Chronic illnesses have become prevalent worldwide and are a major contributor to illness and death. Type 2 diabetes mellitus is a major contributor to this burden, with complications like diabetic nephropathy being a key public health concern (1–3). Diabetic nephropathy is the leading cause of end-stage renal disease (ESRD), affecting 5–10% of type 2 diabetics and representing a growing medical crisis (3). India, with over 40.9 million diabetic individuals, is projected to reach 69.9 million by 2025 (4). The Asian Indian phenotype increases vulnerability to microvascular complications such as diabetic nephropathy (5,8). Type 2 diabetics account for nearly 50–60% of patients on renal replacement therapy (6), with microalbuminuria prevalence up to 26.9% (7,9). Diabetic nephropathy is a progressive kidney disease characterized by albuminuria and declining renal function. While metabolic and hemodynamic changes play a role in its pathogenesis, recent studies suggest that chronic low-grade inflammation is also involved (10,11). Inflammatory markers like CRP, IL-6, and fibrinogen are elevated in type 2 diabetics with diabetic nephropathy (12–16). Though these markers are linked to cardiovascular risk, their association with diabetic microangiopathy remains unclear. High-sensitivity CRP (hsCRP), due to its long half-life, cost-effectiveness, and correlation with HbA1c, is a promising marker for disease monitoring. However, limited data exist on the link between hsCRP and diabetic nephropathy in Indian populations. Investigating this connection could enhance early diagnosis and help classify patients by risk level. This study aims to evaluate hsCRP levels in diabetic nephropathy and assess their correlation with HbA1c.

Study Design This was a cross-sectional, case-control study designed to evaluate inflammatory and renal biomarkers in patients with diabetic nephropathy compared to healthy controls. Sample Size A total of 100 subjects were enrolled. The study group comprised 50 clinically diagnosed diabetic nephropathy patients aged 40–90 years, on conservative management. The control group included 50 age- and sex-matched healthy individuals. Inclusion Criteria • Patients diagnosed with Type 2 Diabetes Mellitus (as per WHO criteria). • Urinary albumin excretion < 3 g/day. Exclusion Criteria • Acute illness including infectious diseases within the previous week. • Cigarette smoking. • Active immunological diseases. • Severe uncontrolled hypertension (blood pressure >160/100 mmHg). • Presence of malignancy. • Patients undergoing dialysis. • Use of medications such as statins, ACE inhibitors, angiotensin receptor blockers (ARBs), and non-steroidal anti-inflammatory drugs (NSAIDs). Methodology Two 24-hour urine samples were collected from all participants to assess urinary albumin excretion (UAE). UAE was evaluated through the colorimetric method, and the average of two measurements was taken. UAE was classified as follows: • Normoalbuminuria: <30 mg/24 hr • Microalbuminuria: 30–300 mg/24 hr • Macroalbuminuria: >300 mg/24 hr Highly sensitive C-reactive protein (hs-CRP) was estimated using an ultrasensitive solid-phase enzyme-linked immunosorbent assay (ELISA), with a sensitivity of 0.2 mg/L. hs-CRP levels were categorized into: • Low risk: <1 mg/L • Normal: 1–3 mg/L • High risk: >3 mg/L After 12 hours of fasting, blood samples were collected under aseptic conditions from the median cubital vein using sterile vacutainers. Laboratory investigations included: • Glycated hemoglobin (HbA1c), measured by borate affinity assay (NycoCard) • Serum creatinine, estimated by the Modified Jaffe’s method using an autoanalyzer • Complete hemogram • Urine routine and microscopy • Fasting and postprandial blood glucose • Renal function tests • Ultrasonography of the abdomen and pelvis Statistical Analysis Data were expressed as mean ± standard deviation for continuous variables and as frequency and percentage for categorical data. • An independent, two-tailed Student’s t-test was employed to compare the means. • Chi-square test or Fisher’s exact test was employed to analyze categorical variables. Statistical significance was assessed at the 5% level. Significance levels were defined as: • Suggestive significance (P = 0.05–0.10) • Moderate significance (P = 0.01–0.05) • Strong significance (P ≤ 0.01) All analyses were conducted using SPSS version 22.0, Stata 8.0, MedCalc version 9.0.1, and Systat version 13.0. Graphs and tables were generated using Microsoft Excel, Word, and GraphPad Prism. Ethical Approval Institutional Ethical Approval received prior to commencement of study.

Table 2: Comparison of gender distribution of patients studied. Gender Cases Controls No % No % Male 27 54 24 48 Female 23 46 26 52 Total 50 50 Table 3: Comparison of Blood sugars in two groups of patients Blood sugars Cases Controls Significance Mean ± Sd Mean ± Sd FBS (mg/dl) 188.96 ± 54.66 83.46 ± 12.71 t=13.29, p<0.0001** PPBS (mg/dl) 298.64 ± 86.48 86.48 ± 9.13 t=13.73, p<0.0001** Table 4: Comparison of duration of disease in years Duration in years Cases Controls No % No % 1-10 22 44 -- -- 11-20 26 52 -- -- 21-30 2 4 -- -- Total 50 100 -- -- Mean ± SD 13±4.69 -- -- Table 5: Comparison of Renal function tests in two groups of patients Renal function tests Cases Controls Significance Mean ± Sd Mean ± Sd Blood urea (mg/dl) 57.14 ± 19.06 19.06 ± 9.86 t =11.21, p<0.0001** Serum creatinine (mg/dl) 1.07 ± 0.25 0.72 ± 0.25 t=6.897, p<0.0001** Na+ 134.62 ± 5.56 136.68 ± 4.72 t=1.997, p-0.0486* K+ 4.36 ± 0.9 3.92 ± 0.54 t=2.925, p=0.0043** cl- 103.25 ± 15.64 98.06 ± 7.2 t=2.13, p=0.0356* ** Highly significant; *Significant Table 6: Comparison of Fundoscopy findings. Fundoscopy findings Cases Controls No % No % Normal 3 -- 47 94 NPDR 24 48 -- -- PDR 20 46 -- -- Vitreal degeneration 3 6 3 6 Total 50 50 Table 7: Comparison of hs-CRP (mg/L) in two groups of patients Hs-CRP (mg/L) Cases Controls Min-Max 0.5-8.1 0.1-2.2 Mean ± SD 3.96 ± 1.65 0.7 ± 0.41 95%CI 0.66-7.26 0.12-1.52 Significance t=13.55, p<0.0001, HS Table 8: Correlation of hs-CRP, HbA1c, UAE, and Disease Duration Correlation Pair Group r-value P-value Significance hs-CRP with UAE Cases 0.629 <0.0001** Highly Significant Controls -0.020 0.891 Not Significant hs-CRP with HbA1c Cases 0.741 <0.0001** Highly Significant Controls 0.151 0.296 Not Significant HbA1c with Duration of Disease Cases -0.059 0.684 Not Significant Table 9: Comparison of HbA1C and Correlation of hs-CRP according to gender Group HbA1C (mean ± SD) HbA1C Significance hs-CRP (Male) (mean ± SD) hs-CRP (Female) (mean ± SD) hs-CRP p-value Cases 12.65 ± 11.46 t = 4.55, p < 0.001 ** 12.74 ± 3.78 13.3 ± 5.64 0.566 Controls 5.26 ± 0.76 0.67 ± 0.43 0.73 ± 0.39 0.973 Table 10: Correlation of HbA1c with Gender HbA1c Cases (50) Controls (50) P-value Mean ± SD Mean ± SD Male 10.94±1.86 5.24±073 0.422 Female 14.65±1.63 5.28±0.72 0.1725 Table 11: Pearson correlation of age, duration, renal function tests with Hs-CRP, hs-CRP and urine albumin excretion and hs-CRP levels and HbA1c Correlation Pair Cases (50) Controls (50) r-value P-value r-value P-value hs-CRP with age -0.084 0.56 -0.039 0.788 hs-CRP with duration of disease 0.453 0.001** hs-CRP with UAE 0.629 <0.0001** -0.020 0.891 hs-CRP with HbA1c 0.741 <0.0001** 0.151 0.296 hs-CRP with FBS (mg/dl) 0.416 0.003* 0.059 0.686 hs-CRP with PPBS (mg/dl) 0.178 0.215 -0.076 0.602 hs-CRP with Blood urea (mg/dl) vs 0.168 0.244 0.137 0.344 hs-CRP with Serum creatinine (mg/dl) 0.345 0.012* 0.152 0.29 hs-CRP with Na+ -0.012 0.512 -0.019 0.898 hs-CRP with K+ 0.046 0.75 -0.04 0.785 hs-CRP with Cl- 0.294 0.038* 0.055 0.703 hs-CRP with Hb% 0.193 0.179 0.07 0.627 hs-CRP with TC -0.084 0.56 0.114 0.429 hs-CRP with ESR (mm/hr) -0.086 0.551 -0.273 0.05*

This study assessed the correlation between high-sensitivity C-reactive protein (hs-CRP), glycated hemoglobin (HbA1c), and urinary albumin excretion (UAE) in 50 patients with type 2 diabetic nephropathy and 50 non-diabetic controls aged ≥40 years. Significantly elevated hs-CRP levels in diabetic nephropathy patients (3.96 ± 1.65 mg/L) compared to controls (0.7 ± 0.41 mg/L; P < 0.0001) suggest a pronounced inflammatory state in diabetic nephropathy, consistent with findings by Roopakala et al. and Patil et al. (17,18). The observed positive correlation between hs-CRP and HbA1c (r = 0.741, P < 0.0001) supports the role of systemic inflammation in poor glycemic control and its contribution to diabetic nephropathy pathogenesis. Previous studies by Sarinnapakorn et al., Li et al., Amanullah et al., Gohel and Chacko have similarly reported elevated hs-CRP in patients with poor glycemic status and advancing microvascular complications (1-6). The study also revealed a strong positive correlation between hs-CRP and UAE (r = 0.629, P < 0.0001), reinforcing the association between inflammation and renal damage. These findings are supported by research from Choudhary et al. and the Insulin Resistance Atherosclerosis Study, which linked inflammatory markers with early increases in albuminuria (10,11). Furthermore, Stehouwer et al. and Navarro et al. proposed that chronic inflammation promotes endothelial dysfunction and glomerular injury, facilitating albumin leakage and contributing to diabetic nephropathy progression (12,13). The high prevalence of diabetic retinopathy (91%) among diabetic nephropathy cases in this study aligns with findings by Ahluwalia et al. (14), underscoring a shared pathophysiological pathway involving poor glycemic control, microvascular injury, and chronic inflammation. While our findings strongly support hs-CRP as a valuable biomarker for early diabetic nephropathy detection, some studies such as those by Otto et al. and Geetha Bhaktha et al. reported no significant correlation (15,16). These discrepancies may be attributed to smaller sample sizes, differences in study populations, or inclusion of patients in earlier disease stages. Nonetheless, the consistent association observed in our study between hs-CRP, HbA1c, and UAE reinforces the inflammatory basis of diabetic nephropathy and suggests that hs-CRP could serve as a non-invasive, cost-effective tool for early risk assessment and monitoring. Further large-scale, longitudinal studies are needed to validate its prognostic value and explore its potential in guiding anti-inflammatory therapeutic strategies in diabetic care.

This study demonstrates a progressive increase in hs-CRP levels in diabetic nephropathy patients, suggesting inflammation plays a key role beyond traditional metabolic and hemodynamic factors. The significant association between hs-CRP and urinary albumin excretion (UAE) indicates inflammation as a pathogenetic mechanism in diabetic nephropathy. Both low-grade inflammation (hs-CRP) and hyperglycemia (HbA1c) contribute to disease progression, reflecting ongoing renal damage. The observed positive correlation between hs-CRP and HbA1c reinforces the connection between inflammation and hyperglycemia in diabetic nephropathy. Therefore, monitoring hs-CRP alongside glycemic control may aid early intervention to prevent complications and preserve renal function. Moreover, addressing inflammation by preventing obesity and using antioxidants or anti-inflammatory treatments may offer therapeutic benefits. Additional research is necessary to better understand the contribution of intrarenal inflammation to the development of diabetic nephropathy.

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