Predicting Major Adverse Events in Patients Undergoing Transcatheter Left Atrial Appendage Occlusion.

IF 9.1 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
Kamil F Faridi, Emily L Ong, Sarah Zimmerman, Paul D Varosy, Daniel J Friedman, Jonathan C Hsu, Fred Kusumoto, Bobak J Mortazavi, Karl E Minges, Lucy Pereira, Dhanunjaya Lakkireddy, Christina Koutras, Beth Denton, Julie Mobayed, Jeptha P Curtis, James V Freeman
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引用次数: 0

Abstract

Background: The National Cardiovascular Data Registry Left Atrial Appendage Occlusion Registry (LAAO) includes the vast majority of transcatheter LAAO procedures performed in the United States. The objective of this study was to develop a model predicting adverse events among patients undergoing LAAO with Watchman FLX.

Methods: Data from 41 001 LAAO procedures with Watchman FLX from July 2020 to September 2021 were used to develop and validate a model predicting in-hospital major adverse events. Randomly selected development (70%, n=28 530) and validation (30%, n=12 471) cohorts were analyzed with 1000 bootstrapped samples, using forward stepwise logistic regression to create the final model. A simplified bedside risk score was also developed using this model.

Results: Increased age, female sex, low preprocedure hemoglobin, no prior attempt at atrial fibrillation termination, and increased fall risk most strongly predicted in-hospital major adverse events and were included in the final model along with other clinically relevant variables. The median in-hospital risk-standardized adverse event rate was 1.50% (range, 1.03%-2.84%; interquartile range, 1.42%-1.64%). The model demonstrated moderate discrimination (development C-index, 0.67 [95% CI, 0.65-0.70] and validation C-index, 0.66 [95% CI, 0.62-0.70]) with good calibration. The simplified risk score was well calibrated with risk of in-hospital major adverse events ranging from 0.26% to 3.90% for a score of 0 to 8, respectively.

Conclusions: A transcatheter LAAO risk model using National Cardiovascular Data Registry and LAAO Registry data can predict in-hospital major adverse events, demonstrated consistency across hospitals and can be used for quality improvement efforts. A simple bedside risk score was similarly predictive and may inform shared decision-making.

预测接受经导管左房阑尾闭塞术患者的主要不良事件
背景:美国国家心血管数据登记处和左心房阑尾闭塞(LAAO)登记处包括了在美国实施的绝大多数经导管 LAAO 手术。本研究的目的是建立一个模型,预测使用 Watchman FLX 进行 LAAO 患者的不良事件:2020年7月至2021年9月期间使用Watchman FLX进行的41001例LAAO手术数据被用于开发和验证院内主要不良事件预测模型。随机选取开发组群(70%,n=28 530)和验证组群(30%,n=12 471),使用前向逐步逻辑回归建立最终模型,并对1000个引导样本进行分析。利用该模型还开发了简化的床边风险评分:结果:年龄增大、性别为女性、术前血红蛋白偏低、之前未尝试过房颤终止术以及跌倒风险增加最能预测院内重大不良事件,这些因素与其他临床相关变量一起被纳入最终模型。院内风险标准化不良事件发生率的中位数为1.50%(范围为1.03%-2.84%;四分位间范围为1.42%-1.64%)。该模型显示出适度的区分度(开发 C 指数为 0.67 [95% CI,0.65-0.70],验证 C 指数为 0.66 [95% CI,0.62-0.70])和良好的校准性。简化风险评分校准良好,0至8分的院内主要不良事件风险分别为0.26%至3.90%:使用美国国家心血管数据登记处和LAAO登记处数据建立的经导管LAAO风险模型可以预测院内重大不良事件,在不同医院具有一致性,可用于质量改进工作。简单的床边风险评分也具有类似的预测能力,可为共同决策提供参考。
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来源期刊
CiteScore
13.70
自引率
4.80%
发文量
187
审稿时长
4-8 weeks
期刊介绍: Circulation: Arrhythmia and Electrophysiology is a journal dedicated to the study and application of clinical cardiac electrophysiology. It covers a wide range of topics including the diagnosis and treatment of cardiac arrhythmias, as well as research in this field. The journal accepts various types of studies, including observational research, clinical trials, epidemiological studies, and advancements in translational research.
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