ArticleFrontiers in cardiovascular medicine2026
Predictive value of combined estimated plasma volume status and neutrophil-to-lymphocyte ratio for cardiovascular mortality in patients with acute myocardial infarction with heart failure.
Article in Frontiers in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: Estimated plasma volume status (ePVS) and neutrophil-to-lymphocyte ratio (NLR) are novel biomarkers reflecting hemodynamic load and systemic inflammatory immune status, respectively. This study aimed to explore the prognostic value of combined ePVS and NLR for cardiovascular mortality in patients with heart failure (HF) complicating acute myocardial infarction (AMI). Methods: This retrospective observational study consecutively enrolled patients diagnosed with AMI complicated by HF at Putian University Affiliated Hospital from January 2020 to June 2024. Admission hemoglobin and hematocrit levels were used to calculate ePVS, while routine blood test parameters were applied to determine NLR. The primary endpoint was cardiovascular mortality within two years after AMI. Cox proportional hazards regression models were constructed to analyze the associations of ePVS and NLR with clinical endpoints. The predictive efficacy of single and combined ePVS and NLR was comprehensively evaluated using the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: A total of 2046 patients were ultimately included. During a mean follow-up of 819 days, endpoint events occurred in 14.90% of the study population. Univariate Cox regression analysis demonstrated that ePVS served as a strong risk factor for cardiovascular mortality (HR = 1.571, 95% CI: 1.502-1.642, Conclusion: ePVS and NLR represent valuable prognostic biomarkers for cardiovascular mortality in AMI patients. The combination of ePVS and NLR significantly improves predictive performance and facilitates precise risk stratification.
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