主管单位:中华人民共和国
国家卫生健康委员会
主办单位:中国医师协会
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编辑部主任:吴翔宇
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英文作者:Ma Lin Zhang Chunxiu Bai Wenlian
单位:甘肃省临夏回族自治州人民医院心血管内科,临夏731100
英文单位:Department of Cardiovascular Medicine People′s Hospital of Linxia Hui Autonomous Prefecture Gansu Province Linxia 731100 China
英文关键词:Nonvalvularatrialfibrillation;Fibrinogen;Leftatrialappendagethrombosis;Correlation
目的 探讨非瓣膜性心房颤动(NVAF)患者血浆纤维蛋白原(FIB)水平与左心耳血栓形成(LAAT)的相关性。方法 选取2019年12月至2020年11月于甘肃省临夏回族自治州人民医院住院治疗的NVAF患者212例为研究对象。收集患者临床资料,根据患者是否产生LAAT将患者分为形成组(70例)和非形成组(142例),比较2组临床资料。Logistic回归法分析NVAF患者发生LAAT的危险因素,采用Spearman相关性分析方法分析NVAF患者血浆FIB水平与发生LAAT的相关性。依据FIB水平三分位数将患者分为低FIB组(≤2 g/L)、中FIB组(>2~<4 g/L)和高FIB组(≥4 g/L),Cox回归模型分析NVAF患者FIB水平与LAAT风险的关系,依据NVAF患者发生LAAT的独立危险因素构建预测模型,评价预测效能。结果 年龄>67岁、心房颤动病程>36个月、左心房前后径>37.20 mm、B型脑钠肽>311.65 ng/L、FIB>2.98 g/L、血尿酸>438 μmol/L、CHA2DS2-VASc评分>5分、冠心病(冠状动脉粥样硬化性心脏病)、心力衰竭是NVAF患者发生LAAT的独立危险因素(均P<0.05)。FIB水平与LAAT呈正相关(r=0.691, P=0.001)。低FIB组患者发生LAAT的风险显著低于高FIB组(风险比=2.852,95%置信区间1.302~6.432,P=0.005)。基于LAAT的独立危险因素构建LAAT预测模型,该模型在训练集(159例)中曲线下面积为0.771(95%置信区间:0.620~0.966),在测试集(53例)中曲线下面积为0.756(95%置信区间:0.661~0.995),其间差异无统计学意义(P=0.142)。结论 高FIB水平是NVAF患者发生LAAT的独立危险因素,临床应及时关注并纠正NVAF患者FIB水平。
Objective To explore the relationship between plasma fibrinogen (FIB) level and left atrial appendage thrombosis(LAAT) in patients with nonvalvular atrial fibrillation(NVAF). Methods From December 2019 to November 2020, 212 inpatients with NVAF admitted to People′s Hospital of Linxia Hui Autonomous Prefecture, Gansu Province were selected. The clinical data of patients were collected, patients were divided into forming groups(70 cases) and non-forming groups(142 cases) according to whether they had LAAT, and clinical data were compared between the two groups. Logistic regression method was used to analyze the risk factors of LAAT in patients with NVAF, and Spearman correlation analysis was used to analyze the relationship between FIB and LAAT in patients with NVAF. Patients were divided into low FIB group(≤2 g/L), moderate FIB group(>2-<4 g/L) and high FIB group(≥4 g/L) according to the tertiles of plasma FIB level. Cox regression model was used to analyze the relationship between the FIB level and the risk of LAAT in patients with NVAF. The predictive model was constructed based on the independent risk factors of LAAT in NVAF patients, and its predictive effectiveness was evaluated. Results Age>67 years, atrial fibrillation course>36 months, left atrial anteroposterior diameter>37.20 mm, brain natriuretic peptide>311.65 ng/L, FIB>2.98 g/L, serum uric acid>438 μmol/L, CHA2DS2-VASc score>5, coronary atherosclerotic heart disease and heart failure were independent risk factors for LAAT in patients with NVAF(all P<0.05). FIB level was positively correlated with LAAT (r=0.691, P=0.001). The risk of LAAT in patients of low FIB group was significantly lower than that of high FIB group(hazard ratio=2.852, 95% confidence interval: 1.302-6.432, P=0.005). The LAAT predictiive model was constructed based on the independent risk factors of LAAT. The area under the curve(AUC) of the model in training set (159 cases) was 0.771(95% confidence interval: 0.620-0.966). The AUC of the LAAT predictive model for NVAF patients in test set was 0.756(95% confidence interval: 0.661-0.995). Compared with the training set, the difference in AUC was not statistically significant(P=0.142). Conclusion High FIB level is an independent risk factor for LAAT in patients with NVAF. Clinicians should pay attention to and correct the FIB level in patients with NVAF in time.
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