Back

Association Between Systemic Inflammation Response Index (SIRI) and Cardiovascular Disease Mortality in Individuals with Anemia: Findings from NHANES 1999-2018

Cheng, X.; Liu, L.; Wu, J.; Tian, Y.; Du, X.; Li, Z.; Lin, Y.

2025-10-24 cardiovascular medicine
10.1101/2025.10.21.25338494 medRxiv
Show abstract

BackgroundCardiovascular disease (CVD) is a leading cause of mortality in individuals with anemia. This study investigates the association between the Systemic Inflammation Response Index (SIRI) and CVD mortality in this population. MethodsData from 3,212 participants with confirmed anemia from the NHANES 1999-2018 were analyzed. Participants were stratified by SIRI levels. Univariate and multivariate Cox regression analyses assessed the relationship between SIRI and CVD mortality, with subgroup analyses for various demographic and clinical factors. ResultsHigher SIRI levels were associated with older age, male gender, and increased prevalence of chronic conditions, such as chronic kidney disease, diabetes, and hypertension. CVD mortality was significantly higher in the highest SIRI group (15.7%) compared to the lowest (4.9%, p < 0.001). SIRI was a significant predictor of CVD mortality (HR: 1.3, 95% CI: 1.25-1.36, p < 0.001). Participants in the highest SIRI quartile had a markedly increased risk (HR: 4.24, 95% CI: 2.96-6.07, p < 0.001). A non-linear relationship was observed with a threshold at SIRI 0.244, above which the risk steeply increased (HR: 4.807, 95% CI: 2.945-7.845, p < 0.001). ConclusionsHigher SIRI levels are strongly associated with increased CVD mortality in individuals with anemia, with a non-linear relationship. These findings highlight the role of systemic inflammation in CVD risk, suggesting that SIRI may be a valuable biomarker in this population.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.