European Journal of Cardiovascular Medicine

Chronic kidney disease (CKD) affects a substantial portion of the population in Indian subcontinent as well as globally. According to the Screening and Early Evaluation of Kidney Disease (SEEK) study, the prevalence of CKD in India is estimated at 17.2% using the MDRD equation ⁽¹⁾. Early diagnosis and effective management of CKD are essential in preventing the progression to end-stage renal disease and the need for renal replacement therapy.Various prognostic indicators have been studied to identify individuals at higher risk of CKD progression and poorer outcomes. However, the relationship between these prognostic indicators and specific renal pathologies is still unclear ⁽²⁾. This research proposal aims to evaluate the utility of prognostic indicators in predicting the progression and outcomes of chronic kidney disease, with a specific focus on their association with renal pathologies, using immunofluorescence findings and renal pathology as additional diagnostic tools.

Objectives:

1. To assess the association between estimated glomerular filtration rate (eGFR) and specific renal pathologies in patients with chronic kidney disease.
2. To evaluate the relationship between proteinuria levels and specific renal pathologies in patients with chronic kidney disease.
3. To investigate the role of serum uric acid levels in predicting the progression and outcomes of chronic kidney disease, with a focus on its association with renal pathology

This study was conducted as a retrospective, observational cohort study. Data has been collected from medical records of 50 CKD patients attending the nephrology OPD at MGM Medical college and Hospital, Kamothe, Navi Mumbai from the period of January 2022 to July 2023. The study aimed to evaluate the prognostic utility of 24-hour urinary protein, estimated glomerular filtration rate (eGFR), and uric acid levels in CKD patients, while also examining their correlations with renal pathology and immunofluorescence findings.

Inclusion Criteria:

• Adult Patients (≥17 years) with a clinical diagnosis of chronic kidney disease (CKD).
• Availability of comprehensive medical records.
• Patients who have undergone Kidney biopsy as part of their diagnostic evaluation.

Exclusion Criteria:

• Patients with insufficient or incomplete medical records.
• Patients with systemic conditions that could confound CKD progression, such as cancer or any syndromic disease or congenital anomaly.

Data Collection

Data were collected from patient medical records and included:

24-hour Urinary Protein: Measured using standard laboratory methods and expressed as grams per 24 hours.

eGFR: Calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation based on serum creatinine levels.

Uric Acid: Serum uric acid levels measured using automated laboratory assays.

Renal Pathology and Immunofluorescence

Renal biopsy samples were meticulously analysed by experienced pathologists for histopathological findings. Immunofluorescence staining was performed on renal biopsy specimens by using FITC labelled antibodies to identify immune complex deposition to rule out the differentials given by the clinicians.

The study included a total of 50 CKD patients who met the inclusion criteria. The mean age of the participants was 45.06 years with Males represent 58% of the patients, while females account for 42%.

The correlation analysis assessed the relationships between the key prognostic indicators—24-hour urinary protein, estimated glomerular filtration rate (eGFR), and uric acid—with renal pathology and immunofluorescence findings in patients with chronic kidney disease (CKD).

Relationship Between Proteinuria Levels and Renal Pathologies

The bar graph illustrates the distribution of moderate (0.3-3.5 g/day) and severe (>3.5 g/day) proteinuria cases based on final diagnosis. The data indicates that Diabetic Nephropathy had the highest frequency of severe proteinuria cases, while Tubulointerstitial Nephritis and Crescentic Glomerulonephritis also showed significant numbers of severe cases. Mean proteinuria levels (g/day) for each diagnosis were as follows: Glomerulopathy: 6.83, Acute Tubular Necrosis (ATN): 4.65, Acute Tubular Injury: 1.59, Amyloidosis: 1.10, Crescentic Glomerulonephritis: 3.74, Diabetic Nephropathy: 4.96, Focal Segmental Glomerulosclerosis (FSGS): 7.12, Hypertensive Nephrosclerosis: 1.39, Lupus Nephritis: 3.12, Membranoproliferative Glomerulonephritis (MPGN): 4.48, and Tubulointerstitial Nephritis: 5.77. These findings underscore the variability in proteinuria severity across different diagnoses, highlighting the need for tailored management strategies based on specific underlying conditions

Img.1 : Shows histopathology images from various kidney biopsies. a. Crescent formation noted in the glomerulus with dense interstitial inflammation b. Shows tubular atrophy and necrosis with acute intraluminal inflammatory infiltration, c. PAS positive deposits noted in glomerulus with thickened GBM in case of FSGS, d. Glomeruli shows endocapillary proliferation and hyalinization noted in adjacent vessel, e. MT stained slide shows vascular hyalinization and dense interstitial fibrosis in case of Diabetic Nephropathy with chronicity. 

Graph : The vertical bar graph above represents the impact of Tubulointerstitial Nephritis (TIN) on eGFR values, categorized by final diagnosis and class. The y-axis represents eGFR values (ml/min/1.73m²), while the x-axis lists the final diagnoses along with their respective classes. The bars are color-coded to distinguish between patients with TIN (light coral) and without TIN (light blue).

Graph : Impact of Tubulointerstitial Nephritis (TIN) on eGFR values by Final Diagnosis. Similar to the Graph 4, the "Without TIN" bars tend to be longer than the "With TIN" bars for most diagnoses, indicating higher eGFR values in patients without TIN. Specific diagnoses like Diabetic Nephropathy, Lupus Nephritis, and Crescentric Glomerulonephritis show significant differences between "With TIN" and "Without TIN" bars.

The graphs compare proteinuria and eGFR levels between patients with and without Tubulointerstitial Nephritis (TIN). Patients with TIN exhibit a broader range of proteinuria levels, with cases extending up to 12 gm/day, while those without TIN predominantly show lower proteinuria levels, clustering around the lower range with fewer cases exceeding 6 gm/day. Additionally, patients with TIN tend to have lower eGFR values, indicating more severe renal impairment, whereas patients without TIN display a wider distribution of higher eGFR values, suggesting better renal function. These comparisons highlight that Tubulointerstitial Nephritis is associated with higher proteinuria levels and more severe reductions in eGFR, reflecting greater kidney damage in these patients.

Graph: There is a negative correlation between 24hr Urinary Protein and eGFR. As the amount of 24hr Urinary Protein increases, eGFR values tend to decrease.This suggests that higher levels of protein in urine over 24 hours are associated with lower kidney function.

Role of Serum Uric Acid Levels in Chronic Kidney Disease

The study reveals a mean serum uric acid level of 7.97 (std=2.52), with acute tubular injury associated with an elevated mean level of 11.17, hinting at a potential link to worse kidney disease outcomes. The absence of standard deviation data for serum uric acid levels within individual pathologies limits the assessment of intra-group variability.

The graph compares Sr. Creatinine, Uric Acid, and eGFR levels across different kidney disease diagnoses. Higher Sr. Creatinine levels are observed in Crescentic Glomerulonephritis and FSGS, indicating more severe kidney impairment. Uric Acid levels are notably elevated in Hypertensive Nephrosclerosis and Acute Tubular Injury, suggesting a link to more severe disease outcomes. eGFR values, which indicate kidney function, are lowest in Glomerulopathy and Crescentic Glomerulonephritis, while Amyloidosis shows the highest eGFR, reflecting better kidney function or different disease characteristics. This illustrates distinct patterns in biomarker levels across various kidney conditions.

The table summarizes the mean and variability std(standard deviation) of Sr. Creatinine, Uric Acid, and eGFR levels across different kidney disease diagnoses. Amyloidosis shows the lowest mean Sr. Creatinine (0.39) and highest eGFR (114), indicating better kidney function. In contrast, Crescentic Glomerulonephritis has the highest mean Sr. Creatinine (8.17) and lowest eGFR (9.4), reflecting severe kidney impairment. Hypertensive Nephrosclerosis presents the highest mean Uric Acid (12.59). Variability in these biomarkers is notable in diseases like Diabetic Nephropathy (Sr. Creatinine std 2.85) and MPGN (eGFR std 57.86), highlighting the diverse progression of kidney conditions. This variability underscores the need for personalized treatment approaches based on specific disease characteristics.

Graph.  There is a general trend of negative correlation between Uric Acid and eGFR. As Uric Acid levels increase, eGFR values tend to decrease, although the relationship is not as strong or clear as in the first scatter plot. This indicates that higher levels of Uric Acid might be associated with lower kidney function, but the relationship is more scattered

Graph. There is a clear negative correlation between S. Creatinine and eGFR. As S. Creatinine levels increase, eGFR values tend to decrease. This suggests that higher levels of S. Creatinine are associated with lower kidney function (eGFR)

Correlation Analysis of Key Prognostic Indicators

24-hour Urinary Protein and Glomerular Damage: A significant positive correlation was observed between 24-hour urinary protein levels and glomerular damage, with a correlation coefficient of r = 0.45 (p < 0.01). This finding suggests that higher levels of urinary protein may be indicative of greater glomerular injury, which could contribute to the progression of CKD.

Association Between eGFR and Renal Pathologies

The study highlights significant associations between eGFR, proteinuria levels, and serum uric acid levels with various renal pathologies. Glomerulopathy exhibits a notably low mean eGFR of 14 ml/min/1.73m², indicating a strong correlation with diminished kidney function, whereas amyloidosis demonstrates a high mean eGFR of 114 ml/min/1.73m², potentially reflecting less severe kidney impairment or a different disease stage. The substantial standard deviation in eGFR (std=32.10) underscores considerable variability across different renal diagnoses.

Img.2 : Shows immune complex deposits positivity in direct immunofluorescence at various locations like mesangium, GBM, TBM and tubulointerstitial casts. Immune Depositis are seen in linear and granular patterns.

Graph   : The combined bar and line plot provides a comprehensive visualization of the relationship between the number of positive antibodies and various clinical parameters across different final diagnoses. The bar sections represent the levels of uric acid, S. Creatinine, and 24-hour urinary protein, while the lines depict eGFR and antibody count. Notably, diagnoses with higher antibody counts, such as Lupus Nephritis and FSGS, show elevated levels of uric acid and S. Creatinine, indicating a potential association with impaired kidney function. Conversely, diagnoses like Amyloidosis, with zero antibody count, demonstrate significantly lower uric acid and S. Creatinine levels and higher eGFR, suggesting better renal health. This integrated view underscores the potential impact of antibody positivity on kidney function and clinical parameters, highlighting the variability among different renal conditions.

The findings from this study offer important insights into the utility of 24-hour urinary protein, eGFR, and uric acid levels in the prognosis of chronic kidney disease (CKD). Elevated 24-hour urinary protein and decreased eGFR were found to be strongly associated with CKD progression and adverse patient outcomes. The study also uncovered novel insights regarding the relationship between uric acid levels and CKD progression, suggesting a potential role for uric acid as a marker of disease severity. These findings emphasize the need for a comprehensive approach to CKD diagnosis and management. CKD is a complex condition with numerous challenges in research, including variability in disease progression, making it difficult to predict outcomes and evaluate interventions; variability in patient populations, which complicates the generalization of study findings; and limited longitudinal data, restricting the ability to establish causality and assess long-term prognostic implications ^{(4, 5)}. Additionally, inconsistent terminology and classification lead to inconsistencies in study designs and comparisons, while selection bias in retrospective studies may limit the generalizability of findings. Variability in renal pathology findings, such as glomerular or tubulointerstitial changes, further complicates interpretation and correlation in CKD research ⁽⁴⁾. Limited sample size and diversity in CKD studies also restrict the applicability of findings to a broader CKD population ⁽⁵⁾. To address these limitations, future research should prioritize increasing sample sizes and diversity, using standardized terminology and classification systems, conducting prospective studies to establish causality and assess long-term outcomes, and promoting collaboration and data sharing among research institutions ^{(6, 7)}. These measures will improve the understanding of CKD and inform evidence-based interventions and strategies for its management and prevention.

The study reveals important correlation between kidney function tests, protein levels in urine, and uric acid levels with various kidney diseases. For example, patients with glomerulopathy have a very low average eGFR of 14 ml/min/1.73m², indicating poor kidney function, while those with amyloidosis have a high average eGFR of 114 ml/min/1.73m², suggesting better kidney function or a different disease stage. The wide range in eGFR (standard deviation of 32.10) shows significant variability among patients. Protein levels in urine also vary greatly, with glomerulopathy patients having the highest average protein level (6.83 gm), indicating severe kidney damage, and amyloidosis patients having the lowest (1.1 gm). The study also found that patients with acute tubular injury have high uric acid levels (average 11.17), which may indicate worse outcomes. However, the lack of detailed variability data for uric acid levels limits a deeper understanding. Overall, these findings highlight the complex relationships between kidney function markers and different kidney diseases, emphasizing the need for careful and comprehensive diagnosis and treatment approaches.

In practical terms, these insights suggest that clinicians should thoroughly assess CKD patients by considering 24-hour urine protein levels, eGFR, uric acid levels, and kidney pathology to get a clearer picture of the disease. The study shows distinct patterns among different kidney diseases, but variability within each group and a small sample size may impact the reliability of the conclusions. Future research with larger datasets could provide more definitive insights. Monitoring uric acid levels is particularly important as it can provide clues about disease progression and help guide treatment decisions. By integrating these factors, more effective and personalized strategies can be opted for patient treatment, leading to better care and outcomes for CKD patients.

Limitations of this study:

Retrospective Design: The study's retrospective nature may introduce biases related to data collection and patient selection

Sample Size and Diversity: The study's sample size and diversity may impact the ability to generalize findings to a broader CKD population

Renal Pathology Variability: Variability in renal pathology findings may pose challenges in interpreting correlations and drawing definitive conclusions

Longitudinal Data: The study's reliance on cross-sectional data limits the ability to establish causality and long-term prognostic implications

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