European Journal of Cardiovascular Medicine

Diabetes mellitus is a chronic metabolic disorder characterised by impaired carbohydrate metabolism due to insulin deficiency, defective insulin secretion, or peripheral insulin resistance. Recognised by the WHO as a major global health challenge, diabetes poses a significant burden in morbidity, mortality, and healthcare costs. In 2013, an estimated 382 million individuals were affected, with projections rising to 592 million by 2035¹.

Among its complications, diabetic nephropathy is a leading cause of end-stage renal disease (ESRD), affecting 30-40% of Type 1 and 50% of Type 2 diabetes patients over 20 years. Microalbuminuria serves as an early marker of renal impairment, progressing to renal failure if untreated².

Glycation, a key mechanism in diabetes complications, leads to the formation of advanced glycation end products (AGEs). Haemoglobin A1c (HbA1c), a marker of glycemic control, is linked to nephropathy progression³. Major trials like DCCT and UKPDS demonstrate that intensive glycemic control delays microvascular complications. The ADA and EASD recommend maintaining HbA1c ≤7.0% to reduce complications⁴.

While HbA1c is a widely used glycemic control marker, albuminuria is a key indicator of renal dysfunction. Understanding their combined impact can improve risk stratification and guide early interventions⁵.

Additionally, factors such as hypertension, dyslipidemia, smoking, and genetic predisposition contribute to nephropathy progression. Further research on treatment strategies is essential to optimise clinical management, mitigate disease progression, and reduce the burden of ESRD⁶. This study aims to enhance early detection by evaluating the interplay between glycemic control, albuminuria, and other modifiable risk factors.

Study Design and Setting: This cross-sectional study was conducted at a tertiary care institute in Ahmedabad from October 2016 to September 2018. Patients attending both inpatient and outpatient departments were considered for inclusion. All participants were informed in detail about the study, and only those who provided written informed consent were enrolled.

Inclusion and Exclusion Criteria: The study included patients diagnosed with Type 2 diabetes mellitus (T2DM) between 18 and 80 years old who provided written informed consent. Patients with Type 1 diabetes mellitus and those with macrovascular complications such as coronary artery disease (CAD), peripheral arterial disease (PAD), or cerebrovascular accident (CVA) were excluded. Additionally, individuals with significant comorbidities, including chronic liver disease, chronic kidney disease, and heart failure, were not considered for the study. Pregnant women and patients with conditions causing transient albuminuria, such as infections, heart failure, strenuous exercise, or uncontrolled hypertension, were also excluded. Finally, individuals unwilling to provide consent were not enrolled.

Sample Size and Sampling Technique: 150 patients diagnosed with Type 2 diabetes mellitus were included purposively in the study.

Data Collection and Assessment: A detailed history was obtained from all participants, focusing on demographic information, duration of diabetes, and treatment history. Patients were also evaluated for symptoms such as tingling or numbness in the limbs. A history of cardiovascular symptoms, including chest pain, claudication, and stroke, was recorded. Additionally, any history of blurring of vision and comorbid conditions such as hypertension was documented.

A thorough general examination was conducted for all participants. Body mass index (BMI) was calculated using the Quetelet Index (weight in kilograms divided by height in square meters). Blood pressure was measured in the right brachial artery while the patient was sitting, with an average of three readings recorded in hypertensive individuals. A routine systemic examination was performed to assess overall health status.

A systemic examination was carried out to evaluate potential complications associated with diabetes. The cardiovascular system was assessed for cardiac abnormalities, while the respiratory system was examined for pulmonary involvement. Special emphasis was placed on evaluating the central nervous system, particularly for signs of peripheral neuropathy and autonomic dysfunction. The gastrointestinal system was also examined for any diabetes-related manifestations.

Laboratory Investigations: As part of the standard management protocol, patients with diabetes undergo a basic metabolic and renal profile. We collected details of these tests, which included haemoglobin levels as part of the routine haematological evaluation, serum creatinine and early morning spot urine albumin-creatinine ratio (UACR) for renal function assessment, and fasting blood glucose (FBG), postprandial blood glucose (PPBG), and glycated haemoglobin (HbA1c) for glycemic control, with HbA1c measured using automated high-performance liquid chromatography (HPLC). Additionally, lipid profile analysis encompassed total cholesterol, triglycerides, and high-density lipoprotein (HDL) levels.

To assess diabetes-related complications, all participants underwent a fundus examination using direct ophthalmoscopy, which an ophthalmologist performed to evaluate diabetic retinopathy. Neuropathy was considered in patients who exhibited symptoms and signs, including two or more of the following: neuropathic symptoms, decreased distal sensation, or unequivocally reduced or absent ankle reflexes.

Biochemical Methods: Serum glucose levels were measured using the hexokinase enzymatic method. HbA1c levels were analysed using automated high-performance liquid chromatography (HPLC), ensuring accurate quantification of long-term glycemic control. Albuminuria was evaluated using the early morning spot urine albumin-creatinine ratio (UACR), a reliable indicator of early renal dysfunction in diabetic patients.

Data analysis: Data were entered and analysed through Epi info 7. Frequency and proportions were derived for categorical variables. Relations between categorical variables were assessed through a chi-square test. A p-value less than 0.05 was considered statistically significant.

As per Table 1, the majority (66.6%) had normoalbuminuria, while 24% had microalbuminuria and 9.3% had macroalbuminuria. Males constituted 62.6% of the patients, and the most common age group was 51-60 (32%).

Table 1: Demographic and Clinical Characteristics

According to Table 2, a higher proportion of patients with microalbuminuria (75%) had elevated total cholesterol (>200 mg/dL) and HbA1c (>7%) compared to normoalbuminuria patients. LDL levels were relatively balanced across groups, with 55.3% having LDL <100 mg/dL.

Table 2: Lipid Profile and Glycemic Control by Albuminuria Status

Table 3 highlights the relationship between Albumin-Creatinine Ratio (ACR) and lipid profile, HbA1c, and treatment status. Patients with higher LDL (>100 mg/dL), total cholesterol (>200 mg/dL), and HbA1c (>7%) exhibited elevated ACR levels (>30 mg/g), indicating high ACR. Those on treatment had moderate ACR levels (50 ± 7 mg/g), while untreated patients showed significantly higher ACR (85 ± 12 mg/g). Higher ACR was linked to elevated LDL, cholesterol, HbA1c, and lack of treatment, indicating renal dysfunction in Type 2 diabetes.

Table 3: Albumin-Creatinine Ratio (ACR) to Lipid Profile, HbA1c, and Treatment

The table shows complications in type 2 diabetes patients by albuminuria status. Retinopathy and hypertension were significantly more prevalent in microalbuminuria (19.4% and 41.6%) and macroalbuminuria (14.2% and 42.8%) groups compared to normoalbuminuria (5% and 22%). Neuropathy showed no significant difference across groups (p=0.8315).

Table 4: Complications and Albuminuria:

This study categorised patients into three groups based on albuminuria levels: normoalbuminuric, microalbuminuric, and macroalbuminuric. Among the 150 participants, males constituted 62.6% (n=94) and females 37.3% (n=56), with a higher male predominance observed in the macroalbuminuric group (71.4%). Most patients (66.6%) were normoalbuminuric, followed by 24% with microalbuminuria and 9.3% with macroalbuminuria.

The prevalence of microalbuminuria observed in this study aligns with prior epidemiological data, confirming a slightly higher incidence in males^7,8. Differences in reported prevalence across studies result from variations in study populations, methodologies, and diagnostic thresholds. The findings underscore the importance of early detection in mitigating the progression of diabetic nephropathy⁹.

An analysis of disease duration demonstrated a clear association with albuminuria levels. Patients were stratified into four groups based on the duration of diabetes: 0–5 years, 6–10 years, 11–15 years, and 16–20 years. The highest incidence of microalbuminuria was detected in patients diagnosed within the first five years of disease onset. However, previous studies have reported a higher prevalence of microalbuminuria with increasing disease duration^10,11. The difference in findings stems from the limited representation of patients with longstanding diabetes in this study, mainly due to patient attrition, loss to follow-up, or exclusion of individuals with severe comorbidities.

Body mass index (BMI) was evaluated to determine its association with albuminuria, and the results confirm a strong correlation between obesity and renal dysfunction. Among the study population, 43.3% were obese, 20% were overweight, and 36.6% had a normal BMI. A higher prevalence of both microalbuminuria and macroalbuminuria was observed among obese individuals, substantiating previous evidence that establishes obesity as a significant risk factor for renal dysfunction in diabetes¹². These findings affirm the necessity of weight management in mitigating renal complications among diabetic patients.

Glycemic control, assessed through HbA1c levels, significantly correlated with albuminuria severity. Patients were categorised into two groups based on HbA1c values: <7% and ≥7%. Among the macroalbuminuric cohort, 50% exhibited HbA1c levels ≥7%, while 75% of microalbuminuric patients belonged to the same category. The statistically significant association confirms that chronic hyperglycemia contributes to the progression of diabetic nephropathy^13,14. The findings support the necessity of stringent glycemic control in delaying nephropathy onset and progression.

Among the study cohort, 133 patients received pharmacological treatment for diabetes, while 17 were not on any therapeutic regimen. Despite ongoing therapy, the mean albumin-creatinine ratio (ACR) in treated patients remained elevated at 285, confirming persistent renal involvement. The mean HbA1c among treated individuals was 9.3%, compared to 10.6% in untreated patients. These findings establish that while pharmacological intervention improves glycemic control, it does not invariably prevent albuminuria progression, reinforcing the necessity for more aggressive, individualised treatment protocols¹⁵.

The study further examined the interplay between lipid parameters and microalbuminuria, identifying a statistically significant correlation with total cholesterol, triglycerides, and HDL levels. However, LDL levels did not exhibit a strong association. Among microalbuminuric patients, 75% had total cholesterol levels exceeding 200 mg/dL, while 61.1% had serum triglycerides above 150 mg/dL. Additionally, individuals with HDL levels below 40 mg/dL demonstrated a disproportionately higher prevalence of albuminuria. These findings confirm the contributory role of dyslipidemia in the pathogenesis of diabetic nephropathy and reinforce the importance of lipid modulation as an essential component of nephroprotective strategies⁹.

Multivariate regression analysis, adjusted for confounders such as age, sex, BMI, and antihypertensive medication use, demonstrated a significant association between microalbuminuria and both diastolic blood pressure and fasting plasma glucose levels. However, systolic blood pressure, serum HDL cholesterol, and triglyceride levels did not demonstrate statistically significant correlations. Furthermore, a strong association between microalbuminuria and hypertension was identified, affirming the critical role of blood pressure management in preventing nephropathy progression⁸.

Retinopathy, a well-established microvascular complication of diabetes, was frequently observed in conjunction with microalbuminuria. Previous studies have identified microalbuminuria as a predictive marker for diabetic retinopathy progression, particularly in individuals with declining renal function¹⁶. The findings reinforce the necessity of regular ophthalmologic screening in diabetic patients with evidence of albuminuria.

This study demonstrates a strong correlation between microalbuminuria and key clinical factors such as disease duration, BMI, HbA1c levels, dyslipidemia, and hypertension, reaffirming the complex interplay of metabolic and vascular mechanisms in the progression of diabetic nephropathy. The findings underscore the necessity of proactive and comprehensive intervention strategies, focusing on maintaining optimal glycemic control, regulating blood pressure, and managing lipid levels. These measures are crucial in minimising the risk of progressive renal impairment in individuals with Type 2 diabetes mellitus.

Limitations

Our study is limited by a smaller sample size, particularly among patients with a diabetes duration of more than 10 years, likely due to loss to follow-up or the presence of significant comorbidities that prevented participation. Additionally, seasonal variations in albuminuria were not considered, which may influence the findings.

Microalbuminuria is an early predictor of diabetic nephropathy, strongly linked to poor glycemic control, dyslipidemia, hypertension, and early diabetes duration. Routine screening with urine analysis, albumin-creatinine ratio, and targeted interventions, including lifestyle modifications, antidiabetic therapy, and ACEIs/ARBs, can help reduce proteinuria and delay disease progression.

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