The synergistic predictive value of hemoglobin glycation index and SYNTAX score for coronary artery disease complexity and long-term prognosis after percutaneous coronary intervention
Dongyue Jia, Maoling Jiang, Jie Feng, Junli Pan, Yuqi Tao, Sisi Wang, Si Liu, Hanxiong Liu, Zhen Zhang, Shiqiang Xiong, Lin Cai

TL;DR
This study shows that combining a blood sugar measure (HGI) with a coronary lesion score (SYNTAX) improves prediction of heart disease severity and long-term risks after a common heart procedure.
Contribution
The study identifies a novel synergistic predictive model using HGI and SYNTAX score for CAD prognosis after PCI.
Findings
Higher HGI and SYNTAX scores are linked to increased mortality and complex coronary lesions.
HGI and SYNTAX score are independent predictors of major adverse cardiac and cerebrovascular events.
The SYNTAX score partially mediates the relationship between HGI and adverse outcomes.
Abstract
The complexity of coronary artery lesions and glucose metabolic disorders contributes to adverse long-term prognosis following percutaneous coronary intervention (PCI). This study aimed to evaluate the synergistic effect of coronary artery lesions—assessed by the SYNTAX score—and glucose metabolic disorders—quantified by the hemoglobin glycation index (HGI)—on predicting major adverse cardiac and cerebrovascular events (MACCEs) after PCI. A total of 609 coronary artery disease (CAD) patients undergoing PCI were enrolled in the final analysis. HGI was calculated by subtracting the predicted HbA1c (derived from fasting plasma glucose regression) from the observed HbA1c. Pearson’s coefficients were used for correlation analyses. Kaplan–Meier and Cox regression analyses were used to assess associations with MACCEs. Mediation analysis evaluated whether the SYNTAX score mediated the…
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Taxonomy
TopicsDiabetes, Cardiovascular Risks, and Lipoproteins · Inflammatory Biomarkers in Disease Prognosis · Hyperglycemia and glycemic control in critically ill and hospitalized patients
