ArticlePloS one2025
Comparison of systemic immunoinflammatory biomarkers for assessing severe abdominal aortic calcification among US adults aged≥40 years: A cross-sectional analysis from NHANES.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Prognostic value of the aggregate index of systemic inflammation in predicting in-hospital adverse outcomes among patients with ST-segment elevation myocardial infarction undergoing primary percutaneous intervention.BMC cardiovascular disorders · 2026Article
- Article
- The association between hematological inflammatory markers and atrial fibrillation recurrence after radiofrequency ablation.Frontiers in medicine · 2026Article
- Inflammation-Based Cell Ratios Beyond White Blood Cell Count for Predicting Postimplantation Syndrome After EVAR and TEVAR.International journal of molecular sciences · 2025Article
- AISI and MASLD: a nonlinear association in U.S. adults (NHANES 2017-2020).BMC gastroenterology · 2025Article
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Authors and funding
8 authors.
Funding
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Abstract
objectiveSeveral novel biomarkers, including the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), aggregate index of systemic inflammation (AISI), platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and monocyte-lymphocyte ratio (MLR), are linked to the systemic immunity inflammation response and the odds and severity of abdominal aortic calcification (AAC). However, still no previous research has systematically compared their association with severe AAC.
methodsThis study utilized a cross-sectional approach, examining a cohort of 3,047 adults from National Health and Nutrition Examination Survey (NHANES). Weighted logistic regression was utilized to investigate the associations between a range of immunoinflammatory biomarkers and the likelihood of severe AAC. Segmented regression and limited cubic spline models were used in the investigation to characterize the threshold effects and non-linear correlations. Additionally, subgroup and interaction tests, Spearman correlation, least absolute shrinkage, and selection operator regression studies were conducted.
resultsThe 3047 participants included in this study had a mean age of 58.63 years and 51.79% were female. After fully adjusting for all covariates, the ln-SIRI (OR 1.39 [CI 1.10-1.74], P = 0.005), ln-AISI (OR 1.26 [1.03-1.53], P = 0.024), and ln-MLR (OR 1.62 [1.15-2.30], P = 0.006) were significantly correlated with the odds of severe AAC. A non-linear dose-response relationship was observed between ln-SII and severe AAC. Additional subgroup analyses revealed that this relationship was more evident in the diabetic population. Additionally, MLR (AUC = 0.644) predicted the prevalence of severe AAC better than other biomarkers, and the prediction model constructed in conjunction with screened clinical indicators showed good predictive value (AUC = 0.853).
conclusionsIn this study, we comprehensively evaluated and compared the associations between six biomarkers and severe AAC, and developed a clinical prediction model using the MLR with the best predictive effect. However, cohort studies and model validation are still needed in the future to further confirm their relationship.
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