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Abstract：
OBJECTIVE: Sufficient survival time following left atrial appendage occlusion (LAAO) is essential for ensuring the efficacy and cost-effectiveness of this strategy for stroke prevention. Understanding prognostic factors for early mortality after LAAO could optimize patient selection. In the current study, we perform an in-depth analysis of 2-year mortality after LAAO, focusing particularly on potential predictors.
RESULTS: The EWOLUTION registry is a real-world cohort comprising 1020 patients that underwent LAAO. Endpoint definitions were pre-specified, and death was categorized as cardiovascular, non-cardiovascular, or unknown origin. Mortality rates were calculated from Kaplan-Meier estimates. Baseline characteristics significantly associated with death in univariate Cox regression analysis were incorporated into the multivariate analysis. All multivariate predictors were included in a risk model. Two-year mortality rate was 16.4% [confidence interval (CI): 14.0-18.7%], with 50% of patients dying from a non-cardiovascular cause. Multivariate baseline predictors of 2-year mortality included age [hazard ratio (HR) 1.05, CI: 1.03-1.08, per year increase], heart failure (HR 1.73, CI: 1.24-2.41), vascular disease (HR 1.47, CI: 1.05-2.05), valvular disease (HR 1.63, CI: 1.15-2.33), abnormal liver function (HR 1.80, CI: 1.02-3.17), and abnormal renal function (HR 1.58, CI: 1.10-2.27). Mortality rate exhibited a gradual rise as the number of risk factors increased, reaching 46.1% in patients presenting with five or six risk factors.
CONCLUSIONS: One in six patients died within 2 years after LAAO. We identified six independent predictors of mortality. When combined, this model showed a gradual increase in mortality rate with a growing number of risk factors, which may guide appropriate patient selection for LAAO.
BACKGROUND: The original EWOLUTION registry was registered at clinicaltrials.gov under identifier NCT01972282.
RESULTS: The EWOLUTION registry is a real-world cohort comprising 1020 patients that underwent LAAO. Endpoint definitions were pre-specified, and death was categorized as cardiovascular, non-cardiovascular, or unknown origin. Mortality rates were calculated from Kaplan-Meier estimates. Baseline characteristics significantly associated with death in univariate Cox regression analysis were incorporated into the multivariate analysis. All multivariate predictors were included in a risk model. Two-year mortality rate was 16.4% [confidence interval (CI): 14.0-18.7%], with 50% of patients dying from a non-cardiovascular cause. Multivariate baseline predictors of 2-year mortality included age [hazard ratio (HR) 1.05, CI: 1.03-1.08, per year increase], heart failure (HR 1.73, CI: 1.24-2.41), vascular disease (HR 1.47, CI: 1.05-2.05), valvular disease (HR 1.63, CI: 1.15-2.33), abnormal liver function (HR 1.80, CI: 1.02-3.17), and abnormal renal function (HR 1.58, CI: 1.10-2.27). Mortality rate exhibited a gradual rise as the number of risk factors increased, reaching 46.1% in patients presenting with five or six risk factors.
CONCLUSIONS: One in six patients died within 2 years after LAAO. We identified six independent predictors of mortality. When combined, this model showed a gradual increase in mortality rate with a growing number of risk factors, which may guide appropriate patient selection for LAAO.
BACKGROUND: The original EWOLUTION registry was registered at clinicaltrials.gov under identifier NCT01972282.
摘要：
目的：左心耳封堵术（LAAO）后足够的生存时间对于确保该预防中风策略的有效性和成本效益至关重要。了解LAAO术后早期死亡的预后因素可以优化患者选择。在目前的研究中,我们对LAAO术后2年死亡率进行了深入分析，特别关注潜在的预测因素。
结果：EWOLUTION注册是一个真实世界的队列，包括1020名接受LAAO的患者。端点定义已预先指定，死亡被归类为心血管疾病，非心血管疾病,或者来历不明。根据Kaplan-Meier估计计算死亡率。单变量Cox回归分析中与死亡显著相关的基线特征被纳入多变量分析。所有多变量预测因子都包含在风险模型中。两年死亡率为16.4%[置信区间（CI）：14.0-18.7%]，50%的患者死于非心血管原因。2年死亡率的多变量基线预测因素包括年龄[风险比（HR）1.05，CI：1.03-1.08，每年增加]，心力衰竭（HR1.73，CI：1.24-2.41），血管疾病（HR1.47，CI：1.05-2.05），瓣膜疾病（HR1.63，CI：1.15-2.33），肝功能异常（HR1.80，CI：1.02-3.17），肾功能异常（HR1.58，CI：1.10-2.27）。随着危险因素的增加，死亡率逐渐上升，在存在5或6个危险因素的患者中达到46.1%。
结论：六分之一的患者在LAAO后2年内死亡。我们确定了六个独立的死亡率预测因子。当组合时，该模型显示，随着危险因素的增加，死亡率逐渐增加，这可以指导LAAO的适当患者选择。
背景：原始的EWOLUTION注册表在clinicaltrials.gov注册，其标识符为NCT01972282。
结果：EWOLUTION注册是一个真实世界的队列，包括1020名接受LAAO的患者。端点定义已预先指定，死亡被归类为心血管疾病，非心血管疾病,或者来历不明。根据Kaplan-Meier估计计算死亡率。单变量Cox回归分析中与死亡显著相关的基线特征被纳入多变量分析。所有多变量预测因子都包含在风险模型中。两年死亡率为16.4%[置信区间（CI）：14.0-18.7%]，50%的患者死于非心血管原因。2年死亡率的多变量基线预测因素包括年龄[风险比（HR）1.05，CI：1.03-1.08，每年增加]，心力衰竭（HR1.73，CI：1.24-2.41），血管疾病（HR1.47，CI：1.05-2.05），瓣膜疾病（HR1.63，CI：1.15-2.33），肝功能异常（HR1.80，CI：1.02-3.17），肾功能异常（HR1.58，CI：1.10-2.27）。随着危险因素的增加，死亡率逐渐上升，在存在5或6个危险因素的患者中达到46.1%。
结论：六分之一的患者在LAAO后2年内死亡。我们确定了六个独立的死亡率预测因子。当组合时，该模型显示，随着危险因素的增加，死亡率逐渐增加，这可以指导LAAO的适当患者选择。
背景：原始的EWOLUTION注册表在clinicaltrials.gov注册，其标识符为NCT01972282。
