Evidence map›Paper›PMID 42495078›Full record

ArticleFrontiers in cardiovascular medicine2026

Systemic immune-inflammation Index is an independent risk factor for Major adverse cardiovascular events in patients with coronary artery ectasia.

Deguang Wang, Jingxian Xing, Zhaoqing Xie, Yunlong Zhang, Yunjie Wu, Tao Geng

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Article in Frontiers in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Deguang WangDepartment of Coronary Heart Disease 7, Cangzhou Central Hospital, Cangzhou, China.
Jingxian XingDepartment of Coronary Heart Disease 7, Cangzhou Central Hospital, Cangzhou, China.
Zhaoqing XieDepartment of Coronary Heart Disease 7, Cangzhou Central Hospital, Cangzhou, China.
Yunlong ZhangDepartment of Coronary Heart Disease 7, Cangzhou Central Hospital, Cangzhou, China.
Yunjie WuDepartment of Coronary Heart Disease 7, Cangzhou Central Hospital, Cangzhou, China.
Tao GengDepartment of Coronary Heart Disease 7, Cangzhou Central Hospital, Cangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Reliable biomarkers for long-term risk stratification in coronary artery ectasia (CAE) remain limited. The systemic immune-inflammation index (SII), derived from routine hematological parameters, reflects the balance between inflammation and immune status and has demonstrated prognostic value in various cardiovascular conditions. Objective: This study aimed to evaluate whether SII independently predicts major adverse cardiovascular events (MACE) in patients with angiographically confirmed CAE. Methods: In this retrospective cohort study at Cangzhou Central Hospital, 200 consecutive patients with CAE were enrolled and followed for a median duration of 30 months. SII was calculated as platelet count×neutrophil count divided by lymphocyte count. The primary endpoint was MACE, defined as a composite of cardiovascular death, nonfatal myocardial infarction, ischemic stroke, and target vessel revascularization. Receiver operating characteristic (ROC) curve analysis was performed to determine the optimal SII cut-off value. Kaplan-Meier survival analysis and Cox proportional hazards regression models were used to assess the association between SII and outcomes. Incremental predictive value was evaluated by comparing model discrimination and reclassification indices. Results: During follow-up, 18% of patients experienced MACE. Baseline SII levels were significantly higher in patients who developed adverse events. ROC analysis demonstrated good discriminatory ability of SII for predicting MACE (AUC 0.81), with an optimal cut-off value of 645. Kaplan-Meier analysis showed significantly lower event-free survival in patients with high SII levels. In multivariate Cox regression analysis, SII remained independently associated with MACE both as a continuous variable (adjusted HR 1.72 per SD increase) and as a categorical variable (adjusted HR 2.48 for high vs. low SII). Addition of SII to a baseline clinical model significantly improved discrimination (C-statistic increase from 0.72 to 0.83) and enhanced risk reclassification. Conclusion: Elevated systemic immune-inflammation index is an independent predictor of major adverse cardiovascular events in patients with coronary artery ectasia. Incorporation of SII into clinical risk assessment models significantly improves prognostic accuracy, suggesting that this readily available biomarker may serve as a valuable tool for risk stratification in this high-risk population.

Indexed as

coronary artery ectasiainflammationmajor adverse cardiovascular eventsrisk stratificationsystemic immune-inflammation index

Identifiers

PMID42495078
PMCPMC13391856

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.