Association between Triglyceride-Glucose Index and Major Adverse Cardiovascular Events Risk in Coronary Heart Disease Patients with Blood Stasis Syndrome after Percutaneous Coronary Intervention
10.13288/j.11-2166/r.2024.17.008
- VernacularTitle:冠心病PCI术后血瘀证患者甘油三酯葡萄糖乘积指数与主要心血管不良事件风险的相关性
- Author:
Shiyi TAO
1
;
Lintong YU
1
;
Jun LI
2
;
Li HUANG
3
;
Zicong XIE
2
;
Deshuang YANG
3
;
Tiantian XUE
2
;
Yuqing TAN
1
Author Information
1. Beijing University of Chinese Medicine，Beijing，100029
2. Guang'anmen Hospital，China Academy of Chinese Medical Sciences
3. China-Japan Friendship Hospital
- Publication Type:Journal Article
- Keywords:
coronary heart disease;
percutaneous coronary intervention;
blood stasis syndrome;
triglyceride-glucose index;
major adverse cardiovascular events
- From:
Journal of Traditional Chinese Medicine
2024;65(17):1784-1793
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo explore the association between triglyceride-glucose （TyG） index and major adverse cardiovascular events （MACEs） risk in coronary heart disease （CHD） patients with blood stasis syndrome after percutaneous coronary intervention （PCI）. MethodsA total of 857 CHD patients with blood stasis syndrome after PCI were enrolled and divided into four groups according to the baseline TyG index quartiles， Q1 （TyG ＜ 8.51）， Q2 （8.51 ≤ TyG ＜ 8.88）， Q3 （8.88 ≤ TyG ＜ 9.22）， and Q4 （TyG ≥ 9.22）. The clinical outcome was defined as a compound endpoint of cardiovascular events including cardiac death， non-fatal myocardial infarction， unplanned revascularization， in-stent restenosis and stroke. The machine learning Boruta algorithm was used for feature selection related to MACEs risk. Kaplan-Meier survival analysis and Cox proportional hazards regression model were used to compare the differences in MACEs risk among the four groups. Restricted cubic spline （RCS） and subgroup analysis were performed to determine the relationship between the TyG index and MACEs risk. The area under the receiver operating characteristic （ROC） curve （AUC）， calibration curve and Hosmer-Lemeshow test， and decision curve analysis （DCA） were plotted to evaluate the predictive value of the TyG index for MACEs risk. ResultsThe median follow-up time of the included patients was 2.45 years. During the follow-up period， 313 cases （36.52%） of new MACEs occurred. The incidence of MACEs in Q1， Q2， Q3， Q4 group was 28.17% （60/213）， 29.05% （61/210）， 39.45% （86/218） and 49.07% （106/216）， respectively. Kaplan-Meier survival analysis suggested statistically significant differences in MACEs risk among the four groups （P＜0.001）. Cox proportional hazards regression model analysis found that the risk of MACEs in patients with high TyG index increased by 60.1% （P＜0.01）. Using Q1 as the reference， the MACEs risk in Q2， Q3 and Q4 groups gradually increased， and the trend was statistically significant （P＜0.05）. RCS model suggested that the TyG index was nonlinearly associated with the MACEs risk （P＜0.001）. The TyG index had a good predictive performance for MACEs risk according to ROC analysis （AUC=0.758， 0.724-0.792） and Hosmer-Lemeshow test （χ2 = 4.319， P = 0.827）. Additionally， DCA analysis also suggested a good clinical efficacy of the TyG index for predicting MACEs. Subgroup analysis showed that different baseline TyG index was positively correlated with the MACEs risk in the stratification of age， male， BMI， history of diabetes and hypertension， and low-density lipoprotein cholesterol （LDL-C）≥1.8 mmol·L-1（P＜0.05）. ConclusionThe elevated TyG index is closely corrected with an increased risk of MACEs in CHD patients with blood stasis syndrome after PCI， indicating a guiding significance for early risk stratification and clinical decisions.
