The predictive values of GGT and Hcy in the risk stratifications and prognoses of NSTE-ACS patients.
2021
OBJECTIVE This research was designed to probe into the predictive value of glutamyltransferase (GGT) and homocysteine (Hcy) in the risk stratifications and prognoses of non-ST segment elevation acute coronary syndrome (NSTE-ACS) patients. METHODS A total of 182 NSTE-ACS patients treated with percutaneous coronary intervention (PCI) in our hospital from February 2016 to May 2018 were recruited as a patient group (PG). They were followed up for one year, and the occurrences of any major adverse cardiovascular events (MACCE) were recorded. In addition, 90 healthy volunteers were recruited as a normal group (NG) during the same period. The GGT and Hcy expressions in the serum of both groups were tested, and the predictive values of these levels, the patient risk stratification, and the prognoses were analyzed. RESULTS Compared with the NG, the GGT and Hcy expressions in the PG were markedly higher (P < 0.05). Compared with the patients without MACE, the GGT and Hcy expressions in the serum of those with MACE increased dramatically (P < 0.05). The serum GGT and Hcy levels were positively correlated with the NSTE-ACS patients' SYNTAX scores (P < 0.05). A Kaplan-Meier curve indicated that the MACE-free survival rate of the patients with low GGT levels was dramatically higher than the survival rate of the patients with high GGT levels, and the MACE-free survival rate of low Hcy patients was significantly higher than the MACE-free survival rate of the high Hcy patients (P < 0.05). Our COX proportional hazards regression models indicated that the serum GGT and Hcy levels are independent predictors of MACCE in NSTE-ACS patients (P < 0.05). Our ROC curve analysis indicated that the serum GGT and Hcy levels are diagnostic criteria for predicting whether MACE occurred in NSTE-ACS patients. CONCLUSION The serum GGT and Hcy levels are positively correlated with the severity of coronary artery disease (CAD) in NSTE-ACS patients. They are independent predictors of adverse prognoses and can help refine the risk stratification management in clinical work.
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