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Comparison of different thromboembolism risk scores with the predictive value of left atrial thrombosis and/or spontaneous ultrasound in patients with non-valvular atrial fibrillation
Vol 2, Issue 2, 2021
VIEWS - 3616 (Abstract)
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Abstract
Objective: To compare the predictive value of CHADS2, CHA2DS2-VASc, ATRIA and R2-CHADS2 scores and left atrial thrombosis and/or spontaneous ultrasound in patients with non-valvular atrial fibrillation (AF) Methods patients with non-valvular atrial fibrillation who were hospitalized in the Department of Cardiology of Sun Yat Sen Memorial. Results: 564 patients were included. The age of patients was (61.1 ± 10.1) years old, of which 63.3% were men. Hypertension was the most common complication, which was found in 49.6% of patients. Patients were divided into thrombus group (n = 82) and non-thrombus group (n = 482) according to the presence of left atrial thrombus and/or spontaneous ultrasound development CHADS2 score in thrombotic group (1[0,2]) was higher than that in non-thrombotic group (1[0,1]) (P < 0.05), and CHA2DS2-VASc score in thrombotic group (2[1,3]) was higher than that in non-thrombotic group (2[1,2]) (P < 0.05) 11.06%, 13.39%, 26.58%, 18.52% and 16.67% of patients with CHADS2 score of 0, 1, 2, 3 and 4 had left atrial thrombus and/or spontaneous ultrasound (P fortrend = 0.016), and 11.06%, 13.39% and 23.68% of patients with low, medium and high risk had left atrial thrombus and/or spontaneous ultrasound (P fortrend = 0.004); 10.81%, 10.19%, 16.57%, 21.05%, 21.05%, 16.67%, 14.29% of patients with CHA2DS2-VASc score of 0, 1, 2, 3, 4, 5, 6 or above had left atrial thrombosis and/or spontaneous ultrasound development (P fortrend = 0.019), and 8.75%, 13.90% and 19.35% of patients with low, medium and high risk had left atrial thrombosis and/or spontaneous ultrasound development (P fortrend = 0.004); The area under the ROC curve of ATRIA score and R2-CHADS2 score was 0.562. The samples based on this study had no statistical significance in the diagnosis of left atrial thrombosis and/or spontaneous ultrasound (P>0.05). Conclusion: CHADS2 score and CHA2DS2-VASc score have considerable and limited diagnostic value for left atrial thrombosis and/or spontaneous ultrasound in patients with non-valvular atrial fibrillation.
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References
1. Minno MN, Ambrosino P, DelloRusso A, et al. Prevalence of left atrial thrombus in patients with non-valvular atrial fibrillation. Thrombosis and Haemostasis. 2016; 115(03): 663-677. doi: 10.1160/th15-07-0532
2. Lowe BS, Kusunose K, Motoki I, et al. Prognostic Significance of Left Atrial Appendage “Sludge” in Patients with Atrial Fibrillation: A New Transesophageal Echocardiographic Thromboembolic Risk Factor. Journal of the American Society of Echocardiography. 2014; 27(11): 1176-1183. doi: 10.1016/j.echo.2014.08.016
3. Bernhardt P, Schmidt H, Hammerstingl C, et al. Patients with Atrial Fibrillation and Dense Spontaneous Echo Contrast at High Risk. Journal of the American College of Cardiology. 2005; 45(11): 1807-1812. doi: 10.1016/j.jacc.2004.11.071
4. Kim YG, Shim J, Oh SK, et al. Risk Factors for Ischemic Stroke in Atrial Fibrillation Patients Undergoing Radiof-requency Catheter Ablation. Scientific Reports. 2019; 9(1). doi: 10.1038/s41598-019-43566-z
5. Fatkin D, Kelly R, Feneley M. Relations between left atrial appendage blood flow velocity, spontaneous echocar-diographic contrast and thromboembolic risk in vivo. J Am Coll Cardiol. 1994; 23(4): 961.
6. Gage BF, Waterman AD, Shannon W, et al. Validation of Clinical Classification Schemes for Predicting Stroke. JAMA. 2001; 285(22): 2864. doi: 10.1001/jama.285.22.2864
7. Lip GYH, Nieuwlaat R, Pisters R, et al. Refining Clinical Risk Stratification for Predicting Stroke and Thrombo-embolism in Atrial Fibrillation Using a Novel Risk Factor-Based Approach. Chest. 2010; 137(2): 263-272. doi: 10.1378/chest.09-1584
8. Piccini JP, Stevens SR, Chang Y, et al. Renal Dysfunction as a Predictor of Stroke and Systemic Embolism in Patients with Nonvalvular Atrial Fibrillation. Circulation. 2013; 127(2): 224-232. doi: 10.1161/circulationaha.112.107128
9. Singer DE, Chang Y, Borowsky LH, et al. A New Risk Scheme to Predict Ischemic Stroke and Other Thrombo-embolism in Atrial Fibrillation: The ATRIA Study Stroke Risk Score. Journal of the American Heart Association. 2013; 2(3). doi: 10.1161/jaha.113.000250
10. Huang C, Zhang S, Huang D, et al. Atrial fibrillation: current understanding and treatment recommendations-2018. Chinese Journal of Cardiac Pacing and Electrophysiology. 2018; 32(4): 315.
11. Willens HJ, Gómez-Marín O, Nelson K, et al. Correlation of CHADS2 and CHA2DS2-VASc Scores with Transesophageal Echocardiography Risk Factors for Thromboembolism in a Multiethnic United States Population with Nonvalvular Atrial Fibrillation. Journal of the American Society of Echocardiography. 2013; 26(2): 175-184. doi: 10.1016/j.echo.2012.11.002
12. Guo Y, Apostolakis S, Blann AD, et al. Validation of contemporary stroke and bleeding risk stratification scores in non-anticoagulated Chinese patients with atrial fibrillation. International Journal of Cardiology. 2013; 168(2): 904-909. doi: 10.1016/j.ijcard.2012.10.052
13. Hamatani Y, Ogawa H, Takabayashi K, et al. Left atrial enlargement is an independent predictor of stroke and systemic embolism in patients with non-valvular atrial fibrillation. Scientific Reports. 2016; 6(1). doi: 10.1038/srep31042
14. Di Castelnuovo A, Veronesi G, Costanzo S, et al. NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) and the Risk of Stroke. Stroke. 2019; 50(3): 610-617. doi: 10.1161/strokeaha.118.023218
15. He H, Guo J, Zhang A. The value of urine albumin in predicting thromboembolic events for patients with non-valvular atrial fibrillation. International Journal of Cardiology. 2016; 221: 827-830. doi: 10.1016/j.ijcard.2016.07.145
16. Li Q, Liao J, Kong B, et al. The relationship between left atrial appendage parameters on transesophageal ultrasound and left atrial appendage thrombus and/or spontaneous imaging in patients with atrial fibrillation. Chinese Journal of Cardiac Pacing and Electrophysiology. 2017; 31(2): 131.
17. Roldan V, Marín F, Fernández H, et al. Renal Impairment in a “Real-Life” Cohort of Anticoagulated Patients with Atrial Fibrillation (Implications for Thromboembolism and Bleeding). The American Journal of Cardiology. 2013; 111(8): 1159-1164. doi: 10.1016/j.amjcard.2012.12.045
18. Van Staa TP, Setakis E, Di Tanna GL, et al. A comparison of risk stratification schemes for stroke in 79884 atrial fibrillation patients in general practice. Journal of Thrombosis and Haemostasis. 2011; 9(1): 39-48. doi: 10.1111/j.1538-7836.2010.04085.x
19. Tsadok MA, Senderey AB, Reges O, et al. Comparison of Stroke Risk Stratification Scores for Atrial Fibrillation. The American Journal of Cardiology. 2019; 123(11): 1828-1834. doi: 10.1016/j.amjcard.2019.02.056
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Prof. Prakash Deedwania
University of California,
San Francisco, United States