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
{"title":"预测接受经导管左房阑尾闭塞术患者的主要不良事件","authors":"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","doi":"10.1161/CIRCEP.123.012424","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":10319,"journal":{"name":"Circulation. Arrhythmia and electrophysiology","volume":" ","pages":"e012424"},"PeriodicalIF":9.1000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11021146/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predicting Major Adverse Events in Patients Undergoing Transcatheter Left Atrial Appendage Occlusion.\",\"authors\":\"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\",\"doi\":\"10.1161/CIRCEP.123.012424\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":10319,\"journal\":{\"name\":\"Circulation. 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Predicting Major Adverse Events in Patients Undergoing Transcatheter Left Atrial Appendage Occlusion.
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.
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.