Prognostic value of Geriatric Nutritional Risk Index and systemic immune-inflammatory index in elderly patients with acute coronary syndromes
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Updated: Jul 4, 2025

Coronary Progenitor Cells and Soluble Biomarkers in Cardiovascular Prognosis after Coronary Angioplasty
Published on: January 28, 2020
Xing-Yu Zhu1,2, Kai-Jie Zhang1, Xiao Li1
1Graduate School of Hebei North University, Zhangjiakou, 075031, Hebei Province, China.
Insights
This study found that combining the Geriatric Nutritional Risk Index (GNRI) and Systemic Immunoinflammatory Index (SII) effectively predicts major adverse cardiovascular events (MACE) in elderly patients with acute coronary syndrome (ACS). The new model outperforms the GRACE score for this patient group.
Area of Science:
- Cardiology
- Geriatrics
- Biomarkers
Background:
- Acute coronary syndrome (ACS) in the elderly is associated with a high risk of major adverse cardiovascular events (MACE).
- Accurate risk stratification is crucial for guiding treatment and improving outcomes in these patients.
- Existing risk scores may not fully capture the complex interplay of factors contributing to MACE in older adults.
Purpose of the Study:
- To evaluate the predictive value of the Geriatric Nutritional Risk Index (GNRI) combined with the Systemic Immunoinflammatory Index (SII) for MACE risk.
- To develop and validate a novel clinical prediction model for MACE in elderly ACS patients.
- To compare the performance of the new model against the established GRACE score.
Main Methods:
- Retrospective review of 1202 elderly patients with ACS, divided into MACE and non-MACE groups.
- Analysis included sensitivity analysis with machine learning, restricted cubic spline approach for nonlinear relationships, and model construction using GNRI, SII, and Age.
- Model validation involved comparison with the GRACE score using subject work and recall curves, Integrated Discriminant Improvement Index (IDI), and Net Reclassification Index (NRI).
Main Results:
- Lower GNRI and higher SII were significantly associated with increased MACE risk (P < 0.001).
- The novel prediction model demonstrated superior performance with an Area Under the Curve (AUC) of 0.778 compared to the GRACE score's AUC of 0.744.
- The new model showed significant improvements in reclassification metrics (NRI = 0.5569, IDI = 0.0571, P < 0.001).
Conclusions:
- The combined GNRI and SII model is a simple, cost-effective, and valuable tool for predicting 1-year MACE risk in elderly ACS patients.
- This novel prediction model shows better accuracy and clinical utility than the GRACE score in the studied population.
- Integrating nutritional and inflammatory markers offers a promising approach for enhanced cardiovascular risk assessment in geriatric populations.
Abstract:
The objective of this study was to evaluate the predictive value of the Geriatric Nutritional Risk Index (GNRI) combined with the Systemic Immunoinflammatory Index (SII) for the risk of major adverse cardiovascular events (MACE) following percutaneous coronary intervention in elderly patients with acute coronary syndrome (ACS). We retrospectively reviewed the medical records of 1202 elderly patients with acute coronary syndromes divided into MACE and non-MACE groups according to whether they had a MACE. The sensitivity analysis utilized advanced machine learning algorithms to preliminarily identify the critical role of GNRI versus SII in predicting MACE risk. We conducted a detailed analysis using a restricted cubic spline approach to investigate the nonlinear relationship between GNRI, SII, and MACE risk further. We constructed a clinical prediction model based on three key factors: GNRI, SII, and Age. To validate the accuracy and usefulness of this model, we compared it to the widely used GRACE score using subject work and recall curves. Additionally, we compared the predictive value of models and GRACE scores in assessing the risk of MACE using the Integrated Discriminant Improvement Index (IDI) and the Net Reclassification Index (NRI). This study included 827 patients. The GNRI scores were lower in the MACE group than in the non-MACE group, while the SII scores were higher in the MACE group (P < 0.001). The multifactorial analysis revealed a low GNRI (OR = 2.863, 95% CI: 2.026-4.047, P = 0.001), High SII (OR = 3.102, 95% CI: 2.213-4.348, P = 0.001). The area under the curve (AUC) for the predictive model was 0.778 (95% CI: 0.744-0.813, P = 0.001), while the AUC for the GRACE score was 0.744 (95% CI: 0.708-0.779, P = 0.001). NRI was calculated to be 0.5569, with NRI + at 0.1860 and NRI- at 0.3708. The IDI was found to be 0.0571, with a P-value of less than 0.001. These results suggest that the newly developed prediction model is more suitable for use with the population in this study than the GRACE score. The model constructed using GNRI and SII demonstrated good standardization and clinical impact, as evidenced by the standard, DCA, and clinical impact curves. The study shows that combining GNRI and SII can be a simple, cost-effective, and valuable way to predict the risk of MACE within one year in elderly acute coronary syndromes.
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