EARLY BIOMARKER-BASED PREDICTION OF CARDIORENAL SYNDROME IN AMI PATIENTS: AN INDIAN PERSPECTIVE

Background: Cardiorenal Syndrome Type 1 (CRS1) is dened as acute kidney injury precipitated by acute cardiac dysfunction, especially acute myocardial infarction (AMI). Early recognition of CRS1 is essential to improve outcomes. Biomarkers such as B-type natriuretic peptide (BNP), high-sensitivity C-reactive protein (hsCRP), and estimated glomerular ltration rate (eGFR) may provide predictive value. Aim: To evaluate the role of BNP, hs-CRP, and eGFR in predicting CRS1 in AMI patients and to assess their combined diagnostic performance. Materials And Methods: This prospective observational study included 115 AMI patients admitted to SRN Hospital, Prayagraj. Demographic, clinical, and laboratory data were collected. BNP, hs-CRP, serum urea, creatinine, and eGFR were measured. CRS1 was diagnosed using KDIGO criteria. Logistic regression identied independent predictors, and diagnostic accuracy was assessed with ROC analysis. Results: CRS1 developed in 41 patients (35.7%). Independent predictors included age >65 years (OR 3.82), eGFR <60 mL/min (OR 6.15), BNP >800 pg/mL (OR 2.97), and urea >40 mg/dL (OR 8.43). hs-CRP was higher in CRS1 but was less predictive independently. ROC analysis showed AUCs of 0.664 (BNP), 0.672 (hs-CRP), 0.986 (eGFR), and 0.961 for the combined biomarker model. Conclusion: BNP, hs-CRP, and eGFR are valuable predictors of CRS1 in AMI patients. A combined biomarker model provides excellent predictive accuracy and should be incorporated into routine risk stratication.