引言接受左心耳闭塞(LAAO)的患者出血或血栓栓塞事件的风险增加。同时,在房颤患者的危险分层中,生物标志物越来越重要.我们旨在评估LAAO后血液学标志物和临床特征与血栓栓塞和出血事件发生的关系。方法七个植入中心回顾性收集血液标志物(即血小板计数(PC),平均血小板体积(MPV),和纤维蛋白原)在LAAO之前。收集预先确定的血栓栓塞和主要出血结果,并使用Cox回归分析评估与术前血液学标志物和临床特征的关联。结果总计,纳入1315例患者(74±9岁,36%女性,CHA2DS2-VASc4.3±1.5,HAS-BLED3.3±1.1)。总随访时间为2682例患者年,LAAO后发生了77起血栓栓塞事件和107起主要出血事件。基线PC是每50*109增量显示与血栓栓塞事件相关信号的唯一生物标志物(HR1.18,95%CI:1.00-1.39)。p=0.056)。血栓事件发生率,包括装置相关血栓,在较高的PC四分位数内增加。血栓栓塞与年龄(HR1.05,95%CI:1.00-1.10,每年增加)和既往血栓栓塞(HR2.08,95%CI:1.07-4.03)相关,但是没有多变量分析中的生物标志物。没有观察到任何血液学标志物与大出血的关联。LAAO后的大出血与先前的大出血有关(HR5.27,95%CI:2.71-10.22),肾脏疾病(HR1.93,95%CI:1.17-3.18)和双重抗血小板治疗的出院(HR1.71,95%CI:1.05-2.77)。结论大多数血栓事件发生在PC的最高四分位数。但在我们的分析中未观察到任何血液学标志物与血栓栓塞或大出血的相关性.在多变量分析中,高龄和既往血栓栓塞与血栓栓塞相关.先前大出血,肾脏疾病和DAPT出院是LAAO术后大出血的多变量预测因子.
BACKGROUND: Patients undergoing left atrial appendage occlusion (LAAO) are at increased risk for bleeding or thromboembolic events. Concurrently, biomarkers are of growing importance in risk stratification for atrial fibrillation patients. We aimed to evaluate the association of hematological markers and clinical characteristics with the occurrence of thromboembolic and bleeding events following LAAO.
METHODS: Seven implanting centers retrospectively gathered data on hematological markers (i.e., platelet count [PC], mean platelet volume [MPV], and fibrinogen) prior to LAAO. Prespecified thromboembolic and major bleeding outcomes were collected and the association with pre-procedural hematological markers and clinical characteristics was evaluated using Cox regression analysis.
RESULTS: In total, 1,315 patients were included (74 ± 9 years, 36% female, CHA2DS2-VASc 4.3 ± 1.5, HAS-BLED 3.3 ± 1.1). Over a total follow-up duration of 2,682 patient years, 77 thromboembolic events and 107 major bleeding events occurred after LAAO. Baseline PC was the only biomarker showing a signal for a relation to thromboembolic events (HR 1.18, 95% CI: 1.00-1.39) per 50*109 increment, p = 0.056). Thrombotic event rates, including device-related thrombus, increased within higher PC quartiles. Thromboembolism was associated with age (HR 1.05, 95% CI: 1.00-1.10, per year increase) and prior thromboembolism (HR 2.08, 95% CI: 1.07-4.03), but with none of the biomarkers in multivariate analysis. No association of any of the hematological markers with major bleeding was observed. Major bleeding following LAAO was associated with prior major bleeding (HR 5.27, 95% CI: 2.71-10.22), renal disease (HR 1.93, 95% CI: 1.17-3.18), and discharge on dual antiplatelet therapy (DAPT) (HR 1.71, 95% CI: 1.05-2.77).
CONCLUSIONS: Most thrombotic events occurred in the highest PC quartile, but no association of any of the hematological markers with thromboembolism or major bleeding was observed in our analysis. In multivariate analysis, older age and prior thromboembolism were associated with thromboembolism. Prior major bleeding, renal disease and discharge on DAPT were multivariate predictors of major bleeding after LAAO.