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The role of cut-off values for creatinine, blood urea nitrogen, and uric acid in prognostic assessment of chronic heart failure: a retrospective cohort study
The role of cut-off values for creatinine, blood urea nitrogen, and uric acid in prognostic assessment of chronic heart failure: a retrospective cohort study
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The role of cut-off values for creatinine, blood urea nitrogen, and uric acid in prognostic assessment of chronic heart failure: a retrospective cohort study
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The role of cut-off values for creatinine, blood urea nitrogen, and uric acid in prognostic assessment of chronic heart failure: a retrospective cohort study
The role of cut-off values for creatinine, blood urea nitrogen, and uric acid in prognostic assessment of chronic heart failure: a retrospective cohort study

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The role of cut-off values for creatinine, blood urea nitrogen, and uric acid in prognostic assessment of chronic heart failure: a retrospective cohort study
The role of cut-off values for creatinine, blood urea nitrogen, and uric acid in prognostic assessment of chronic heart failure: a retrospective cohort study
Journal Article

The role of cut-off values for creatinine, blood urea nitrogen, and uric acid in prognostic assessment of chronic heart failure: a retrospective cohort study

2025
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Overview
Background Chronic heart failure (CHF) significantly harms patients and society, causing high mortality and reduced quality of life, straining healthcare systems; early identification and intervention are crucial for improving long-term prognosis. Methods This retrospective cohort study involved 297 CHF patients. After collecting data on demographics, lab results, echocardiography, and comorbidities, ROC analysis was used to determine optimal cut-off values, followed by survival analysis and multivariate Cox regression to identify poor prognosis risk factors. Results ROC analysis set optimal cut-offs for Scr, BUN, and UA at 101.5 µmol/L, 8.61 mmol/L, and 462 µmol/L, with AUCs of 0.602 (Scr, UA) and 0.674 (BUN). Kaplan-Meier analysis showed significant curve separation, while Cox regression identified risk factors for poor prognosis: Scr ≥ 101.5 µmol/L (HR = 2.209, 95% CI 1.372–3.557, P  = 0.001), BUN ≥ 8.61 mmol/L (HR = 3.709, 95% CI 2.270–6.061, P  < 0.001), UA ≥ 462 µmol/L (HR = 2.625, 95% CI 1.631–4.228, P  < 0.001), male sex(HR = 1.764, 95% CI 1.067–2.915, P  = 0.027), hyperlipidemia (HR = 0.567, 95% CI 0.351–0.916, P  = 0.02), and re-hospitalization(HR = 0.480, 95% CI 0.280–0.826, P  = 0.008). Subgroup analysis indicates that male gender is a significant risk factor for females (OR:2.424, P  < 0.001); and age also posed a risk (OR:1.026, P  = 0.036). NYHA class IV had an OR of 0.42 compared to class III ( P  < 0.001), and class III had an OR of 0.307 compared to class II ( P  = 0.016). Patients without CHD had a 1.905-fold increased risk of poor prognosis ( P  = 0.033). Conclusion This study highlights key characteristics, assessment parameters, and risk factors for CHF patients, emphasizing the importance of Scr, BUN, and UA cut-off levels in management and guiding future research.