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Model Embraced Electromechanical Coupling Time for Estimation of Heart Failure in Patients With Hypertrophic Cardiomyopathy
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 P...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9254680/ https://www.ncbi.nlm.nih.gov/pubmed/35800170 http://dx.doi.org/10.3389/fcvm.2022.895035 |
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author | Hu, Su Mi, Lan Fu, Jianli Ma, Wangxia Ni, Jingsong Zhang, Zhenxia Li, Botao Guan, Gongchang Wang, Junkui Zhao, Na |
author_facet | Hu, Su Mi, Lan Fu, Jianli Ma, Wangxia Ni, Jingsong Zhang, Zhenxia Li, Botao Guan, Gongchang Wang, Junkui Zhao, Na |
author_sort | Hu, Su |
collection | PubMed |
description | 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 (n = 82). Data were used to screen predictors of HF using univariate and multivariate analyses. Predictors were implemented to discover the optimal cut-off value, were incorporated into a model, and shown as a nomogram. The cumulative HF curve was calculated using the Kaplan–Meier method. Additionally, patients with HCM at other hospitals collected from March 2019 to March 2021 formed the validation dataset. The model’s performance was confirmed both in training and validation sets. 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, p < 0.001) and achieved a good C-index of 0.918 (95% CI: 0.867–0.969). In validation dataset, the model had an AUC of 0.991 (95% CI: 0.848–1.000, p < 0.001) and achieved a strong C-index of 0.941 (95% CI: 0.923–1.000). Calibration plots showed high agreement between predicted and observed outcomes in both two datasets. CONCLUSION: We established and validated a novel model incorporating electromechanical coupling time courses for predicting HF in patients with HCM. |
format | Online Article Text |
id | pubmed-9254680 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92546802022-07-06 Model Embraced Electromechanical Coupling Time for Estimation of Heart Failure in Patients With Hypertrophic Cardiomyopathy Hu, Su Mi, Lan Fu, Jianli Ma, Wangxia Ni, Jingsong Zhang, Zhenxia Li, Botao Guan, Gongchang Wang, Junkui Zhao, Na Front Cardiovasc Med Cardiovascular Medicine 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 (n = 82). Data were used to screen predictors of HF using univariate and multivariate analyses. Predictors were implemented to discover the optimal cut-off value, were incorporated into a model, and shown as a nomogram. The cumulative HF curve was calculated using the Kaplan–Meier method. Additionally, patients with HCM at other hospitals collected from March 2019 to March 2021 formed the validation dataset. The model’s performance was confirmed both in training and validation sets. 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, p < 0.001) and achieved a good C-index of 0.918 (95% CI: 0.867–0.969). In validation dataset, the model had an AUC of 0.991 (95% CI: 0.848–1.000, p < 0.001) and achieved a strong C-index of 0.941 (95% CI: 0.923–1.000). Calibration plots showed high agreement between predicted and observed outcomes in both two datasets. CONCLUSION: We established and validated a novel model incorporating electromechanical coupling time courses for predicting HF in patients with HCM. Frontiers Media S.A. 2022-06-16 /pmc/articles/PMC9254680/ /pubmed/35800170 http://dx.doi.org/10.3389/fcvm.2022.895035 Text en Copyright © 2022 Hu, Mi, Fu, Ma, Ni, Zhang, Li, Guan, Wang and Zhao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine Hu, Su Mi, Lan Fu, Jianli Ma, Wangxia Ni, Jingsong Zhang, Zhenxia Li, Botao Guan, Gongchang Wang, Junkui Zhao, Na Model Embraced Electromechanical Coupling Time for Estimation of Heart Failure in Patients With Hypertrophic Cardiomyopathy |
title | Model Embraced Electromechanical Coupling Time for Estimation of Heart Failure in Patients With Hypertrophic Cardiomyopathy |
title_full | Model Embraced Electromechanical Coupling Time for Estimation of Heart Failure in Patients With Hypertrophic Cardiomyopathy |
title_fullStr | Model Embraced Electromechanical Coupling Time for Estimation of Heart Failure in Patients With Hypertrophic Cardiomyopathy |
title_full_unstemmed | Model Embraced Electromechanical Coupling Time for Estimation of Heart Failure in Patients With Hypertrophic Cardiomyopathy |
title_short | Model Embraced Electromechanical Coupling Time for Estimation of Heart Failure in Patients With Hypertrophic Cardiomyopathy |
title_sort | model embraced electromechanical coupling time for estimation of heart failure in patients with hypertrophic cardiomyopathy |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9254680/ https://www.ncbi.nlm.nih.gov/pubmed/35800170 http://dx.doi.org/10.3389/fcvm.2022.895035 |
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