Estimation of Major Adverse Cardiovascular Events in Patients With Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: A Risk Prediction Score Model From a Derivation and Validation Study
Background: The population with myocardial infarction (MI) undergoing primary percutaneous coronary intervention (PPCI) is growing, but validated models to guide their clinical management are lacking. This study aimed to develop and validate prognostic models to predict major adverse cardiovascular...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-11-01
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| Series: | Frontiers in Cardiovascular Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2020.603621/full |
| _version_ | 1818383874126774272 |
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| author | Xiaoxiao Zhao Chen Liu Peng Zhou Zhaoxue Sheng Jiannan Li Jinying Zhou Runzhen Chen Ying Wang Yi Chen Li Song Hanjun Zhao Hongbing Yan Hongbing Yan |
| author_facet | Xiaoxiao Zhao Chen Liu Peng Zhou Zhaoxue Sheng Jiannan Li Jinying Zhou Runzhen Chen Ying Wang Yi Chen Li Song Hanjun Zhao Hongbing Yan Hongbing Yan |
| author_sort | Xiaoxiao Zhao |
| collection | DOAJ |
| description | Background: The population with myocardial infarction (MI) undergoing primary percutaneous coronary intervention (PPCI) is growing, but validated models to guide their clinical management are lacking. This study aimed to develop and validate prognostic models to predict major adverse cardiovascular events (MACEs) in patients with MI undergoing PPCI.Methods and Results: Models were developed in 4,151 patients with MI who underwent PPCI in Fuwai Hospital between January 2010 and June 2017, with a median follow-up of 698 days during which 544 MACEs occurred. The predictors included in the models were age, a history of diabetes mellitus, atrial fibrillation, chronic kidney disease, coronary artery bypass grafting, the Killip classification, ejection fraction at admission, the high-sensitivity C-reactive protein (hs-CRP) level, the estimated glomerular filtration rate, the d-dimer level, multivessel lesions, and the culprit vessel. The models had good calibration and discrimination in the derivation and internal validation with C-indexes of 0.74 and 0.60, respectively, for predicting MACEs. The new prediction model and Thrombolysis in Myocardial Infarction (TIMI) risk score model were compared using the receiver operating characteristic curve. The areas under the curve of the new prediction model and TIMI risk score model were 0.806 and 0.782, respectively (difference between areas = 0.024 < 0.05; z statistic, 1.718).Conclusion: The new prediction model could be used in clinical practice to support risk stratification as recommended in clinical guidelines. |
| first_indexed | 2024-12-14T03:13:18Z |
| format | Article |
| id | doaj.art-c8c5c34f0e314677982e68568622d8ca |
| institution | Directory Open Access Journal |
| issn | 2297-055X |
| language | English |
| last_indexed | 2024-12-14T03:13:18Z |
| publishDate | 2020-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cardiovascular Medicine |
| spelling | doaj.art-c8c5c34f0e314677982e68568622d8ca2022-12-21T23:19:12ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2020-11-01710.3389/fcvm.2020.603621603621Estimation of Major Adverse Cardiovascular Events in Patients With Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: A Risk Prediction Score Model From a Derivation and Validation StudyXiaoxiao Zhao0Chen Liu1Peng Zhou2Zhaoxue Sheng3Jiannan Li4Jinying Zhou5Runzhen Chen6Ying Wang7Yi Chen8Li Song9Hanjun Zhao10Hongbing Yan11Hongbing Yan12Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaFuwai Hospital, Chinese Academy of Medical Sciences, Shenzhen, ChinaBackground: The population with myocardial infarction (MI) undergoing primary percutaneous coronary intervention (PPCI) is growing, but validated models to guide their clinical management are lacking. This study aimed to develop and validate prognostic models to predict major adverse cardiovascular events (MACEs) in patients with MI undergoing PPCI.Methods and Results: Models were developed in 4,151 patients with MI who underwent PPCI in Fuwai Hospital between January 2010 and June 2017, with a median follow-up of 698 days during which 544 MACEs occurred. The predictors included in the models were age, a history of diabetes mellitus, atrial fibrillation, chronic kidney disease, coronary artery bypass grafting, the Killip classification, ejection fraction at admission, the high-sensitivity C-reactive protein (hs-CRP) level, the estimated glomerular filtration rate, the d-dimer level, multivessel lesions, and the culprit vessel. The models had good calibration and discrimination in the derivation and internal validation with C-indexes of 0.74 and 0.60, respectively, for predicting MACEs. The new prediction model and Thrombolysis in Myocardial Infarction (TIMI) risk score model were compared using the receiver operating characteristic curve. The areas under the curve of the new prediction model and TIMI risk score model were 0.806 and 0.782, respectively (difference between areas = 0.024 < 0.05; z statistic, 1.718).Conclusion: The new prediction model could be used in clinical practice to support risk stratification as recommended in clinical guidelines.https://www.frontiersin.org/articles/10.3389/fcvm.2020.603621/fullmyocardial infarctionprimary percutaneous coronary interventionMACEderivationvalidation |
| spellingShingle | Xiaoxiao Zhao Chen Liu Peng Zhou Zhaoxue Sheng Jiannan Li Jinying Zhou Runzhen Chen Ying Wang Yi Chen Li Song Hanjun Zhao Hongbing Yan Hongbing Yan Estimation of Major Adverse Cardiovascular Events in Patients With Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: A Risk Prediction Score Model From a Derivation and Validation Study Frontiers in Cardiovascular Medicine myocardial infarction primary percutaneous coronary intervention MACE derivation validation |
| title | Estimation of Major Adverse Cardiovascular Events in Patients With Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: A Risk Prediction Score Model From a Derivation and Validation Study |
| title_full | Estimation of Major Adverse Cardiovascular Events in Patients With Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: A Risk Prediction Score Model From a Derivation and Validation Study |
| title_fullStr | Estimation of Major Adverse Cardiovascular Events in Patients With Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: A Risk Prediction Score Model From a Derivation and Validation Study |
| title_full_unstemmed | Estimation of Major Adverse Cardiovascular Events in Patients With Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: A Risk Prediction Score Model From a Derivation and Validation Study |
| title_short | Estimation of Major Adverse Cardiovascular Events in Patients With Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: A Risk Prediction Score Model From a Derivation and Validation Study |
| title_sort | estimation of major adverse cardiovascular events in patients with myocardial infarction undergoing primary percutaneous coronary intervention a risk prediction score model from a derivation and validation study |
| topic | myocardial infarction primary percutaneous coronary intervention MACE derivation validation |
| url | https://www.frontiersin.org/articles/10.3389/fcvm.2020.603621/full |
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