ArticleImmunity, inflammation and disease2024
Prognosis impact of multiple novel lymphocyte-based inflammatory indices in patients with initially diagnosed coronary artery disease.
Article in Immunity, inflammation and disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Immunosenescence biomarkers and outcomes in isolated coronary artery bypass grafting.JTCVS open · 2026Article
- Limited Utility of Lymphocyte-Based Inflammatory Indices in Troponin-Negative Unstable Angina Pectoris.Journal of cardiovascular development and disease · 2026Article
- Platelet Apoptosis in Patients with Coronary Artery Disease Before and After CABG.International journal of molecular sciences · 2026Article
- Systemic Immune-Inflammation Index Outperforms Conventional Inflammatory Markers in Predicting Cardiovascular Outcomes in Heart Failure with Preserved Ejection Fraction.Journal of inflammation research · 2026Article
- The systemic immune-inflammation index in coronary heart disease: a narrative review of thromboinflammation, phenotype-dependent utility, and clinical translation.Frontiers in cardiovascular medicine · 2026Review
- The Monocyte-to-Lymphocyte Ratio Exhibits A Superior Prognostic Value in Patients with Newly Diagnosed Acute Coronary Syndrome.Reviews in cardiovascular medicine · 2025Article
- Divergent Immune Pathways in Coronary Artery Disease and Aortic Stenosis: The Role of Chronic Inflammation and Senescence.International journal of molecular sciences · 2025Article
- The Clinical Value of Systemic Immune Inflammatory Index in Predicting the Prognosis of Patients with Bloodstream Infection.Journal of inflammation research · 2025Article
- Prognosis impact of multiple novel lymphocyte-based inflammatory indices in patients with initially diagnosed coronary artery disease.Immunity, inflammation and disease · 2024Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundThis study aimed to evaluate six novel lymphocyte-based inflammatory markers (neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio, platelet-lymphocyte ratio [PLR], systemic immune inflammation index [SII], systemic inflammatory response index, and systemic immune inflammation response index [SIIRI]) in patients with newly diagnosed coronary artery disease [CAD].
methodsA total of 959 patients newly diagnosed with CAD and underwent diagnostic coronary angiography were enrolled in this study and followed for major adverse cardiovascular events (MACEs), including cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke. The best cutoff value was used to compare the six indicators. Cox risk regression analysis evaluated the relationship between novel lymphocyte-based inflammatory markers and MACEs in newly diagnosed CAD patients.
resultsDuring a mean follow-up period of 33.3 ± 9.9 months, 229 (23.9%) MACEs were identified. Multivariate Cox regression analysis showed that only SIIRI (hazard ratio [HR]: 5.853; 95% confidence interval [CI]: 4.092-8.371; p < .001) and PLR (HR: 1.725; 95% CI: 1.214-2.452; p = .002) were independent predictors of MACEs. Nevertheless, following the adjustment for covariates, only the SIIRI was found to be a significant predictor MACEs and its corresponding specific endpoint occurrences. The predictive ability of the model was improved when six different inflammatory markers were added to the basic model established by traditional risk factors, namely, the C-index increased, and the SIIRI increased most significantly (AUC: 0.778; 95% CI: 0.743-0.812; p < .001). However, among the six novel inflammatory markers, only SIIRI had improved net reclassification improvement (NRI) and integrated discrimination improvement (IDI) (NRI: 0.187; 95% CI: 0.115-0.259, p < .001. IDI: 0.135; 95% CI: 0.111-0.159, p < .001), which was superior to the basic model established by traditional risk factors.
conclusionsSIIRI is independent predictor of MACEs in newly diagnosed CAD patients. SIIRI was superior to other measures in predicting MACEs. The combination of SIIRI and traditional risk factors can more accurately predict MACEs.
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