Literature DB >> 34147459

Maximal Wall Thickness Measurement in Hypertrophic Cardiomyopathy: Biomarker Variability and its Impact on Clinical Care.

Gabriella Captur1, Charlotte H Manisty2, Betty Raman3, Alberto Marchi4, Timothy C Wong5, Rina Ariga3, Anish Bhuva2, Elizabeth Ormondroyd6, Ilaria Lobascio7, Claudia Camaioni7, Savvas Loizos7, Jenade Bonsu-Ofori8, Aslan Turer9, Vlad G Zaha9, João B Augutsto2, Rhodri H Davies2, Andrew J Taylor10, Arthur Nasis11, Mouaz H Al-Mallah12, Sinitsyn Valentin13, Diego Perez de Arenaza14, Vimal Patel15, Mark Westwood7, Steffen E Petersen16, Chunming Li17, Lijun Tang18, Shiro Nakamori19, Reza Nezafat19, Raymond Y Kwong20, Carolyn Y Ho20, Alan G Fraser21, Hugh Watkins6, Perry M Elliott2, Stefan Neubauer3, Guy Lloyd2, Iacopo Olivotto4, Petros Nihoyannopoulos22, James C Moon23.   

Abstract

OBJECTIVES: The aim of this study was to define the variability of maximal wall thickness (MWT) measurements across modalities and predict its impact on care in patients with hypertrophic cardiomyopathy (HCM).
BACKGROUND: Left ventricular MWT measured by echocardiography or cardiovascular magnetic resonance (CMR) contributes to the diagnosis of HCM, stratifies risk, and guides key decisions, including whether to place an implantable cardioverter-defibrillator (ICD).
METHODS: A 20-center global network provided paired echocardiographic and CMR data sets from patients with HCM, from which 17 paired data sets of the highest quality were selected. These were presented as 7 randomly ordered pairs (at 6 cardiac conferences) to experienced readers who report HCM imaging in their daily practice, and their MWT caliper measurements were captured. The impact of measurement variability on ICD insertion decisions was estimated in 769 separately recruited multicenter patients with HCM using the European Society of Cardiology algorithm for 5-year risk for sudden cardiac death.
RESULTS: MWT analysis was completed by 70 readers (from 6 continents; 91% with >5 years' experience). Seventy-nine percent and 68% scored echocardiographic and CMR image quality as excellent. For both modalities (echocardiographic and then CMR results), intramodality inter-reader MWT percentage variability was large (range -59% to 117% [SD ±20%] and -61% to 52% [SD ±11%], respectively). Agreement between modalities was low (SE of measurement 4.8 mm; 95% CI 4.3 mm-5.2 mm; r = 0.56 [modest correlation]). In the multicenter HCM cohort, this estimated echocardiographic MWT percentage variability (±20%) applied to the European Society of Cardiology algorithm reclassified risk in 19.5% of patients, which would have led to inappropriate ICD decision making in 1 in 7 patients with HCM (8.7% would have had ICD placement recommended despite potential low risk, and 6.8% would not have had ICD placement recommended despite intermediate or high risk).
CONCLUSIONS: Using the best available images and experienced readers, MWT as a biomarker in HCM has a high degree of inter-reader variability and should be applied with caution as part of decision making for ICD insertion. Better standardization efforts in HCM recommendations by current governing societies are needed to improve clinical decision making in patients with HCM.
Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  cardiovascular magnetic resonance; echocardiography; hypertrophic cardiomyopathy; wall thickness

Mesh:

Substances:

Year:  2021        PMID: 34147459     DOI: 10.1016/j.jcmg.2021.03.032

Source DB:  PubMed          Journal:  JACC Cardiovasc Imaging        ISSN: 1876-7591


  2 in total

1.  Global longitudinal strain differentiates physiological hypertrophy from maladaptive remodeling.

Authors:  Yvonne Bewarder; Lucas Lauder; Saarraaken Kulenthiran; Ortwin Schäfer; Christian Ukena; Robert Percy Marshall; Pierre Hepp; Ulrich Laufs; Stephan Stöbe; Andreas Hagendorff; Michael Böhm; Felix Mahfoud; Sebastian Ewen
Journal:  Int J Cardiol Heart Vasc       Date:  2022-05-06

2.  Derivation and Validation of a Screening Model for Hypertrophic Cardiomyopathy Based on Electrocardiogram Features.

Authors:  Lanyan Guo; Chao Gao; Weiping Yang; Zhiling Ma; Mengyao Zhou; Jianzheng Liu; Hong Shao; Bo Wang; Guangyu Hu; Hang Zhao; Ling Zhang; Xiong Guo; Chong Huang; Zhe Cui; Dandan Song; Fangfang Sun; Liwen Liu; Fuyang Zhang; Ling Tao
Journal:  Front Cardiovasc Med       Date:  2022-05-24
  2 in total

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