Prognostic value of Geriatric Nutritional Risk Index and systemic immune-inflammatory index in elderly patients with acute coronary syndromes

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.

Figure 1

(A) The Pearson analysis of MACE in acute coronary syndromes in the elderly and related factors. (B) SHAP Summary Chart. Application of machine learning to feature selection. The features are ordered on the vertical axis based on the sum of their SHAP values across all samples. The horizontal axis represents the distribution of the effects of the features on the model output. Each point on the graph represents a sample, with the sample size stacked vertically. The colors indicate the eigenvalues, with red representing high values and blue representing low values. (C, D) Distribution of GNRI and SII in various subgroups. The MACE group is represented by the pink area, while the non-MACE group is represented by the green area. Each region is represented by three dotted lines indicating the 25th, 50th, and 75th quartiles. The violin plot's wider section indicates a higher probability of an observation taking a particular value, while the narrower section corresponds to a lower probability.

Figure 2

Restricted cubic spline relationships between GNRI, SII, and MACE risk. 1 in Group grouping in Figures (A and B) represents Age greater than or equal to 68, and 0 represents less than 68. Multivariable adjusted risk ratios for MACE risk ratios adjusted for SII and GNRI scores on continuous scales. The red solid line is the multivariate-adjusted risk ratio, and the dashed line is the 95 percent confidence interval derived from a three-section restricted cubic spline regression. A dashed line with a risk ratio of 1.0 indicates the unrelated reference line. The sizes of GNRI and SII are shown separately on the x-axis. The distribution of GNRI and SII score densities in the study population is presented in histograms and density plots.

Figure 3

Nomogram of the clinical prediction model for the occurrence of MACE within one year after PCI in elderly ACS patients.

Figure 4

Efficacy of Predictive Models and GRCE Scores for Assessing MACE Risks.

Figure 5

ROC and recall curves were used to predict MACE in elderly ACS patients within one year of PCI. Standard Curve for Clinical Prediction Model for the Development of MACE within One Year of PCI in Elderly Patients with ACS.

Figure 6

DCA Curve and Clinical Impact Curve of a Clinical Prediction Model for the Development of MACE within One Year of PCI in Elderly Patients with ACS.