The levels of systemic inflammatory markers exhibit a positive correlation with the occurrence of heart failure: a cross-sectional study from NHANES
Year: 2024
Type: article
Study design: Observational Study
Abstract: Background: We conducted a large-scale epidemiological analysis to investigate the associations between systemic inflammation markers and heart failure (HF). Our aim is to identify potential biomarkers for early detection of HF. Methods: A cross-sectional study was conducted using data from the National Health and Nutrition Examination Survey. We investigated the associations between five systemic inflammation markers (neutrophil to lymphocyte ratio [NLR], platelet to lymphocyte ratio [PLR], systemic immune inflammation index [SII], system inflammation response index [SIRI], and aggregate index of systemic inflammation [AISI]) and the risk of HF. Results: The prevalence rates of HF exhibited a gradual increase across increasing logNLR, logPLR, logSII, logSIRI, and logAISI tertiles. Compared to those in the highest tertiles of logNLR, logSII, logSIRI, and logAISI had a 1.579-fold, 1.341-fold, 1.956-fold, and 1.499-fold increased risk of HF compared to those in the lowest tertile respectively. Conversely, there was no significant correlation between logPLR and HF risk among subjects in the highest tertile. The restricted cubic splines (RCS) analysis revealed a non-linear relationship between the elevation of systemic inflammation markers and HF prevalence. Specifically, a per standard deviation increase in any of these variables is associated with a respective 45%, 29%, 28%, 44% and 29% increase in HF prevalence. The receiver operating characteristic (ROC) analysis demonstrated favorable sensitivity and specificity of these systemic inflammation markers in detecting the presence of HF. Conclusion: Our cross-sectional study demonstrates significant positive correlations between the NLR, PLR, SII, SIRI, and AISI with the incidence of HF.
Institutions: Ningbo University, Ningbo Medical Center Lihuili Hospital
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,295
OpenAlex ID: W4403342726
