Metabolic-Associated Chronic Kidney Disease: A Pilot Study of 32 Patients for Validating the Diagnostic Criteria

 

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https://storage.unitedwebnetwork.com/files/1099/4a60a8b320bcd16c76d1a72a8a244486.pdf
Metabolic-Associated Chronic Kidney Disease: A Pilot Study of 32 Patients for Validating the Diagnostic Criteria

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Sourabh
Sharma
Sourabh Sharma drsourabh05@gmail.com Vardhman Mahavir Medical College and Safdarjung Hospital Nephrology New Delhi India *
Varun Kumar B varun.vims@gmail.com Dr. Pinnamaneni Siddhartha Institute of Medical Science and Research Foundation Nephrology Gannavaram India -
Neha Sharma drneha.bkn@gmail.com Vardhman Mahavir Medical College and Safdarjung Hospital Pathology New Delhi India -
Ananth Rao Ananthrao740@gmail.com KIMS Hospitals Nephrology Kurnool India -
Sudeep Prakash prakash.sudeep@gmail.com Command Hospital (Central Command) Nephrology Lucknow India -
Pritam Khomane pritam.khomane@gmail.com Jupiter Hospital Nephrology Thane India -
Himanshu Verma himanshu.verma16@gmail.com Vardhman Mahavir Medical College and Safdarjung Hospital Nephrology New Delhi India -
Sanjay Kalra brideknl@gmail.com Bharti Hospital Endocrinology Karnal India -
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Metabolic-associated chronic kidney disease (mCKD) represents a novel construct that recognizes CKD developing within a background of metabolic dysfunctions- diabetes, hypertension, obesity, dyslipidaemia, and metabolic dysfunction-associated steatotic liver disease (MASLD). The concept integrates metabolic and renal injury as a unified entity. This study aimed to apply and validate proposed diagnostic criteria for mCKD.

As a multi-centre cross-sectional study, thirty-two consecutive adults with evidence of CKD and at least two metabolic abnormalities were prospectively evaluated between January and May 2025. The diagnosis of mCKD required fulfilment of four diagnostic pillars: evidence of CKD, presence of ≥2 metabolic abnormalities, exclusion of primary renal disease, and at least one supportive feature (Table 1). All participants underwent comprehensive metabolic and renal evaluation including anthropometry, blood pressure, HbA1c, lipid profile, liver ultrasound, serum uric acid, bicarbonate, and urine albumin-creatinine ratio (UACR). Renal ultrasonography was used to rule out congenital or obstructive pathology. Data were analysed descriptively.

Table 1. Proposed Diagnostic Criteria for mCKD

Criterion

Details

Clinical Relevance

Evidence of CKD

• eGFR < 60 ml/min/1.73 m² for ≥3 months and/or
• Albuminuria > 30 mg/gm creatinine

Confirms chronic kidney damage independent of cause

Presence of ≥2 metabolic abnormalities

• Type 2 diabetes mellitus (T2DM)
• Hypertension (>140/90 mmHg or on antihypertensives)
• Obesity (BMI >30 kg/m² or >25 kg/m² in Asians) or Overweight (BMI >23 kg/m²)
• Dyslipidaemia (TG >150 mg/dL, HDL <40 mg/dL)
• MASLD (ultrasound evidence)

Defines metabolic milieu contributing to kidney dysfunction

Exclusion of primary glomerular disease

Absence of: anasarca, nephrotic-range proteinuria (>3 g/day), haematuria, rapid eGFR decline, autoimmune/vasculitic serology, or biopsy-proven glomerulopathy

Ensures kidney injury not primarily glomerular

Exclusion of primary tubulointerstitial disease

Absence of: congenital anomalies, shrunken/single kidneys, polycystic kidneys, or obstruction on imaging

Excludes structural or obstructive renal disease

Supportive features (≥1)

Hyperuricemia, metabolic acidosis, cardiovascular disease, stroke, or obstructive sleep apnoea

Strengthens diagnosis and indicates systemic metabolic involvement

The baseline demographic and metabolic profile of mCKD patients have been depicted in Table 2. The mean age was 54 ± 10.8 years; 19 (59%) were male. All patients satisfied the mCKD diagnostic triad. Hypertension (84%) and T2DM (78%) were most common, followed by dyslipidaemia (72%), obesity/overweight (63%), and MASLD (41%). Mean BMI was 28.6 ± 3.9 kg/m² and waist circumference 96 ± 8 cm. Renal indices confirmed moderate CKD with significant metabolic overlap. Mean serum creatinine was 1.8 ± 0.6 mg/dL, mean eGFR 52 ± 12 ml/min/1.73 m², and albuminuria >30 mg/gm in 22 (69%) patients. Supportive features included hyperuricemia (47%), metabolic acidosis (34%), and cardiovascular disease (28%). Renal and metabolic laboratory characteristics have been depicted in Table 3.

Table 2. Baseline Demographic and Metabolic Profile of mCKD Patients (n = 32)

Parameter

Mean ± SD / n (%)

Interpretation

Age (years)

54 ± 10.8

Middle-aged cohort typical for metabolic CKD

Male: Female

19:13

Male predominance

BMI (kg/m²)

28.6 ± 3.9

Overweight/obese range

Waist Circumference (cm)

96 ± 8

High central adiposity

Hypertension

27 (84%)

Most prevalent abnormality

Type 2 Diabetes Mellitus

25 (78%)

Major metabolic contributor

Dyslipidaemia

23 (72%)

Coexistent lipid disorder

Obesity/Overweight

20 (63%)

Common in Asians

MASLD

13 (41%)

Liver-metabolic linkage

Cardiovascular Disease

9 (28%)

Reflects systemic vascular risk

Obstructive Sleep Apnoea

4 (13%)

Associated metabolic comorbidity

Table 3. Renal and Metabolic Laboratory Characteristics in mCKD (n = 32)

Parameter

Mean ± SD / n (%)

Clinical Implication

Serum Creatinine (mg/dL)

1.8 ± 0.6

Mild to moderate renal dysfunction

eGFR (ml/min/1.73 m²)

52 ± 12

Stage 3 CKD predominant

Albuminuria (>30 mg/gm)

22 (69%)

Marker of renal endothelial injury

HbA1c (%)

7.9 ± 1.2

Suboptimal glycaemic control

Serum Triglycerides (mg/dL)

182 ± 48

Elevated in majority

HDL (mg/dL)

39 ± 8

Consistently low, reflecting dyslipidaemia

Serum Uric Acid (mg/dL)

7.8 ± 1.3

Reflects metabolic overload

Serum Bicarbonate (mEq/L)

21 ± 3

Tendency to metabolic acidosis

Hyperuricemia

15 (47%)

Common supportive marker

Metabolic Acidosis

11 (34%)

Confirms metabolic derangement

This pilot validation confirms the feasibility, reproducibility, and clinical relevance of the proposed diagnostic framework for mCKD. The clustering of multiple metabolic derangements with chronic kidney impairment reinforces the concept of mCKD as a distinct metabolic-renal phenotype. Early identification through these criteria allows clinicians to target metabolic pathways for kidney protection. Larger multicentric studies are needed for external validation, prognostic correlation, and therapeutic stratification.

Kewords