凝血酶原活动度与冠状动脉慢血流患者预后的相关性分析

Correlation analysis of prothrombin activity with prognosis of patients with coronary slow flow phenomenon

摘要:

目的 筛查预测冠状动脉慢血流(CSFP)患者出院后再发不良心血管事件的有效分子标志物。方法 通过前瞻性观察研究分析了2013年1月至2014年12月在解放军总医院心内科住院治疗的行冠状动脉造影(CAG)确诊为单纯CSFP患者共54例,出院后随访发生心血管不良事件患者10例(不良事件组),未发生不良事件44例(无不良事件组),对比分析两组患者一般实验室指标和心脏超声指标。对单因素分析有统计学意义的数据及预测CSFP预后的实验室指标纳入Cox 回归分析模型；将最为显著的独立危险因素纳入ROC曲线分析；并采用Kaplan-Meiers生存分析比较不同危险因素患者的不良心血管事件的发生率。结果 不良事件组甘油三酯(TG)、载脂蛋白B(ApoB)、肌酸激酶MB同工酶(CK-MB)、凝血酶原活动度(PTA)显著高于无不良事件组(P<0.05)。Cox回归模型分析显示PTA增高是患者预后不良的独立危险因素(HR=1.193,95%CI为1.036~1.374,P<0.05)。采用Kaplan-Meiers生存率分析,高PTA患者的总体不良事件发生率明显高于低PTA患者(P<0.05),血浆PTA预测患者出院后随访期间不良心血管事件的ROC曲线相关性好(曲线下面积0.717,P=0.033)。结论 PTA可作为预测CSF患者的长期不良事件发生率的检测指标。

Abstract:

Objective To explore the effective laboratory markers for predicting adverse cardiovascular events in the patients with coronary slow flow phenomenon (CSFP). Methods A prospective study was carried out on 54 patients who underwent coronary angiography (CAG) and diagnosed with simple CSFP in our department from January 2013 to December 2014. According to the incidence of adverse cardiovascular events during the follow-up, they were divided into adverse events group (n=10) and adverse events-free group (n=44).The laboratory indicators and echocardiographic parameters were compared and analyzed between the 2 groups. Statistical data from univariate analysis and laboratory indicators predicting CSFP prognosis were included in the Cox regression model. The most significant independent risk factors were included in the receiver operating characteristic (ROC) curve analysis. Kaplan-Meiers survival analysis was used to compare the incidence of adverse cardiovascular events among the patients with different risk factors. Results The serum contents of triglycerides (TG), apolipoproteins B (ApoB), creatine kinase MB isoenzyme (CK-MB), and plasma prothrombin activity (PTA)were significantly higher in the adverse events group than the adverse events-free group(HR=1.193, 95%CI 1.036-1.374, P<0.05). Cox regression analysis showed that increased PTA was an independent risk factor for poor prognosis(P<0.05). Kaplan-Meiers survival analysis also indicated that those with higher PTA had higher incidence of adverse events than those with low PTA (P<0.05). The plasma PTA showed good correlation between the ROC curve and adverse cardiovascular events during the follow-up period after discharge (area under the curve=0.717, P=0.033). Conclusion PTA can be used as an indicator in the prediction of long term adverse events in CSFP patients.