Photo Credit: Pitchayanan Kongkaew

The following is a summary of “Role Of Cut-Off Values For Creatinine, Blood Urea Nitrogen, And Uric Acid In Prognostic Assessment Of Chronic Heart Failure: A Retrospective Cohort Study,” published in the March 2025 issue of the BMC Cardiovascular Disorders by Xu et al.

Chronic heart failure (CHF) remains a significant public health concern, contributing to high mortality rates, diminished quality of life, and increased healthcare burdens. Early identification of patients with high risk through reliable biomarkers and clinical parameters is crucial for optimizing management strategies and improving long-term outcomes. This retrospective cohort study analyzed 297 patients diagnosed with CHF to determine key prognostic indicators. Data on demographics, laboratory findings, echocardiographic parameters, and comorbidities were collected. Receiver operating characteristic (ROC) curve analysis was employed to establish optimal cut-off values for serum creatinine (Scr), blood urea nitrogen (BUN), and uric acid (UA), while Kaplan-Meier survival analysis and multivariate Cox regression models were utilized to identify independent risk factors associated with poor prognosis. 

The ROC analysis determined optimal threshold values for Scr, BUN, and UA at 101.5 µmol/L, 8.61 mmol/L, and 462 µmol/L, respectively, with area under the curve (AUC) values of 0.602 for Scr and UA and 0.674 for BUN, indicating their predictive relevance. Kaplan-Meier survival curves showed significant stratification based on these cut-off points. Cox regression analysis identified several independent risk factors for poor prognosis, including 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), and UA ≥ 462 µmol/L (HR = 2.625, 95% CI: 1.631–4.228, P < 0.001). 

Additional risk factors included male sex (HR = 1.764, 95% CI: 1.067–2.915, P = 0.027) and absence of coronary heart disease (CHD), which was associated with a 1.905-fold increased risk of poor prognosis (P = 0.033). Conversely, hyperlipidemia (HR = 0.567, 95% CI: 0.351–0.916, P = 0.02) and prior hospitalization (HR = 0.480, 95% CI: 0.280–0.826, P = 0.008) appeared to be protective factors. Subgroup analysis further highlighted that male sex was a significant risk factor among female patients (OR = 2.424, P < 0.001), and advanced age also increased risk (OR = 1.026, P = 0.036). New York Heart Association (NYHA) classification strongly correlated with prognosis, as NYHA class IV patients exhibited a 0.42-fold risk reduction compared to class III patients (P < 0.001), while class III had a 0.307-fold risk reduction relative to class II (P = 0.016). These findings underscore the importance of Scr, BUN, and UA as prognostic biomarkers and provide critical insights for risk stratification in CHF management. 

By integrating these parameters into routine clinical assessments, healthcare providers can better identify patients at high risk and tailor therapeutic interventions accordingly. This study contributes to a growing body of evidence supporting biomarker-driven CHF management and lays the groundwork for future research aimed at refining predictive models and improving patient outcomes.

Source: bmccardiovascdisord.biomedcentral.com/articles/10.1186/s12872-025-04675-y