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Association Between Systemic Immune-inflammation Index and Cardiovascular-kidney-metabolic Syndrome

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Journal Sci Rep
Specialty Science
Date 2024 Aug 19
PMID 39160192
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Abstract

This study aims to explore the relationship between the Systemic Immune-Inflammation Index (SII) and Cardiovascular-Kidney-Metabolic (CKM) Syndrome and its components. Data from the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2018 were analyzed. CKM Syndrome is defined as the coexistence of Cardiometabolic Syndrome (CMS) and Chronic Kidney Disease (CKD). The SII is calculated using the formula: SII = (Platelet count × Neutrophil count)/Lymphocyte count. Weighted logistic regression models were used to examine the associations between SII and CKM, as well as its specific components. Restricted cubic splines explored non-linear relationships, and piecewise linear regression models assessed threshold effects. A consistent positive correlation was observed between elevated SII levels and the likelihood of CKM and its related diseases. In the fully adjusted Model 3, an increase of 1000 units in SII was associated with a 1.48-fold increase in the odds of CKM (95% CI 1.20-1.81, p < 0.001). Quartile analysis revealed a dose-response relationship, with the highest quartile of SII (Q4) showing the strongest association with CKM and its components. Nonlinear analyses revealed inflection points for waist circumference, triglycerides, low HDL-C, and cardiometabolic syndrome at specific SII levels, indicating a change in the direction or strength of associations beyond these points. Conversely, a linear relationship was observed between SII and chronic kidney disease. The SII is positively correlated with the risk of CKM Syndrome and its individual components, with evidence of non-linear relationships and threshold effects for some components.

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References
1.
Ndumele C, Neeland I, Tuttle K, Chow S, Mathew R, Khan S . A Synopsis of the Evidence for the Science and Clinical Management of Cardiovascular-Kidney-Metabolic (CKM) Syndrome: A Scientific Statement From the American Heart Association. Circulation. 2023; 148(20):1636-1664. DOI: 10.1161/CIR.0000000000001186. View

2.
Seshasai S, Kaptoge S, Thompson A, Di Angelantonio E, Gao P, Sarwar N . Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011; 364(9):829-841. PMC: 4109980. DOI: 10.1056/NEJMoa1008862. View

3.
Matsushita K, van der Velde M, Astor B, Woodward M, Levey A, de Jong P . Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet. 2010; 375(9731):2073-81. PMC: 3993088. DOI: 10.1016/S0140-6736(10)60674-5. View

4.
Navarro-Gonzalez J, Mora-Fernandez C, de Fuentes M, Garcia-Perez J . Inflammatory molecules and pathways in the pathogenesis of diabetic nephropathy. Nat Rev Nephrol. 2011; 7(6):327-40. DOI: 10.1038/nrneph.2011.51. View

5.
Ridker P, Hennekens C, Buring J, Rifai N . C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med. 2000; 342(12):836-43. DOI: 10.1056/NEJM200003233421202. View