ArticleFrontiers in cardiovascular medicine2022
Model Embraced Electromechanical Coupling Time for Estimation of Heart Failure in Patients With Hypertrophic Cardiomyopathy.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 4 citations in OpenAlex.
- Preliminary results of a single, easy-to-use device for multimodal detection of intervals associated with heart failure decompensation.European heart journal. Digital health · 2026Article
- Effects of Mavacamten on Cardiac Magnetic Resonance Features in Chinese Patients With Obstructive Hypertrophic Cardiomyopathy.JACC. Asia · 2025Article
- The Establishment of Hypertrophic Cardiomyopathy Diagnosis Model via Artificial Neural Network and Random Decision Forest Method.Mediators of inflammation · 2022Article
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Authors and funding
10 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to establish a model embraced electromechanical coupling time (EMC-T) and assess the value of the model for the prediction of heart failure (HF) in patients with hypertrophic cardiomyopathy (HCM). Materials and Methods: Data on 82 patients with HCM at Shaanxi Provincial People's Hospital between February 2019 and November 2021 were collected and then formed the training dataset ( Results: During a median of 22.91 months, 19 (13.38%) patients experienced HF. Cox analysis showed that EMC-T courses in the lateral wall, myoglobin, PR interval, and left atrial volume index were independent predictors of HF in patients with HCM. Five factors were incorporated into the model and shown as a nomogram. Stratification of patients into two risk subgroups by applying risk score (<230.65, ≥230.65) allowed significant distinction between Kaplan-Meier curves for cumulative incidence of HF events. In training dataset, the model had an AUC of 0.948 (95% CI: 0.885-1.000, Conclusion: We established and validated a novel model incorporating electromechanical coupling time courses for predicting HF in patients with HCM.
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