The China Hypertrophic Cardiomyopathy Project (CHCMP): The Rationale and Design of a Multicenter, Prospective, Registry Cohort Study

Tuohy CV, et al. Hypertrophic cardiomyopathy: the future of treatment. Eur J Heart Fail. 2020;22(2):228–40.

Article  PubMed  Google Scholar 

Ommen SR, et al. 2020 AHA/ACC guideline for the diagnosis and treatment of patients with hypertrophic cardiomyopathy: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2020;142(25):e558–631.

PubMed  Google Scholar 

Liu J, et al. Improvement in sudden cardiac death risk prediction by the enhanced American College of Cardiology/American Heart Association strategy in Chinese patients with hypertrophic cardiomyopathy. Heart Rhythm. 2020;17(10):1658–63.

Article  PubMed  Google Scholar 

Semsarian C, et al. New perspectives on the prevalence of hypertrophic cardiomyopathy. J Am Coll Cardiol. 2015;65(12):1249–54.

Article  PubMed  Google Scholar 

Norrish G, et al. Clinical features and natural history of preadolescent nonsyndromic hypertrophic cardiomyopathy. J Am Coll Cardiol. 2022;79(20):1986–97.

Article  PubMed  PubMed Central  Google Scholar 

Maron BJ. Clinical Course and Management of Hypertrophic Cardiomyopathy. N Engl J Med. 2018;379(7):655–68.

Article  PubMed  Google Scholar 

Authors/Task Force, m., 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): p. 2733-79.

Maron MS, et al. Enhanced American College of Cardiology/American Heart Association strategy for prevention of sudden cardiac death in high-risk patients with hypertrophic cardiomyopathy. JAMA Cardiol. 2019;4(7):644–57.

Article  PubMed  PubMed Central  Google Scholar 

Dong Y, et al. Validation of the 2020 AHA/ACC risk stratification for sudden cardiac death in Chinese patients with hypertrophic cardiomyopathy. Front Cardiovasc Med. 2021;8: 691653.

Article  PubMed  PubMed Central  Google Scholar 

Wang, J., et al., Assessment of late gadolinium enhancement in hypertrophic cardiomyopathy improves risk stratification based on current guidelines. Eur Heart J, 2023.

Leonardi S, et al. Usefulness of cardiac magnetic resonance in assessing the risk of ventricular arrhythmias and sudden death in patients with hypertrophic cardiomyopathy. Eur Heart J. 2009;30(16):2003–10.

Article  PubMed  Google Scholar 

Hen Y, et al. High signal intensity on t2-weighted cardiovascular magnetic resonance imaging predicts life-threatening arrhythmic events in hypertrophic cardiomyopathy patients. Circ J. 2018;82(4):1062–9.

Article  PubMed  Google Scholar 

Ismail TF, et al. Role of late gadolinium enhancement cardiovascular magnetic resonance in the risk stratification of hypertrophic cardiomyopathy. Heart. 2014;100(23):1851–8.

Article  PubMed  Google Scholar 

Ochoa JP, et al. Formin Homology 2 domain containing 3 (FHOD3) is a genetic basis for hypertrophic cardiomyopathy. J Am Coll Cardiol. 2018;72(20):2457–67.

Article  CAS  PubMed  Google Scholar 

Lopes LR, et al. Alpha-protein kinase 3 (ALPK3) truncating variants are a cause of autosomal dominant hypertrophic cardiomyopathy. Eur Heart J. 2021;42(32):3063–73.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Matthia EL, et al. Circulating biomarkers in hypertrophic cardiomyopathy. J Am Heart Assoc. 2022;11(23):e027618.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Johnson KW, et al. Artificial intelligence in cardiology. J Am Coll Cardiol. 2018;71(23):2668–79.

Article  PubMed  Google Scholar 

Motwani M, et al. Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis. Eur Heart J. 2017;38(7):500–7.

PubMed  Google Scholar 

Deo RC. Machine learning in medicine. Circulation. 2015;132(20):1920–30.

Article  PubMed  PubMed Central  Google Scholar 

Weng SF, et al. Can machine-learning improve cardiovascular risk prediction using routine clinical data? PLoS One. 2017;12(4):e0174944.

Article  PubMed  PubMed Central  Google Scholar 

Heo J, et al. Machine learning-based model for prediction of outcomes in acute stroke. Stroke. 2019;50(5):1263–5.

Article  PubMed  Google Scholar 

Alaa AM, et al. Cardiovascular disease risk prediction using automated machine learning: a prospective study of 423,604 UK Biobank participants. PLoS One. 2019;14(5):e0213653.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Al’Aref SJ, et al. Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging. Eur Heart J. 2019;40(24):1975–86.

Article  CAS  PubMed  Google Scholar 

Javaid A, et al. Medicine 2032: The future of cardiovascular disease prevention with machine learning and digital health technology. Am J Prev Cardiol. 2022;12:100379.

Article  PubMed  PubMed Central  Google Scholar 

Lang RM, 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):1–39 (e14).

Article  PubMed  Google Scholar 

Sasson Z, et al. Doppler echocardiographic determination of the pressure gradient in hypertrophic cardiomyopathy. J Am Coll Cardiol. 1988;11(4):752–6.

Article  CAS  PubMed  Google Scholar 

Kumar S, et al. Standardized goal-directed valsalva maneuver for assessment of inducible left ventricular outflow tract obstruction in hypertrophic cardiomyopathy. J Am Soc Echocardiogr. 2018;31(7):791–8.

Article  PubMed  Google Scholar 

Veselka J, Anavekar NS, Charron P. Hypertrophic obstructive cardiomyopathy. Lancet. 2017;389(10075):1253–67.

Article  PubMed  Google Scholar 

Porter TR, et al. Guidelines for the cardiac sonographer in the performance of contrast echocardiography: a focused update from the American Society of Echocardiography. J Am Soc Echocardiogr. 2014;27(8):797–810.

Article  PubMed  Google Scholar 

Kramer CM, et al. Hypertrophic cardiomyopathy registry: the rationale and design of an international, observational study of hypertrophic cardiomyopathy. Am Heart J. 2015;170(2):223–30.

Article  PubMed  PubMed Central  Google Scholar 

Ingles, J. and D.G. MacArthur, The moral and practical urgency of increasing diversity in genomics. Eur Heart J, 2023.

Ingles J, et al. Evaluating the clinical validity of hypertrophic cardiomyopathy genes. Circ Genom Precis Med. 2019;12(2):e002460.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang J, et al. Malignant effects of multiple rare variants in sarcomere genes on the prognosis of patients with hypertrophic cardiomyopathy. Eur J Heart Fail. 2014;16(9):950–7.

Article  PubMed  Google Scholar 

Pua CJ, et al. Genetic studies of hypertrophic cardiomyopathy in singaporeans identify variants in TNNI3 and TNNT2 that are common in chinese patients. Circ Genom Precis Med. 2020;13(5):424–34.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Walsh R, et al. Minor hypertrophic cardiomyopathy genes, major insights into the genetics of cardiomyopathies. Nat Rev Cardiol. 2022;19(3):151–67.

Article  PubMed  Google Scholar 

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