Predictive value of initial Lp-PLA2, NT-proBNP, and peripheral blood-related ratios for heart failure after early onset infarction in patients with acute myocardial infarction

Objective: To analyze the predictive value of lipoprotein-associated phospholipase A2 (Lp-PLA2), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and peripheral blood-related ratios at the initial diagnosis for heart failure (HF) after early-onset infarction in patients with acute myocardial infarction (AMI). Methods: This retrospective analysis included 151 patients first diagnosed with AMI at Xianyang Central Hospital from February 2020 to February 2023. Patients were classified into two groups: those who developed HF during hospitalization (HF group, n=45) and those who did not (non-HF group, NHF, n=106). Differences in Lp-PLA2, NT-proBNP, and peripheral blood ratios at initial diagnosis were compared between the groups. Binary logistic regression was used to identify independent risk factors for HF, and a nomogram model was developed based on these factors. Results: HR (P=0.032), C-reactive protein (CRP) (P<0.001), alanine aminotransferase (ALT) (P=0.015), coronary artery lesion score (CALDS) (P<0.001), D-dimer (D-D) (P=0.021), neutrophil-to-lymphocyte ratio (NLR) (P<0.001), Lp-PLA2 (P<0.001), and NT-proBNP (P<0.001) were significantly higher in the HF group than in the NHF group. Left ventricular end-systolic diameter (LVESD) (P<0.001) and left ventricular end-diastolic diameter (LVEDD) (P<0.001) were significantly lower in the HF group. Multifactorial logistic regression identified HR (P=0.034), CRP (P=0.028), CALDS (P=0.007), NLR (P=0.001), Lp-PLA2 (P=0.001), and NT-proBNP (P=0.002) as independent predictors of HF. The AUCs for NLR, Lp-PLA2, and NT-proBNP were 0.806, 0.849, and 0.780, respectively. The nomogram model achieved an AUC of 0.964, significantly outperforming individual indicators per Delong's test, highlighting its superior predictive efficacy. Conclusion: HR, CRP, CALDS, NLR, Lp-PLA2, and NT-proBNP were identified as independent predictors of HR post-AMI myocardial infarction. The constructed nomogram model provides an effective tool for early clinical identification of high-risk patients, potentially improving prognosis and guiding therapeutic strategies.