Diagnostic Value of a Novel Junctional Cardiometabolic Index for Identifying Reduced Left Ventricular Ejection Fraction in Chinese Patients with Heart Failure: A Retrospective Observational Study

<title>Abstract</title> <p>Background Identification of a patient's reduced left ventricular ejection fraction (LVEF) is critical for determining their risk and treatment strategy when they are diagnosed with heart failure. Nonetheless, traditional clinical and imaging markers may be unable to account for all the multifactorial processes involved in heart dysfunction. The aim of this study was to assess the diagnostic performance of a new biomarker called Novel Junctional Cardiometabolic Index (NJCI) in detecting reduced LVEF in comparison with NT-proBNP. Methods This retrospective cohort consisting of 338 patients suffering from heart failure was included in this study, who further categorized into those having a reduced left ventricular ejection fraction (LVEF &lt; 45%) and those with preserved LVEF (LVEF ≥ 45%). The NJCI was assessed by ln(total bilirubin) × ln(D-dimer)/albumin, combining the role of hepatic function, coagulation, and nutritional-inflammatory systems to form a composite score. The diagnostic utility of NJCI was compared with NT-proBNP, using ROC curve analysis and binary logistic regression analysis. Results In total, there were 338 patients with heart failure analyzed, which were divided into groups of reduced LVEF (&lt; 45%) and preserved LVEF (≥ 45%), according to echocardiography data. It was found out that patients with reduced LVEF had significantly elevated NJCI than those with preserved LVEF (p &lt; 0.001). The ROC analysis showed that NJCI had excellent discrimination potential for the identification of patients with reduced LVEF (AUC = 0.903, 95% CI: 0.871–0.934), compared with NT-proBNP, which had a significantly lower diagnostic efficiency (AUC = 0.773, 95% CI: 0.723–0.823). For the cutoff value, calculated using Youden’s index, 0.383, NJCI demonstrated high sensitivity (98.7%) and acceptable specificity (41.0%) for diagnosing of the target pathology. Binary logistic regression analysis proved NJCI to be an independent predictor of reduced LVEF even after adjusting for NT-proBNP (odds ratio = 5.95, 95% CI: 4.04–8.76, p &lt; 0.001). The model obtained was highly explanatory and informative (Nagelkerke R² = 0.572, classification accuracy = 81.4%). Conclusion The NJCI has been found to have better diagnostic accuracy than NT-proBNP in identifying low LVEF and could be considered an appropriate biomarker that can be used for risk stratification among HF patients.</p>