The amount of late gadolinium enhancement outperforms current guideline-recommended criteria in the identification of patients with hypertrophic cardiomyopathy at risk of sudden cardiac death

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art_FREITAS_The_amount_of_late_gadolinium_enhancement_outperforms_current_2019.PDF (1.25 MB)
Citações na Scopus
58
Tipo de produção
article
Data de publicação
2019
DOI
Scopus
Web of Science
PubMed
Título da Revista
ISSN da Revista
Título do Volume
Editora
BMC
Autores
FREITAS, Pedro
FERREIRA, Antonio Miguel
MESQUITA, Joao
ABECASIS, Joao
MARQUES, Hugo
SARAIVA, Carla
MATOS, Daniel Nascimento
RODRIGUES, Rita
Citação
JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE, v.21, n.1, article ID 50, 10p, 2019
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Background Identifying the patients with hypertrophic cardiomyopathy (HCM) in whom the risk of sudden cardiac death (SCD) justifies the implantation of a cardioverter-defibrillator (ICD) in primary prevention remains challenging. Different risk stratification and criteria are used by the European and American guidelines in this setting. We sought to evaluate the role of cardiovascular magnetic resonance (CMR) late gadolinium enhancement (LGE) in improving these risk stratification strategies. Methods We conducted a multicentric retrospective analysis of HCM patients who underwent CMR for diagnostic confirmation and/or risk stratification. Eligibility for ICD was assessed according to the HCM Risk-SCD score and the American College of Cardiology Foundation/American Heart Association (ACCF/AHA) algorithm. The amount of LGE was quantified (LGE%) and categorized as 0%, 0.1-10%, 10.1-19.9% and >= 20%. The primary endpoint was a composite of SCD, aborted SCD, sustained ventricular tachycardia (VT), or appropriate ICD discharge. Results A total of 493 patients were available for analysis (58% male, median age 46 years). LGE was present in 79% of patients, with a median LGE% of 2.9% (IQR 0.4-8.4%). The concordance between risk assessment by the HCM Risk-SCD, ACCF/AHA and LGE was relatively weak. During a median follow-up of 3.4 years (IQR 1.5-6.8 years), 23 patients experienced an event (12 SCDs, 6 appropriate ICD discharges and 5 sustained VTs). The amount of LGE was the only independent predictor of outcome (adjusted HR: 1.08; 95% CI: 1.04-1.12; p < 0.001) after adjustment for the HCM Risk-SCD and ACCF/AHA criteria. The amount of LGE showed greater discriminative power (C-statistic 0.84; 95% CI: 0.76-0.91) than the ACCF/AHA (C-statistic 0.61; 95% CI: 0.49-0.72; p for comparison < 0.001) and the HCM Risk-SCD (C-statistic 0.68; 95% CI: 0.59-0.78; p for comparison = 0.006). LGE was able to increase the discriminative power of the ACCF/AHA and HCM Risk-SCD criteria, with net reclassification improvements of 0.36 (p = 0.021) and 0.43 (p = 0.011), respectively. Conclusions The amount of LGE seems to outperform the HCM Risk-SCD score and the ACCF/AHA algorithm in the identification of HCM patients at increased risk of SCD and reclassifies a relevant proportion of patients.
Palavras-chave
Hypertrophic cardiomyopathy, Risk stratification
URI
https://observatorio.fm.usp.br/handle/OPI/33453
Referências
  1. Bruder O, 2010, J AM COLL CARDIOL, V56, P875, DOI 10.1016/j.jacc.2010.05.007
  2. Chan RH, 2014, CIRCULATION, V130, P484, DOI 10.1161/CIRCULATIONAHA.113.007094
  3. Doesch C, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-06533-0
  4. Elliott PM, 2014, EUR HEART J, V35, P2733, DOI 10.1093/eurheartj/ehu284
  5. Fernandez A, 2016, AM J CARDIOL, V118, P121, DOI 10.1016/j.amjcard.2016.04.021
  6. Gersh BJ, 2011, J AM COLL CARDIOL, V58, pE212, DOI 10.1016/j.jacc.2011.06.011
  7. Greenberg H, 2004, J AM COLL CARDIOL, V43, P1459, DOI 10.1016/j.jacc.2003.11.038
  8. Ismail TF, 2014, HEART, V100, P1851, DOI 10.1136/heartjnl-2013-305471
  9. Kramer CM, 2015, AM HEART J, V170, P223, DOI 10.1016/j.ahj.2015.05.013
  10. Maron BJ, 2015, AM J CARDIOL, V116, P757, DOI 10.1016/j.amjcard.2015.05.047
  11. Maron BJ, 2013, J AM COLL CARDIOL, V61, P1527, DOI 10.1016/j.jacc.2013.01.037
  12. Mentias A, 2018, J AM COLL CARDIOL, V72, P857, DOI 10.1016/j.jacc.2018.05.060
  13. O'Hanlon R, 2010, J AM COLL CARDIOL, V56, P867, DOI 10.1016/j.jacc.2010.05.010
  14. O'Mahony C, 2018, CIRCULATION, V137, P1015, DOI 10.1161/CIRCULATIONAHA.117.030437
  15. O'Mahony C, 2014, EUR HEART J, V35, P2010, DOI 10.1093/eurheartj/eht439
  16. O'Mahony C, 2013, HEART, V99, P534, DOI 10.1136/heartjnl-2012-303271
  17. Rubinshtein R, 2010, CIRC-HEART FAIL, V3, P51, DOI 10.1161/CIRCHEARTFAILURE.109.854026
  18. Sakamoto N, 2015, HEART RHYTHM, V12, P1276, DOI 10.1016/j.hrthm.2015.02.004
  19. Uno H, 2011, STAT MED, V30, P1105, DOI 10.1002/sim.4154
  20. Vriesendorp PA, 2015, CIRC-ARRHYTHMIA ELEC, V8, P829, DOI 10.1161/CIRCEP.114.002553
  21. Weng Z, 2016, JACC-CARDIOVASC IMAG, V9, P1392, DOI 10.1016/j.jcmg.2016.02.031

Coleções
Artigos e Materiais de Revistas Científicas - FM/MCP
Artigos e Materiais de Revistas Científicas - HC/InCor
Artigos e Materiais de Revistas Científicas - LIM/11
Artigos e Materiais de Revistas Científicas - LIM/64