Establishment and validation of a predictive model for new onset atrial fibrillation in patients with acute coronary syndrome during hospitalization

LI Jun-zheng; XU Xiang; ZHANG Zhi-hui; WU Na; YUAN Zhi-quan; JIA Xiao-yue; LI Cheng-ying; WU Long; XIANG Ying; ZHONG Li; LI Ya-fei

doi:10.16462/j.cnki.zhjbkz.2021.02.016

Volume 25 Issue 2

Feb. 2021

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Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2021 > 25(2): 204-210

LI Jun-zheng, XU Xiang, ZHANG Zhi-hui, WU Na, YUAN Zhi-quan, JIA Xiao-yue, LI Cheng-ying, WU Long, XIANG Ying, ZHONG Li, LI Ya-fei. Establishment and validation of a predictive model for new onset atrial fibrillation in patients with acute coronary syndrome during hospitalization[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(2): 204-210. doi: 10.16462/j.cnki.zhjbkz.2021.02.016

Citation:

LI Jun-zheng, XU Xiang, ZHANG Zhi-hui, WU Na, YUAN Zhi-quan, JIA Xiao-yue, LI Cheng-ying, WU Long, XIANG Ying, ZHONG Li, LI Ya-fei. Establishment and validation of a predictive model for new onset atrial fibrillation in patients with acute coronary syndrome during hospitalization[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(2): 204-210. doi: 10.16462/j.cnki.zhjbkz.2021.02.016

Citation:

LI Jun-zheng, XU Xiang, ZHANG Zhi-hui, WU Na, YUAN Zhi-quan, JIA Xiao-yue, LI Cheng-ying, WU Long, XIANG Ying, ZHONG Li, LI Ya-fei. Establishment and validation of a predictive model for new onset atrial fibrillation in patients with acute coronary syndrome during hospitalization[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2021, 25(2): 204-210. doi: 10.16462/j.cnki.zhjbkz.2021.02.016

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Establishment and validation of a predictive model for new onset atrial fibrillation in patients with acute coronary syndrome during hospitalization

doi: 10.16462/j.cnki.zhjbkz.2021.02.016

1.
Department of Epidemiology, College of Preventive Medicine, Army Medical University, Chongqing 400038, China
2.
Department of Cardiology, First Affiliated Hospital, Army Medical University, Chongqing 400038, China
3.
Cardiovascular Disease Center, Third Affiliated Hospital of Chongqing Medical University, Chongqing 401120, China

Funds:

Youth Science Foundation Project of National Natural Science Foundation of China 81502883

Received Date: 2020-08-24
Rev Recd Date: 2021-01-02
Publish Date: 2021-02-10

Abstract

Abstract

Objective To establish a predictive model of new onset atrial fibrillation in patients with acute coronary syndrome (ACS) during admission, so as to provide scientific basis for early detection of high-risk patients and timely intervention measures. Methods A retrospective cohort study was conducted among 1 915 patients with ACS who were admitted to the Department of Cardiology of a large general hospital between January 2010 and December 2019. Patients were randomly divided into two groups: model group and validation group. In the model group, a multivariate Logistic regression analysis model was used to screen the independent factors associated with new onset atrial fibrillation. Regression prediction model and nomogram were established, and validated in the validation group. Area under curve (AUC) of receiver operating characteristic curve (ROC) and Hosmer-lemoshow test were used to evaluate the discrimination and calibration of the model, respectively. Results There were 958 cases in the model group comprising 62 new onset atrial fibrillation cases, and 957 cases in the validation group comprising 65 new onset atrial fibrillation cases. In the model group, seven indicators were independently associated with atrial fibrillation, including age, heart rate at admission, Killip classification of heart failure, N-terminal pro-brain natriuretic peptide (NT-proBNP) level, left atrial diameter, right atrial diameter and neutrophil count. In the modeling group, the AUC was 0.91 (95% CI: 0.88-0.94) in model group and 0.86 (95% CI: 0.81-0.91) in validation group. Calibration plot and goodness of fit test (in modeling group and validation group, P>0.05) indicated that the prediction model had a good calibration ability. Conclusions In this study, the prediction model of new onset atrial fibrillation in patients with acute coronary syndrome was successfully constructed, which has a good discrimination and calibration, the nomogram could conveniently be used and intuitively predict the risk of atrial fibrillation, thus provides foundation for early intervention and improvement of prognosis in clinical practice.
- Acute coronary syndrome,
- New onset atrial fibrillation,
- Prediction model,
- Model validation,
- Nomogram

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References(19)

References

[1]	段文涛, 张峰, 史东, 等.心房颤动相关危险因素及药物治疗研究新进展[J].武汉大学学报(医学版), 2020, 41(1):164-168. DOI: 10.14188/j.1671-8852.2018.0771. Duan WT, Zhang F, Shi D, et al. Recent advances in risk factors and drug therapy of atrial fibrillation[J]. Med J Wuhan University, 2020, 41(1):164-168. DOI: 10.14188/j.1671-8852.2018.0771.
[2]	Smith JN, Negrelli JM, Manek MB, et al. Diagnosis and management of acute coronary syndrome: an evidence-based update[J]. J Am Board Fam Med, 2015, 28(2):283-293. DOI: 10.3122/jabfm.2015.02.140189.
[3]	González-Pacheco H, Márquez MF, Arias-Mendoza A, et al. Clinical features and in-hospital mortality associated with different types of atrial fibrillation in patients with acute coronary syndrome with and without ST elevation[J]. J Cardiol, 2015, 66(2):148-154. DOI: 10.1016/j.jjcc.2014.11.001.
[4]	Wang CL, Chen PC, Juang HT, et al. Adverse outcomes associated with pre-existing and new-onset atrial fibrillation in patients with acute coronary syndrome: a retrospective cohort study[J]. Cardiol Ther, 2019, 8(1):117-127. DOI: 10.1007/s40119-019-0136-3.
[5]	Galvão Braga C, Ramos V, Vieira C, et al. New-onset atrial fibrillation during acute coronary syndromes: predictors and prognosis[J]. Rev Port Cardiol, 2014, 33(5):281-287. DOI: 10.1016/j.repc.2013.10.017.
[6]	Almendro-Delia M, Valle-Caballero MJ, Garcia-Rubira JC, et al. Prognostic impact of atrial fibrillation in acute coronary syndromes: results from the ARIAM registry[J]. Eur Heart Acute Cardiovasc Care, 2014, 3(2):141-148. DOI: 10.1177/2048872613517370.
[7]	Nagai M, Itoh T, Ishida M, et al. New-onset atrial fibrillation in patients with acute coronary syndrome may be associated with worse prognosis and future heart failure[J]. J Arrhythm, 2019, 35(2):182-189. DOI: 10.1002/joa3.12154.
[8]	Thygesen K, Alpert JS, Jaffe AS, et al. Third universal definition of myocardial infarction[J]. J Am Col Cardiol, 2012, 60(16):1581-1598. DOI: 10.1016/j.jacc.2012.08.001.
[9]	Camm AJ, Kirchhof P, Lip GY, et al. Guidelines for the management of atrial fibrillation: the task force for the management of atrial fibrillation of the European Society of Cardiology (ESC)[J]. Eur Heart J, 2010, 31(19):2369-2429. DOI: 10.1093/eurheartj/ehq278.
[10]	Dorje T, Wang X, Shao M, et al. Plasma N-terminal pro-brain natriuretic peptide levels predict new-onset atrial fibrillation in patients with acute myocardial infarction[J]. Int J Cardiol, 2013, 168(3):3135-3137. DOI: 10.1016/j.ijcard.2013.04.032.
[11]	Zhang H, Dong P, Yang X, et al. Prognostic indicators of new onset atrial fibrillation in patients with acute coronary syndrome[J]. Clin Cardiol, 2020, 43(6):647-651. DOI: 10.1002/clc.23363.
[12]	Ulus T, Isgandarov K, Yilmaz AS, et al. Predictors of new-onset atrial fibrillation in elderly patients with acute coronary syndrome undergoing percutaneous coronary intervention[J]. Aging Clin Exp Res, 2018, 30(12):1475-1482. DOI: 10.1007/s40520-018-0926-9.
[13]	Holl MJ, Van Den Bos EJ, Van Domburg RT, et al. NT-proBNP is associated with mortality and adverse cardiac events in patients with atrial fibrillation presenting to the emergency department[J]. Clini Cardiol, 2018, 41(3):400-405. DOI: 10.1002/clc.22883.
[14]	Mazzone A, Scalese M, Paradossi U, et al. Development and validation of a risk stratification score for new-onset atrial fibrillation in STEMI patients undergoing primary percutaneous coronary intervention[J]. Int J Clini Prac, 2018, 72(4):e13087. DOI: 10.1111/ijcp.13087.
[15]	Jensen MT, Pereira M, Araujo C, et al. Heart rate at admission is a predictor of in-hospital mortality in patients with acute coronary syndromes: results from 58 European hospitals: The European Hospital Benchmarking by Outcomes in acute coronary syndrome Processes study[J]. Eur Heart J Acute Cardiovasc Care, 2018, 7(2):49-57. DOI: 10.1177/2048872616672077.
[16]	He J, Yang Y, Zhang G, et al. Clinical risk factors for new-onset atrial fibrillation in acute myocardial infarction: a systematic review and meta-analysis[J]. Med, 2019, 98(26):e15960. DOI: 10.1097/md.0000000000015960.
[17]	Sepehri Shamloo A, Bollmann A, Dagres N, et al. Natriuretic peptides: biomarkers for atrial fibrillation management[J]. Clin Res in Cardiol, 2020, 109(8):957-966. DOI: 10.1007/s00392-020-01608-x.
[18]	Moons KG, Altman DG, Reitsma JB, et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration[J]. Ann Int med, 2015, 162(1):W1-W73. DOI: 10.7326/m14-0698.
[19]	Karabaǧ Y, Rencuzogullari I, Çaǧdaš M, et al. Association between BNP levels and new-onset atrial fibrillation: a propensity score approach[J]. Herz, 2018, 43(6):548-554. DOI: 10.1007/s00059-017-4598-6.