicted in fig. 1, 46 and 60 [31] in separate studies showed a significant inverse correlation between triglyceride and e-GFR and significant positive correlation between high-density lipoprotein and e-GFR (p=<0.001). Kumari et al. [32] found a negative correlation between serum HDL-C level and serum creatinine levels, which were statistically significant. Muntner et al. have shown that people with low HDL values and high TG values have an increased risk of renal function alteration [33]. Table 4 shows the comparison between lipid profiles of cases and controls showed significant difference between total cholesterol (p= 0.002*), triglyceride (p= 0.002*), HDL (p= 0.008*), LDL (p= 0.013*). On comparing various parameters between cases and controls, there is a significant rise in blood Urea (p<0.001**) and serum Creatinine (p<0.001**). Mohanty et al. study also showed similar significant statistical association of total cholesterol (p= 0.001), triglyceride (p= 0.001), HDL (p= 0.000), LDL (p= 0.000) between control and cases [25]. Kumari et al. study also found similar results to our study [32]. Table 5 shows there is a significant rise in total cholesterol, triglycerides, LDL and fall in HDL in moderate CKD (group B) and severe CKD (group C) comparing to control (group A) with decreasing e-GFR. There is an extremely significant fall in HDL (p<0.001**); comparing moderate CKD (group B) to severe CKD (group C); signifies increasing dyslipidemia with decreasing e-GFR, with increasing severity of CKD.
These findings indicate a rise in serum total cholesterol, triglycerides, low-density lipoproteins and a fall in high-density lipoproteins in CKD with a fall in e-GFR. Similar changes in lipid profiles were seen by Ganta V et al. [23], Patel and Sirajwala [24], Mohanty et al. [25] and Machnur et al. [34].

LIMITATION
A more widespread study including large number of patients and for longer duration; with appropriate clinical trial is required to attain a firm conclusion. Assessment of predialysis and post dialysis lipid profile parameters in the same CKD patient and follow up lipid profile evaluation after repeated hemodialysis will provide more consistent information on the effect of hemodialysis on lipid profile parameters in CKD patients.

CONCLUSION
The results of the present study provide valuable information and an association between lipid abnormalities and CKD patients, concluding that the prevalence of dyslipidemia in non-diabetic CKD is high enough to pose a major health problem and this problem of dyslipidemia increases with the severity of CKD. A high degree of abnormality is found in HDL with disease progression, which is statistically significant. This study confirms the presence of atherogenic lipid profile in CKD patients, which can lead to renal disease progression; and increased morbidity and mortality due to additional CVD risks. Therefore, maintenance of desired lipid parameters either through diet or early initiation of lipid-lowering drugs can be helpful in decreasing the risk of cardiovascular complications in CKD patients.