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Published on: January 28, 2020
The Systemic Immune-Inflammation Index as a Predictor of Clinical Outcomes in Chronic Coronary Syndrome: Influence of
Luwa Gao1, Xinbo Bai1, Yuqi Zhao1
1Department of Cardiology, Cardiovascular Disease Center, Jiangsu Key Laboratory for Cardiovascular Information and Health Engineering Medicine, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, People's Republic of China.
Insights
The Systemic Immune-Inflammation Index (SII) predicts adverse outcomes in chronic coronary syndrome (CCS) patients, especially those with diabetes. Elevated SII combined with diabetes indicates the highest risk for major adverse cardiovascular and cerebrovascular events (MACCEs).
Area of Science:
- Cardiology
- Inflammation Research
- Diabetology
Background:
- Systemic inflammation is crucial in coronary heart disease prognosis.
- The Systemic Immune-Inflammation Index (SII) measures inflammatory status and immune balance.
- The prognostic value of SII in chronic coronary syndrome (CCS), particularly in diabetic patients, requires further investigation.
Purpose of the Study:
- To investigate the predictive value of SII in CCS patients.
- To examine if diabetes modifies the relationship between SII and adverse cardiovascular outcomes.
Main Methods:
- Retrospective analysis of 853 CCS patients undergoing coronary angiography (2022).
- Stratification by SII and glycometabolic status.
- Evaluation of Major Adverse Cardiovascular and Cerebrovascular Events (MACCEs) using Kaplan-Meier, Cox proportional hazard, and restricted cubic spline models.
Main Results:
- Higher SII independently predicted MACCEs in the overall cohort (HR 1.63) and significantly in diabetic patients (HR 2.24).
- No significant association was found between SII and MACCEs in non-diabetic individuals.
- Elevated SII combined with diabetes identified the subgroup with the highest MACCEs risk.
Conclusions:
- Elevated SII is an independent predictor of adverse outcomes in CCS patients.
- The prognostic effect of SII is stronger in diabetic CCS patients.
- SII may serve as a valuable tool for personalized risk stratification in CCS, especially for diabetic individuals.
Background:
Systemic inflammation plays a critical role in the prognosis of coronary heart disease, and the Systemic Immune-Inflammation Index (SII) reflects both inflammatory status and immune balance. While elevated SII has been associated with adverse outcomes, its prognostic value in chronic coronary syndrome (CCS), particularly among diabetic patients, remains unclear. Hyperglycemia-induced inflammation, which enhances neutrophil activation and platelet reactivity, contributes to a more severe atherosclerosis burden in diabetes. This study investigated the predictive value of SII in CCS patients and examined whether diabetes modifies this relationship.
Methods:
From January to December 2022, a cohort of 853 individuals with CCS who underwent coronary angiography was retrospectively analyzed and stratified by SII and glycometabolic status. This retrospective cohort study utilized fully anonymized data from the Coronary Heart Disease Database of Nanjing Drum Tower Hospital. Major adverse cardiovascular and cerebrovascular events (MACCEs), comprising cardiovascular death, nonfatal myocardial infarction, heart failure, ischemia-driven revascularization, and stroke, served as the primary endpoints. Kaplan-Meier analysis, Cox proportional hazard models, and restricted cubic spline (RCS) models were performed to evaluate the independent and combined effects of SII and glycometabolic status on clinical outcomes.
Results:
Over a median follow-up period of 36 months, 85 patients (9.96%) experienced MACCEs. Higher log-transformed SII remained an independent predictor of MACCEs in the whole cohort (hazard ratio (HR) 1.63, 95% confidence interval (CI) 1.05-2.55, P = 0.031) and particularly among patients with diabetes (HR 2.24, 95% CI 1.31-3.82, P = 0.003) after full adjustment. However, there was no statistical significance among non-diabetic individuals (P = 0.772). Comparable findings were observed when SII was analyzed using the optimal cutoff value or quartiles. RCS analysis showed that MACCEs risk appeared to increase linearly with rising SII levels among diabetic patients. Furthermore, the combination of elevated SII and diabetes identified the subgroup with the poorest prognosis (P< 0.01).
Conclusion:
Elevated SII levels independently predict adverse outcomes in patients with CCS, with a stronger prognostic effect among those with diabetes. These findings suggest that SII may serve as a simple and accessible marker for personalized risk stratification in CCS, especially in patients with diabetes.
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