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Identifying Obstructive Hypertrophic Cardiomyopathy from Nonobstructive Hypertrophic Cardiomyopathy: Development and Validation of a Model Based on Electrocardiogram Features Cover

Identifying Obstructive Hypertrophic Cardiomyopathy from Nonobstructive Hypertrophic Cardiomyopathy: Development and Validation of a Model Based on Electrocardiogram Features

Open Access
|Aug 2023

References

  1. 1Geske JB, Gersh BJ. The hypertrophic cardiomyopathy paradox: better with age. Eur Heart J. 2019; 40(12): 994996. DOI: 10.1093/eurheartj/ehy889
  2. 2Maron MS, Olivotto I, Zenovich AG, et al. Hypertrophic cardiomyopathy is predominantly a disease of left ventricular outflow tract obstruction. Circulation. 2006; 114(21): 22322239. DOI: 10.1161/CIRCULATIONAHA.106.644682
  3. 3Lu DY, Pozios I, Haileselassie B, et al. Clinical outcomes in patients with nonobstructive, labile, and obstructive hypertrophic cardiomyopathy. J Am Heart Assoc. 2018; 7(5): e006657. DOI: 10.1161/JAHA.117.006657
  4. 4Maron MS, Rowin EJ, Olivotto I, et al. Contemporary natural history and management of nonobstructive hypertrophic cardiomyopathy. J Am Coll Cardiol. 2016; 67(12): 13991409. DOI: 10.1016/j.jacc.2016.01.023
  5. 5Maron BJ, Desai MY, Nishimura RA, et al. Management of hypertrophic cardiomyopathy: JACC State-of-the-Art review. J Am Coll Cardiol. 2022; 79(4): 390414. DOI: 10.1016/j.jacc.2021.11.021
  6. 6Kimmelstiel C, Zisa D, Kuttab J, et al. Guideline-based referral for septal reduction therapy in obstructive hypertrophic cardiomyopathy is associated with excellent clinical putcomes. Circulation. Cardiovascular interventions. 2019; 12(7): e007673. DOI: 10.1161/CIRCINTERVENTIONS.118.007673
  7. 7Kim L, Swaminathan R, Looser P, et al. Hospital volume outcomes after septal myectomy and alcohol septal ablation for treatment of obstructive hypertrophic cardiomyopathy: US Nationwide Inpatient Database. 2003–2011. JAMA cardiology. 2016; 1(3): 324332. DOI: 10.1001/jamacardio.2016.0252
  8. 8Maron BJ, Desai MY, Nishimura RA, et al. Diagnosis and evaluation of hypertrophic cardiomyopathy: JACC State-of-the-Art review. J Am Coll Cardiol. 2022; 79(4): 372389. DOI: 10.1016/j.jacc.2021.12.002
  9. 9Ommen SR, Mital S, Burke MA, et al. 2020 AHA/ACC guideline for the diagnosis and treatment of patients with hypertrophic cardiomyopathy: executive summary: a report of the American College of Cardiology/American Heart Association Joint Committee on clinical practice guidelines. Circulation. 2020; 142(25): e533e557. DOI: 10.1161/CIR.0000000000000945
  10. 10Captur G, Manisty CH, Raman B, et al. Maximal wall thickness measurement in hypertrophic cardiomyopathy: biomarker variability and its impact on clinical care. JACC Cardiovasc Imaging. 2021; 14(11): 21232134. DOI: 10.1016/j.jcmg.2021.03.032
  11. 11Finocchiaro G, Sheikh N, Biagini E, et al. The electrocardiogram in the diagnosis and management of patients with hypertrophic cardiomyopathy. Heart Rhythm. 2020; 17(1): 142151. DOI: 10.1016/j.hrthm.2019.07.019
  12. 12Montgomery JV, Harris KM, Casey SA, et al. Relation of electrocardiographic patterns to phenotypic expression and clinical outcome in hypertrophic cardiomyopathy. Am J Cardiol. 2005; 96(2): 270275. DOI: 10.1016/j.amjcard.2005.03.058
  13. 13Maron BJ, Friedman RA, Kligfield P, et al. Assessment of the 12-lead electrocardiogram as a screening test for detection of cardiovascular disease in healthy general populations of young people (12–25 years of age): a scientific statement from the American Heart Association and the American College of Cardiology. J Am Coll Cardiol. 2014; 64(14): 14791514. DOI: 10.1016/j.jacc.2014.05.006
  14. 14Guo L, Gao C, Yang W, et al. Derivation and validation of a screening model for hypertrophic cardiomyopathy based on electrocardiogram features. Frontiers in Cardiovascular Medicine. 2022; 9. DOI: 10.3389/fcvm.2022.889523
  15. 15Ko WY, Siontis KC, Attia ZI, et al. Detection of hypertrophic cardiomyopathy using a convolutional neural network-enabled electrocardiogram. J Am Coll Cardiol. 2020; 75(7): 722733. DOI: 10.1016/j.jacc.2019.12.030
  16. 16Lyon A, Ariga R, Mincholé A, et al. Distinct ECG phenotypes identified in hypertrophic cardiomyopathy using machine learning associate with arrhythmic risk markers. Frontiers in physiology. 2018; 9: 213226. DOI: 10.3389/fphys.2018.00213
  17. 17Authors/Task Force M, Elliott PM, Anastasakis A, et al. 2014 ESC guidelines on diagnosis and management of hypertrophic cardiomyopathy: The task force for the diagnosis and management of hypertrophic cardiomyopathy of the European Society of Cardiology (ESC). Eur Heart J. 2014; 35(39): 27332779. DOI: 10.1093/eurheartj/ehu284
  18. 18Gersh BJ, Maron BJ, Bonow RO, et al. 2011 ACCF/AHA guideline for the diagnosis and treatment of hypertrophic cardiomyopathy: A report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation. 2011; 124(24): e783831. DOI: 10.1161/CIR.0b013e318223e2bd
  19. 19Nagueh SF, Smiseth OA, Appleton CP, et al. Recommendations for the evaluation of left ventricular diastolic function by echocardiography: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging. 2016; 17(12): 13211360. DOI: 10.1093/ehjci/jew082
  20. 20Lang RM, Badano LP, Mor-Avi V, et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr. 2015; 28(1): 139. DOI: 10.1016/j.echo.2014.10.003
  21. 21Alba AC, Agoritsas T, Walsh M, et al. Discrimination and calibration of clinical prediction models: users’ guides to the medical literature. JAMA. 2017; 318(14): 13771384. DOI: 10.1001/jama.2017.12126
  22. 22Fitzgerald M, Saville BR, Lewis RJ. Decision curve analysis. JAMA. 2015; 313(4): 409410. DOI: 10.1001/jama.2015.37
  23. 23Zhou M, Ta S, Hahn RT, et al. Percutaneous intramyocardial septal radiofrequency ablation in patients with drug-refractory hypertrophic obstructive cardiomyopathy. JAMA Cardiol. 2022; 7(5): 529538. DOI: 10.1001/jamacardio.2022.0259
  24. 24Gossios T, Savvatis K, Zegkos T, et al. Deciphering hypertrophic cardiomyopathy with electrocardiography. Heart Fail Rev. 2022; 27(4): 13131323. DOI: 10.1007/s10741-021-10147-0
  25. 25Savage DD, Seides SF, Clark CE, et al. Electrocardiographic findings in patients with obstructive and nonobstructive hypertrophic cardiomyopathy. Circulation. 1978; 58(3 Pt 1): 402408. DOI: 10.1161/01.CIR.58.3.402
  26. 26Tison GH, Siontis KC, Abreau S, et al. Assessment of disease status and treatment response with artificial intelligence-enhanced electrocardiography in obstructive hypertrophic cardiomyopathy. J Am Coll Cardiol. 2022; 79(10): 10321034. DOI: 10.1016/j.jacc.2022.01.005
  27. 27Chen Y, Sun G, Guo X, et al. Performance of a novel ECG criterion for improving detection of left ventricular hypertrophy: a cross-sectional study in a general Chinese population. BMJ Open. 2021; 11(9): e051172. DOI: 10.1136/bmjopen-2021-051172
  28. 28Van Kleef M, Visseren FLJ, Vernooij JWP, et al. Four ECG left ventricular hypertrophy criteria and the risk of cardiovascular events and mortality in patients with vascular disease. J Hypertens. 2018; 36(9): 18651873. DOI: 10.1097/HJH.0000000000001785
  29. 29Mino T, Kimura S, Kitaura A, et al. Can left ventricular hypertrophy on electrocardiography detect severe aortic valve stenosis? PLoS One. 2020; 15(11): e0241591. DOI: 10.1371/journal.pone.0241591
  30. 30Girasis C, Vassilikos V, Efthimiadis GK, et al. Patients with hypertrophic cardiomyopathy at risk for paroxysmal atrial fibrillation: advanced echocardiographic evaluation of the left atrium combined with non-invasive P-wave analysis. Eur Heart J Cardiovasc Imaging. 2013; 14(5): 425434. DOI: 10.1093/ehjci/jes172
  31. 31Tuluce K, Ozerkan F, Yakar Tuluce S, et al. Relationships between P wave dispersion, atrial electromechanical delay, left atrial remodeling, and NT-proBNP levels, in patients with hypertrophic cardiomyopathy. Cardiol J. 2015; 22(1): 94100. DOI: 10.5603/CJ.a2014.0025
  32. 32Ozdemir O, Soylu M, Demir AD, et al. P-wave durations as a predictor for atrial fibrillation development in patients with hypertrophic cardiomyopathy. Int J Cardiol. 2004; 94(2–3): 163166. DOI: 10.1016/j.ijcard.2003.01.001
  33. 33Tani T, Tanabe K, Ono M, et al. Left atrial volume and the risk of paroxysmal atrial fibrillation in patients with hypertrophic cardiomyopathy. J Am Soc Echocardiogr. 2004; 17(6): 644648. DOI: 10.1016/j.echo.2004.02.010
  34. 34Lu DY, Pozios I, Haileselassie B, et al. Clinical outcomes in patients with nonobstructive, labile, and obstructive hypertrophic cardiomyopathy. J Am Heart Assoc. 2018; 7(5): e006657. DOI: 10.1161/JAHA.117.006657
  35. 35Pozios I, Corona-Villalobos C, Sorensen LL, et al. Comparison of outcomes in patients with nonobstructive, labile-obstructive, and chronically obstructive hypertrophic cardiomyopathy. Am J Cardiol. 2015; 116(6): 938944. DOI: 10.1016/j.amjcard.2015.06.018
  36. 36Geske JB, Sorajja P, Ommen SR, et al. Variability of left ventricular outflow tract gradient during cardiac catheterization in patients with hypertrophic cardiomyopathy. JACC Cardiovasc Interv. 2011; 4(6): 704709. DOI: 10.1016/j.jcin.2011.02.014
  37. 37Cheng TO. Mechanisms of variability of left ventricular outflow tract gradient in hypertrophic cardiomyopathy. Int J Cardiol. 2010; 145(2): 169171. DOI: 10.1016/j.ijcard.2010.05.051
  38. 38Zuo L, Hsi D, Zhang L, et al. Electrocardiographic QRS voltage amplitude improvement by intramyocardial radiofrequency ablation in patients with hypertrophic obstructive cardiomyopathy and one year follow up. Journal of electrocardiology. 2020; 61: 164169. DOI: 10.1016/j.jelectrocard.2020.06.013
  39. 39Kwon JM, Lee SY, Jeon KH, et al. Deep learning-based algorithm for detecting aortic stenosis using electrocardiography. J Am Heart Assoc. 2020; 9(7): e014717. DOI: 10.1161/JAHA.119.014717
  40. 40Siontis KC, Liu K, Bos JM, et al. Detection of hypertrophic cardiomyopathy by an artificial intelligence electrocardiogram in children and adolescents. Int J Cardiol. 2021; 340: 4247. DOI: 10.1016/j.ijcard.2021.08.026
DOI: https://doi.org/10.5334/gh.1250 | Journal eISSN: 2211-8179
Language: English
Submitted on: Oct 21, 2022
Accepted on: Jun 27, 2023
Published on: Aug 4, 2023
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2023 Lanyan Guo, Zhiling Ma, Weiping Yang, Fuyang Zhang, Hong Shao, Liwen Liu, Chao Gao, Ling Tao, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.