Lowering the Recommended Maximal Wall Thickness Threshold Improves Diagnostic Sensitivity in Asians With Hypertrophic Cardiomyopathy

Le, Thu‐Thao; Huang, Benjamin; Pua, Chee Jian; Tornekar, Vineet; Schumacher-Maurer, Annette; Toh, Desiree-Faye; Bryant, Jennifer; Ang, Benjamin; Corden, Ben; Prasad, Sanjay K.; Tang, Hak-Chiaw; Cook, Stuart A.; Chin, Calvin Woon-Loong

doi:10.1016/j.jacasi.2021.07.001

Cited by 5 publications

(3 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, data are conflicting on whether massive LV hypertrophy increases SCD risk and the optimal LV wall thickness threshold, 21 , 22 , 23 , 24 which may also differ according to imaging modality or ethnicity. 25 , 26 Data from large cohorts showed that an inverted U-shaped relationship seems to exist between maximum LV wall thickness and SCD risk. 23 , 24 This finding may account for the lack of association between massive LV hypertrophy and SCD observed in this study, especially considering that Asian patients with HCM have lower LV wall thickness than other ethnicities.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Performance of 2020 AHA/ACC HCM Guidelines and Incremental Value of Myocardial Strain for Predicting SCD

Lee,

Kim,

Lee

et al. 2024

JACC: Asia

View full text Add to dashboard Cite

Section: Discussionmentioning

confidence: 99%

“… 23 , 24 This finding may account for the lack of association between massive LV hypertrophy and SCD observed in this study, especially considering that Asian patients with HCM have lower LV wall thickness than other ethnicities. 26 …”

Section: Discussionmentioning

confidence: 99%

Performance of 2020 AHA/ACC HCM Guidelines and Incremental Value of Myocardial Strain for Predicting SCD

Lee,

Kim,

Lee

et al. 2024

JACC: Asia

View full text Add to dashboard Cite

“…However, these approaches are relatively unpopular and expensive, need expertized interpretation, and have high inter- and intrareader variability and lack defined conclusions of variant results, all of which have hampered the detection rate of HCM ( 13 – 15 ). Furthermore, since Asians have smaller left ventricular volumes than Caucasians, the diagnostic threshold of maximum wall thickness (MWT) for Asians should be reduced accordingly (recommended from 15 mm to 10–12 mm) ( 16 ). This will then further increase the prevalence and underdiagnosed rate of HCM in Asia, as well as the incidence of potential adverse events, including in China.…”

Section: Introductionmentioning

confidence: 99%

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

Guo

Gao

Yang

et al. 2022

Front. Cardiovasc. Med.

View full text Add to dashboard Cite

BackgroundHypertrophic cardiomyopathy (HCM) is a widely distributed, but clinically heterogeneous genetic heart disease, affects approximately 20 million people worldwide. Nowadays, HCM is treatable with the advancement of medical interventions. However, due to occult clinical presentations and a lack of easy, inexpensive, and widely popularized screening approaches in the general population, 80–90% HCM patients are not clinically identifiable, which brings certain safety hazards could have been prevented. The majority HCM patients showed abnormal and diverse electrocardiogram (ECG) presentations, it is unclear which ECG parameters are the most efficient for HCM screening.ObjectiveWe aimed to develop a pragmatic prediction model based on the most common ECG features to screen for HCM.MethodsBetween April 1st and September 30th, 2020, 423 consecutive subjects from the International Cooperation Center for Hypertrophic Cardiomyopathy of Xijing Hospital [172 HCM patients, 251 participants without left ventricular hypertrophy (non-HCM)] were prospectively included in the training cohort. Between January 4th and February 30th, 2021, 163 participants from the same center were included in the temporal internal validation cohort (62 HCM patients, 101 non-HCM participants). External validation was performed using retrospectively collected ECG data from Xijing Hospital (3,232 HCM ECG samples from January 1st, 2000, to March 31st, 2020; 95,184 non-HCM ECG samples from January 1st to December 31st, 2020). The C-statistic was used to measure the discriminative ability of the model.ResultsAmong 30 ECG features examined, all except abnormal Q wave significantly differed between the HCM patients and non-HCM comparators. After several independent feature selection approaches and model evaluation, we included only two ECG features, T wave inversion (TWI) and the amplitude of S wave in lead V1 (SV1), in the HCM prediction model. The model showed a clearly useful discriminative performance (C-statistic > 0.75) in the training [C-statistic 0.857 (0.818–0.896)], and temporal validation cohorts [C-statistic 0.871 (0.812–0.930)]. In the external validation cohort, the C-statistic of the model was 0.833 [0.825–0.841]. A browser-based calculator was generated accordingly.ConclusionThe pragmatic model established using only TWI and SV1 may be helpful for predicting the probability of HCM and shows promise for use in population-based HCM screening.

show abstract

Three-Dimensional Feature Tracking Study of Healthy Chinese Ventricle by Cardiac Magnetic Resonance

Han,

Chen,

Liu

et al. 2024

Cardiovasc Eng Tech

View full text Add to dashboard Cite

Lowering the Recommended Maximal Wall Thickness Threshold Improves Diagnostic Sensitivity in Asians With Hypertrophic Cardiomyopathy

Cited by 5 publications

References 21 publications

Performance of 2020 AHA/ACC HCM Guidelines and Incremental Value of Myocardial Strain for Predicting SCD

Performance of 2020 AHA/ACC HCM Guidelines and Incremental Value of Myocardial Strain for Predicting SCD

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

Three-Dimensional Feature Tracking Study of Healthy Chinese Ventricle by Cardiac Magnetic Resonance

Contact Info

Product

Resources

About