Development and Validation of Predictive Model—HASBLAD Score—For Major Adverse Cardiovascular Events During Perioperative Period of Non-cardiac Surgery: A Single Center Experience in China
BackgroundMajor adverse cardiovascular events (MACEs) represent a significant reason of morbidity and mortality in non-cardiac surgery during perioperative period. The prevention of perioperative MACEs has always been one of the hotspots in the research field. Current existing models have not been v...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Cardiovascular Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2022.774191/full |
| _version_ | 1818192255742115840 |
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| author | Menglin Zhao Zhi Shang Jiageng Cai Cencen Wu Yuan Xu Lin Zeng Hong Cai Mao Xu Yuanyuan Fan Yanguang Li Wei Gao Weixian Xu Lingyun Zu |
| author_facet | Menglin Zhao Zhi Shang Jiageng Cai Cencen Wu Yuan Xu Lin Zeng Hong Cai Mao Xu Yuanyuan Fan Yanguang Li Wei Gao Weixian Xu Lingyun Zu |
| author_sort | Menglin Zhao |
| collection | DOAJ |
| description | BackgroundMajor adverse cardiovascular events (MACEs) represent a significant reason of morbidity and mortality in non-cardiac surgery during perioperative period. The prevention of perioperative MACEs has always been one of the hotspots in the research field. Current existing models have not been validated in Chinese population, and have become increasingly unable to adapt to current clinical needs.ObjectivesTo establish and validate several simple bedside tools for predicting MACEs during perioperative period of non-cardiac surgery in Chinese hospitalized patients.DesignWe used a nested case-control study to establish our prediction models. A nomogram along with a risk score were developed using logistic regression analysis. An internal cohort was used to evaluate the performance of discrimination and calibration of these predictive models including the revised cardiac risk index (RCRI) score recommended by current guidelines.SettingPeking University Third Hospital between January 2010 and December 2020.PatientsTwo hundred and fifty three patients with MACEs and 1,012 patients without were included in the training set from January 2010 to December 2019 while 38,897 patients were included in the validation set from January 2020 and December 2020, of whom 112 patients had MACEs.Main Outcome MeasuresThe MACEs included the composite outcomes of cardiac death, non-fatal myocardial infarction, non-fatal congestive cardiac failure or hemodynamically significant ventricular arrhythmia, and Takotsubo cardiomyopathy.ResultsSeven predictors, including Hemoglobin, CARDIAC diseases, Aspartate aminotransferase (AST), high Blood pressure, Leukocyte count, general Anesthesia, and Diabetes mellitus (HASBLAD), were selected in the final model. The nomogram and HASBLAD score all achieved satisfactory prediction performance in the training set (C statistic, 0.781 vs. 0.768) and the validation set (C statistic, 0.865 vs. 0.843). Good calibration was observed for the probability of MACEs in the training set and the validation set. The two predictive models both had excellent discrimination that performed better than RCRI in the validation set (C statistic, 0.660, P < 0.05 vs. nomogram and HASBLAD score).ConclusionThe nomogram and HASBLAD score could be useful bedside tools for predicting perioperative MACEs of non-cardiac surgery in Chinese hospitalized patients. |
| first_indexed | 2024-12-12T00:27:36Z |
| format | Article |
| id | doaj.art-94657f07cf3e49f5b6f3821a2bd17101 |
| institution | Directory Open Access Journal |
| issn | 2297-055X |
| language | English |
| last_indexed | 2024-12-12T00:27:36Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cardiovascular Medicine |
| spelling | doaj.art-94657f07cf3e49f5b6f3821a2bd171012022-12-22T00:44:35ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2022-05-01910.3389/fcvm.2022.774191774191Development and Validation of Predictive Model—HASBLAD Score—For Major Adverse Cardiovascular Events During Perioperative Period of Non-cardiac Surgery: A Single Center Experience in ChinaMenglin ZhaoZhi ShangJiageng CaiCencen WuYuan XuLin ZengHong CaiMao XuYuanyuan FanYanguang LiWei GaoWeixian XuLingyun ZuBackgroundMajor adverse cardiovascular events (MACEs) represent a significant reason of morbidity and mortality in non-cardiac surgery during perioperative period. The prevention of perioperative MACEs has always been one of the hotspots in the research field. Current existing models have not been validated in Chinese population, and have become increasingly unable to adapt to current clinical needs.ObjectivesTo establish and validate several simple bedside tools for predicting MACEs during perioperative period of non-cardiac surgery in Chinese hospitalized patients.DesignWe used a nested case-control study to establish our prediction models. A nomogram along with a risk score were developed using logistic regression analysis. An internal cohort was used to evaluate the performance of discrimination and calibration of these predictive models including the revised cardiac risk index (RCRI) score recommended by current guidelines.SettingPeking University Third Hospital between January 2010 and December 2020.PatientsTwo hundred and fifty three patients with MACEs and 1,012 patients without were included in the training set from January 2010 to December 2019 while 38,897 patients were included in the validation set from January 2020 and December 2020, of whom 112 patients had MACEs.Main Outcome MeasuresThe MACEs included the composite outcomes of cardiac death, non-fatal myocardial infarction, non-fatal congestive cardiac failure or hemodynamically significant ventricular arrhythmia, and Takotsubo cardiomyopathy.ResultsSeven predictors, including Hemoglobin, CARDIAC diseases, Aspartate aminotransferase (AST), high Blood pressure, Leukocyte count, general Anesthesia, and Diabetes mellitus (HASBLAD), were selected in the final model. The nomogram and HASBLAD score all achieved satisfactory prediction performance in the training set (C statistic, 0.781 vs. 0.768) and the validation set (C statistic, 0.865 vs. 0.843). Good calibration was observed for the probability of MACEs in the training set and the validation set. The two predictive models both had excellent discrimination that performed better than RCRI in the validation set (C statistic, 0.660, P < 0.05 vs. nomogram and HASBLAD score).ConclusionThe nomogram and HASBLAD score could be useful bedside tools for predicting perioperative MACEs of non-cardiac surgery in Chinese hospitalized patients.https://www.frontiersin.org/articles/10.3389/fcvm.2022.774191/fullnon-cardiac surgerymajor adverse cardiovascular eventsprediction modelTakotsubo cardiomyopathynomogramrisk score |
| spellingShingle | Menglin Zhao Zhi Shang Jiageng Cai Cencen Wu Yuan Xu Lin Zeng Hong Cai Mao Xu Yuanyuan Fan Yanguang Li Wei Gao Weixian Xu Lingyun Zu Development and Validation of Predictive Model—HASBLAD Score—For Major Adverse Cardiovascular Events During Perioperative Period of Non-cardiac Surgery: A Single Center Experience in China Frontiers in Cardiovascular Medicine non-cardiac surgery major adverse cardiovascular events prediction model Takotsubo cardiomyopathy nomogram risk score |
| title | Development and Validation of Predictive Model—HASBLAD Score—For Major Adverse Cardiovascular Events During Perioperative Period of Non-cardiac Surgery: A Single Center Experience in China |
| title_full | Development and Validation of Predictive Model—HASBLAD Score—For Major Adverse Cardiovascular Events During Perioperative Period of Non-cardiac Surgery: A Single Center Experience in China |
| title_fullStr | Development and Validation of Predictive Model—HASBLAD Score—For Major Adverse Cardiovascular Events During Perioperative Period of Non-cardiac Surgery: A Single Center Experience in China |
| title_full_unstemmed | Development and Validation of Predictive Model—HASBLAD Score—For Major Adverse Cardiovascular Events During Perioperative Period of Non-cardiac Surgery: A Single Center Experience in China |
| title_short | Development and Validation of Predictive Model—HASBLAD Score—For Major Adverse Cardiovascular Events During Perioperative Period of Non-cardiac Surgery: A Single Center Experience in China |
| title_sort | development and validation of predictive model hasblad score for major adverse cardiovascular events during perioperative period of non cardiac surgery a single center experience in china |
| topic | non-cardiac surgery major adverse cardiovascular events prediction model Takotsubo cardiomyopathy nomogram risk score |
| url | https://www.frontiersin.org/articles/10.3389/fcvm.2022.774191/full |
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