Identification of inflammatory phenotypes of heart failure using systemic inflammation response index (SIRI): A cross-sectional analysis of NHANES 2021-2023

Objective To examine the associations between systemic inflammation response index (SIRI) and comorbid states of heart failure (HF), including anemia, cancer, coronary artery disease (CAD), chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), diabetes mellitus (DM), hyperlipidemia (HLP), hypertension (HTN), obesity, and stroke to identify inflammatory phenotypes of HF. Method HF comorbid states were obtained from the National Health and Nutrition Examination Survey (NHANES) 2021–2023 dataset. Prevalence rates of single and dual-comorbid states of HF were calculated for participants with SIRI below and above the median value. Odds ratios and confidence intervals were estimated to examine the strength of associations. Receiver Operating Curve (ROC) analyses were performed for single and dual comorbid states of HF to determine the respective area under the ROC curve (AUC), confidence intervals, and p-values. Results This study analyzed data from 7,582 NHANES participants. Median SIRI was 0.94. Nearly all single and dual-comorbid states of HF showed significantly higher prevalence rates and odds ratios for the participants with SIRI above 0.94, with high ORs for some of them, such as HF plus CAD plus CKD (OR = 14.03; 95% CI = 1.87–105.17), HF plus CAD plus stroke (OR = 12.46; 95% CI = 1.65–94.05), and HF plus CKD plus anemia (OR = 8.85; 95% CI = 1.12–69.95). In the ROC analysis, nearly all single- and dual-comorbid states of HF showed significant associations with SIRI. However, some of them had strong associations, such as HF plus stroke plus cancer (AUC = 0.833; 95% CI = 0.742–0.925) HF plus stroke plus DM (AUC = 0.808; 95% CI = 0.743–0.873), and HF plus stroke plus CAD (AUC = 0.791; 95%CI = 0.707–0.875). Conclusion This cross-sectional study suggests that systemic inflammation in HF could be measured by SIRI. Though SIRI cannot be considered an established biomarker of inflammatory phenotypes of HF, it could be used to define inflammatory phenotypes of HF and optimize therapy for HF patients. Inflammatory phenotypes of HF converge with the cardiovascular-kidney-metabolic syndrome, cancer, and COPD.