European Journal of Cardiovascular Medicine

Diabetes is a serious, chronic disease that occurs either when the pancreas does not produce enough insulin (a hormone that regulates blood glucose), or when the body cannot effectively use the produced Insulin. Type 2 diabetes mellitus (T2DM) (formerly called non-insulin-dependent or adult-onset diabetes) results from the body’s ineffective use of Insulin. T2DM accounts for the vast majority of people with diabetes around the world.(¹)The burden of type 2 diabetes mellitus has steadily increased over the past quarter-century in India and across the globe, with India contributing a major part of the global burden.(²)Developing countries in the South Asian region including India are facing an enormous healthcare burden in managing patients with different acute and chronic complications of T2DM.(³) Cardiovascular disease (CVD) and chronic kidney disease (CKD) are two major chronic complications of type 2 diabetes mellitus.(⁴)

Diabetes, a major health problem with global estimates exceeding 382 million people, also plays a role in increasing the prevalence of CKD. In fact, 40% of patients with diabetes develop diabetic kidney disease (DKD) resulting in albuminuria, reduction of the glomerular filtration rate (GFR), or both. (⁵) While CVD accounts for around 75% of deaths among individuals with T2DM, end-stage renal disease (ESRD), due to diabetic nephropathy (DN), is one of the common indications for renal replacement therapy worldwide. (^6,7).

The etiology of CKD is multifactorial, with glomerular hypertension and hyperfiltration reflecting the most prominent mechanistic contributors to disease progression. Hyperfiltration initiates the Renin-Angiotensin-Aldosterone system (RAAS), which in turn, increases glomerular permeability and gives rise to albuminuria, proteinuria, and dyslipidaemia, while also diminishing glomerular filtration rate (GFR), thus reciprocally leading to hypertension. Diabetic kidney disease (DKD) is typically characterized by persistent albuminuria, increasing serum creatinine, and a progressive decline in estimated GFR (eGFR). Over time, worsening DKD is associated with an increased risk of cardiovascular and cerebrovascular events, as well as renal morbidity and mortality.(⁸) Diabetic nephropathy develops in 40%–60% of individuals with type 2 diabetes and is characterized by a progressive and persistent decline in kidney function that with time can lead to ESRD.(⁹) Diabetic nephropathy (DN) is diagnosed by demonstration of albumin over 30mg/grams of creatinine in urine (albuminuria) or reduction of estimated glomerular filtration rate (eGFR) less than 60 ml/min using a standard formula.(¹⁰) Several risks calculating tools are available to assess the CVD risk among patients with T2DM at the primary care level.  United Kingdom Prospective Diabetes Study (UKPDS) risk engine is a risk scoring tool introduced after the landmark UKPDS trial to calculate the coronary heart disease risk (CHDR) in patients with T2DM without symptoms of CVD. (¹¹)

Although the association between DN and high CVD risk is well established in studies conducted in developed countries and there is a rising incidence of T2DM and associated burden of CVD and CKD in developing countries like India.  Demonstration of such an association by measuring the eGFR and albuminuria and its relative strength would be useful for physicians for therapeutic decision making when managing patients with T2DM without cardiac comorbidities and helps to identify those who might benefit from earlier intervention to lower the risk of adverse outcomes.(¹²)With this background, we have planned this study to find out the association of a diabetes-specific CHDR scoring tool, namely, UKPDS risk engine with albuminuria and eGFR, two commonly used tests to diagnose DN and to find association of cardiac comorbidities in patients with T2DM without symptomatic CVD.

The present cross sectional, was carried out at Department of Biochemistry, RUHS-CMS and Associated Hospitals, Jaipur. The study duration was 2 years period from Jan. 2020 to Dec. 2021. A sample size of 100 was calculated at 95% confidence interval at 10% acceptable margin of error by epi info software version 7.3.  In the present study we used a database which included demographic and biochemical data of adult patients with T2DM over the age of 30 years who presented for single visit screening. Data on age (obtained from Aadhar card) and the duration of diabetes to the nearest year (verified from the clinic records) were obtained. Patient’s weight and height were measured and their body mass index (BMI) was calculated. Blood pressure was recorded after at least five minutes rest using a standar0064 mercury sphygmomanometer.

Patients with an established coronary artery, cerebrovascular, or peripheral arterial disease; those with history of nondiabetic renal diseases, for example, due to connective tissue diseases and obstructive uropathy or nephritic/nephrotic syndrome,CKD-IV and V, patients with evidence of urinary tract infection in the urine deposits (pus cells more than 5 per high power field and/or positive nitrites in the dipstick test), pregnant mother, type 1 diabetes mellitus, T2DM for less than one year were excluded. All study participants were subjected to overnight fasting of 10-12 hours, venous blood samples were collected by using the aseptic technique.

 Collected samples were centrifuged, and serum was separated and subjected to the biochemical estimations. Glycated Haemoglobin (HbA1C) was estimated by immuno-turbidimetry. After measuring serum creatinine level with modified Jaffe’s method, eGFR was estimated using modified diet in the renal disease (MDRD) formula. Spot urine sample was collected and analyzed urinary albumin by an immunoturbidimetric method. Urine albumin excretion over 30mg/L were considered as having albuminuria’s score has been calculated by the UKPDS risk engine which includes age, sex, HbA1c, diabetes duration, smoking status, total Chol/HDL-C ratio, systolic blood pressure, and ethnicity and has been calculated the 10-year probability of developing a CHD event. Electrocardiogram was obtained by 12-lead electrocardiogram.

All the type 2 diabetic patients were categorized into 3 groups on the basis of eGFR levels: -

1. CKD-1: eGFR ≥ 90 ml/min/1.73 m2
2. CKD-2: eGFR between 60-89 ml/min/1.73 m2
3. CKD-3: eGFR between 30-59 ml/min/1.73 m2

Ethical Approval: Ethical clearance for the present study was obtained from the RUHS-CMS Ethics Committee, RUHS College of Medical Sciences, Jaipur. Written informed consent was obtained from all study subjects in the local language.

Statistical Analysis: Quantitative data has been collected and submitted to a Microsoft Excel worksheet in the form of a master chart. Quantitative data has been represented in the form of a mean with standard deviation (mean ±SD). We have used Pearson’s chi-square test for the calculation of p-value for the association between the categorical variables and ANOVA test to determine the significance of the correlation between measurable and countable variables for 3 groups to infer data. Levels of statistical significance were set at p-value < 0.05.

Out of all the studied diabetes subjects (n=100), 63% were males. Age, duration of diabetes, eGFR and urinary albumin values were 56.57 ± 12.78years, 5.82 ± 4.59 years,82.38 ± 23.91ml/min/1.73m2 and 73.25 ± 66.87 mg/Respectively. Descriptive data of the participants studied are shown in table 1.

Comparison between groups according to eGFR categories of type 2 DM patients are summarized in table 2.  As the mean age (years), urea (mg/dl), creatinine (mg/dl) and uric acid (mg/dl) increases, eGFR declines within eGFR subcategories. ANOVA test was done to determine the significance of the correlation between these parameters and eGFR categories, p-value was <0.05 which was statistically significant.

Using chi-square test to determine the significance of association between CHDR score and eGFR levels, p-value was 0.014 which was statistically significant.

Table 4 shows that 23.6%, 33.3% and 43.1% patients of albuminuria >30 mg/L had <18, 18-31 and >31 CHDR score respectively. Using chi-square test to determine the significance of association between CHDR score and albuminuria, p-value was <0.05, which was statistically significant. When the association of eGFR with CHDR and eGFR with albuminuria was studied, we found linear correlation between the groups(Figure1 and 2).

The present study revealed two significant findings on association of albuminuria and eGFR with CHDR calculated by UKPDS risk engine among patients with T2DM without symptomatic CVD. Our result underlines the significant role of albuminuria whose association with a CHDR score seems to be stronger than a reduction in eGFR in type 2 diabetic patients. Mean (±SD) age and duration of diabetes were 56.57 (±12.78) and 5.82 (±4.59) years, respectively. As the age (years), serum urea, creatinine, and uric acid increases, eGFR declines significantly. With the increasing duration of diabetes mellitus, eGFR declines but was not significant statistically. There was significant association between CHDR score and eGFR, and albuminuria. Similar result found in a study conducted by A study had been done by Weerarathna Tet al, (¹²) on Sri Lankan population. Of the patients with diabetes studied (n=2434), 64% (1563) were males as found in our study (63.0%). Mean (SD) age and duration of diabetes were 52 (11) and 9 (3) years, respectively. They concluded that predicted CHDR shows a moderate and significant association with eGFR in patients with T2DM without symptomatic CVD. eGFR is a stronger predictor than albuminuria in predicting high CHDR in patients with T2DM. Intensification of CVD prevention measures should be done more confidently among patients with T2DM and reduced eGFR than in those with albuminuria alone.

In clinical practice, diabetic nephropathy is diagnosed either when eGFR falls to less than 60 ml/min or the urine albumin excretion over 30 mg/L. Association of both these parameters with macrovascular disease has been reported in different settings and revealed conflicting findings on their relative value(13) Most of these studies are prospective in design and are conducted in developed countries, and many have used incident CVD events as opposed to calculated CVD risk such as CHDR as in our study. Similar results found in a study conducted from Japan by Bouchi R et al, (¹⁴) included 1002 T2DM patients with no history of CVD in four categories of CKD according to eGFR (≥90, 60-89, 30-59, and 15-29 ml/min) over five years with endpoints of an incident stroke and CHD reported that reduced eGFR was independently associated with incident CHD but not stroke.

The FIELD (Fenofibrate Intervention and Event Lowering in Diabetes) study of Druri PL et al,(¹⁵)  included a larger population of 9,795 low-risk Caucasian patients with diabetes reported that both reduced eGFR and albuminuria were independent predictors of incident CVD over a follow-up period of five years (lower eGFR v/s eGFR ≥ 90 ml/min/1.73 m2 was a risk factor for total CVD events (OR [95% CI] 1.14 [1.01- 1.29] for eGFR 60-89 ml/min/1.73 m2; 1.59 [1.28-1.98] for eGFR 30-59 ml/min/1.73 m2 ; P < 0.001; adjusted for other characteristics) and albuminuria increased increasing total CVD (HR 1.25 [1.01-1.54] and 1.19 [0.76-1.85], respectively; P = 0.001 for trend) when eGFR ≥ 90 ml/min/1.73 m2 ).

Another cross-sectional study of Solini A et al,(¹⁰) from Italy, which evaluated 15,773 patients with T2DM, has reported that CVD risk increased linearly with eGFR decline and albuminuria and became significant for values < 78 mL/min/1.73 m2 and ≥ 10.5 mg/24 h, respectively. Total CVD showed an independent association with albuminuria alone (OR 1.20 [95% CI 1.08- 1.33]), reduced eGFR alone (OR 1.52 [95% CI 1.34-1.73]), and both (OR 1.90 [95% CI 1.66-2.19]). In this study too, coronary artery diseases were associated predominantly with reduced eGFR alone, whereas cerebrovascular and peripheral events showed a stronger correlation with the albuminuric CKD phenotypes.

The study findings are clinically relevant as discussed in above-mentioned literature. We found a statistically significant association of diabetic nephropathy diagnosed with albuminuria >30 mg/L compared to eGFR less than 60 ml/min/1.73m2 with associated CVD risk. eGFR and albuminuria are not only a more convenient but can be considered as reliable and proven indicator for associating CVD risk in patients with T2DM with no symptoms of CVD. Similar results obtained in a study conducted by Oshima Met al,(¹⁶) studied using data from a multicentre observational cohort study of 1417 patients with T2DM over 2 years, and they concluded that combined changes in albuminuria and eGFR over 2 years were strongly associated with future risk of kidney failure in patients with type 2 diabetes.

In conclusion, eGFR and albuminuria have a statistically significant and strong association with CHDR score in associating high CVD risk calculated by UKPDS risk engine in patients with T2DM without cardiac comorbidity. So, measuring eGFR and albuminuria would be useful to make therapeutic decisions to lower the risk of CVD while managing T2DM patients.

1. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus (WHO/NCD/NCS/99.2). Geneva: World Health Organization; 1999.
2. Global report on diabetes. Geneva: World Health Organization; 2016.
3. Misra A, Ramchandran A, Jayawardena R, Shrivastava U, Snehalatha C. Diabetes in South Asians. Diabet Med. 2014;31(10):1153- 62.
4. Hahr AJ, Molitch ME. Diabetes, cardiovascular risk and nephropathy. Cardiol Clin. 2010;28(3):467-75.
5. De Cosmo S, Rossi MC, Pellegrini F, Lucisano G, Bacci S, Gentile S, Ceriello A, Russo G, Nicolucci A, Giorda C, Viazzi F, Pontremoli R, AMD-Annals Study Group- Annals Study Group. Kidney dysfunction and related cardiovascular risk factors among patients with type 2 diabetes. Nephrol Dial Transplant. 2014 March;29(3):657-62.
6. Boon MR, Bakker LEH, Van Der Linden RAD, van Ouwerkerk AF, de Goeje PL, Counotte J, Jazet IM, Rensen PC. High prevalence of cardiovascular disease in South Asians: central role for brown adipose tissue? Crit Rev Clin Lab Sci. 2015;52(3):150-7.
7. Kostakis A, Theodoropoulou E. Diabetes mellitus and renal transplantation: A short update. Exp Clin Transplant. 2018;16(Suppl 1);Suppl 1:1-3.
8. Perkovic V, Agarwal R, Fioretto P, Hemmelgarn BR, Levin A, Thomas MC, Wanner C, Kasiske BL, Wheeler DC, Groop PH, Conference Participants. Manageme of patients with diabetes and CKD: conclusions from a “kidney disease: improving global outcomes” (KDIGO) controversies conference. Kidney Int. 2016;90(6):1175-83.
9. Zoppini G, Targher G, Chonchol M, Ortalda V, Negri C, Stoico V, Bonora E. Predictors of estimated GFR decline in patients with type 2 109 diabetes and preserved kidney function. Clin J Am Soc Nephrol. 2012 March;7(3):401-8.
10. Solini A, Penno G, Bonora E, Fondelli C, Orsi E, Arosio M, Trevisan R, Vedovato M, Cignarelli M, Andreozzi F, Nicolucci A, Pugliese G, Renal Insufficiency And Cardiovascular Events (RIACE) Study Group. Diverging association of reduced glomerular filtration rate and albuminuria with coronary and noncoronary events in patients with type 107 2 diabetes: the renal insufficiency and cardiovascular events (RIACE) Italian multicenter study. Diabetes Care. 2012;35(1):143-9.
11. Davis TME, Coleman RL, Holman RR, UKPDS Group. Prognostic significance of silent myocardial infarction in newly diagnosed type 2 diabetes mellitus: United Kingdom prospective diabetes study (UKPDS) 79. Circulation. 2013;127(9):980-7.
12. Weerarathna T, Liyanage G, Herath M, Weerarathna M, Amarasinghe I. Value of estimated glomerular filtration rate and albuminuria in predicting cardiovascular risk in patients with Type 2 diabetes without cardiovascular disease. BioMed Res Int. 2018;2018:8178043.
13. Blaine and M. Levi, “Chronic kidney disease: Albuminuria or CKD stage as best marker of CVD in diabetes?” Nature Reviews Nephrology, vol. 8, no. 7, pp. 376-377, 2012.
14. Bouchi R, Babazono T, Yoshida N, Nyumura I, Toya K, Hayashi T, Hanai K, Tanaka N, Ishii A, Iwamoto Y. Association of albuminuria and reduced estimated glomerular filtration rate with incident stroke and coronary artery disease in patients with type 2 diabetes. Hypertens Res. 2010;33(12):1298-304.
15. Drury PL, Ting R, Zannino D, Ehnholm C, Flack J, Whiting M, Fassett R, Ansquer JC, Dixon P, Davis TM, Pardy C, Colman P, Keech A. Estimated glomerular filtration rate and albuminuria are independent predictors of cardiovascular events and death in type 2 diabetes mellitus: the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study. Diabetologia,2011vol.54;54(1):32-43.
16. Oshima M, Toyama T, Hara A, Shimizu M, Kitajima S, Iwata Y, Sakai N, Furuichi K, Haneda M, Babazono T, Yokoyama H, Iseki K, Araki SI, Ninomiya T, Hara S, Suzuki Y, Iwano M, Kusano E, Moriya T, Satoh H, Nakamura H, Makino H, Wada T. Combined changes in 115 albuminuria and kidney function and subsequent risk for kidney failure in type 2 diabetes. BMJ Open Diabetes Res Care. 2021;9(1):e002311.