Yan Ju, Deng Chang-Jiang, Min Xuan, Ning Yi, Wang Ming-Yuan, Wang Si-Fan, Aimaitijiang Mikereyi, Zheng Ying-Ying, Xie Xiang, Ma Yi-Tong
Department of Cardiology, The First Affiliated Hospital of Xinjiang Medical University, 830054 Urumqi, Xinjiang, China.
Rev Cardiovasc Med. 2023 Dec 26;24(12):369. doi: 10.31083/j.rcm2412369. eCollection 2023 Dec.
The ratio of fibrinogen to -glutamine transferase (FGR) was used to predict long-term prognosis in patients with coronary heart disease (CHD).
A total of 5638 patients with CHD who were hospitalized from January 2008 to December 2016 were retrospectively enrolled in the study. The mean follow-up time was 35.9 22.5 months. The follow-up endpoints were major cardiac and cerebrovascular adverse events (MACCE). The optimal FGR cut-off value was determined and divided into high- and low-FGR groups according to the receiver operating characteristic (ROC) curve. Statistical methods were used to compare the differences between the two groups and their prognoses to determine whether FGR can predict prognosis in patients with CHD. The traditional predictors were incorporated into the logistic regression model to observe the correlation between these indicators and all-cause mortality (ACM) events. We compared the prediction performance of FGR and traditional predictors on the occurrence of ACM events by ROC curves.
The optimal cut-off value was determined via a ROC analysis (FGR = 1.22, = 0.002), and subjects were classified into high and low FGR groups. The follow-up found that the incidence of MACCE in the high FGR group was higher than that in the low FGR group. The COX multivariate regression model showed that high FGR was independently correlated with the occurrence of MACCE. In addition, the Kaplan-Meier survival curve showed that the risk of events was significantly increased in the group with high FGR. With increases in the FGR ratio, the risk of MACCE was increased. The ROC curve revealed that the risk of ACM was statistically different between the FGR and the traditional risk factor model ( = 0.002), (Fibrinogen ( = 0.008), -glutamine transferase (GGT) ( = 0.004), and N-terminal pro brain natriuretic peptide (NT-ProBNP) ( = 0.024)). The comparison between other different models were not statistically significant ( 0.05). The area under the FGR model curve was larger than that of the traditional risk factors, fibrinogen, GGT and NT-ProBNP models.
High FGR can increase the risk of MACCE in patients with CHD; additionally, it can be used as a new biomarker for long-term prognosis in CHD patients.
All details of this study are registered on the website (http://www.chictr.org.cn), registration number: ChiCTR-ORC-16010153.
纤维蛋白原与γ-谷氨酰胺转移酶比值（FGR）用于预测冠心病（CHD）患者的长期预后。
回顾性纳入2008年1月至2016年12月期间住院的5638例冠心病患者。平均随访时间为35.9±22.5个月。随访终点为主要心脑血管不良事件（MACCE）。根据受试者工作特征（ROC）曲线确定最佳FGR临界值，并将其分为高FGR组和低FGR组。采用统计学方法比较两组之间的差异及其预后情况，以确定FGR是否能够预测冠心病患者的预后。将传统预测指标纳入逻辑回归模型，观察这些指标与全因死亡（ACM）事件之间的相关性。通过ROC曲线比较FGR和传统预测指标对ACM事件发生的预测性能。
通过ROC分析确定最佳临界值（FGR = 1.22，P = 0.002），并将受试者分为高FGR组和低FGR组。随访发现，高FGR组MACCE的发生率高于低FGR组。COX多因素回归模型显示，高FGR与MACCE的发生独立相关。此外，Kaplan-Meier生存曲线显示，高FGR组事件风险显著增加。随着FGR比值的升高，MACCE风险增加。ROC曲线显示，FGR与传统危险因素模型之间的ACM风险存在统计学差异（P = 0.002），（纤维蛋白原（P = 0.008）、γ-谷氨酰胺转移酶（GGT）（P = 0.004）和N末端脑钠肽前体（NT-ProBNP）（P = 0.024））。其他不同模型之间的比较无统计学意义（P>0.05）。FGR模型曲线下面积大于传统危险因素、纤维蛋白原、GGT和NT-ProBNP模型。
高FGR可增加冠心病患者发生MACCE的风险；此外，它可作为冠心病患者长期预后的一种新生物标志物。
本研究的所有详细信息均在网站（http://www.chictr.org.cn）注册，注册号：ChiCTR-ORC-16010153。
