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Listen "AI ECG Boosts Hypertrophic Cardiomyopathy Detection. 10/15/25"
Episode Synopsis
Welcome to Cardiology Today – Recorded October 15, 2025. This episode summarizes 5 key cardiology studies on topics like Systematic COronary Risk Evaluation 2 and bradyarrhythmias. Key takeaway: AI ECG Boosts Hypertrophic Cardiomyopathy Detection..
Article Links:
Article 1: Left atrial pressure normalisation by graded radiofrequency atrial septostomy in heart failure with preserved ejection fraction: a single-arm pilot study. (Heart (British Cardiac Society))
Article 2: Retinal image-based deep learning for mild cognitive impairment detection in coronary artery disease population. (Heart (British Cardiac Society))
Article 3: Predictive performance of cardiovascular disease risk prediction models in older adults: a validation and updating study. (Heart (British Cardiac Society))
Article 4: Clinical implementation of an AI-enabled ECG for hypertrophic cardiomyopathy detection. (Heart (British Cardiac Society))
Article 5: Pacemaker implantation after cardiac surgery: a contemporary, nationwide perspective. (Heart (British Cardiac Society))
Full episode page: https://podcast.explainheart.com/podcast/ai-ecg-boosts-hypertrophic-cardiomyopathy-detection-10-15-25/
Featured Articles
Article 1: Left atrial pressure normalisation by graded radiofrequency atrial septostomy in heart failure with preserved ejection fraction: a single-arm pilot study.
Journal: Heart (British Cardiac Society)
PubMed Link: https://pubmed.ncbi.nlm.nih.gov/40425275
Summary: This single-arm pilot study explored the use of a personalized approach, combining radiofrequency ablation and balloon dilation (C.U.R.B.), to establish interatrial communication in patients with Heart Failure with Preserved Ejection Fraction. The research was conducted at Fuwai Hospital in patients exhibiting elevated resting mean left atrial pressure of 18 millimeters of mercury or higher. This study aimed to normalize left atrial pressure, offering a potential new therapeutic strategy for Heart Failure with Preserved Ejection Fraction management. It successfully investigated the methodology for this intervention, providing a foundation for future larger studies on its efficacy and safety.
Article 2: Retinal image-based deep learning for mild cognitive impairment detection in coronary artery disease population.
Journal: Heart (British Cardiac Society)
PubMed Link: https://pubmed.ncbi.nlm.nih.gov/40379470
Summary: This study aimed to develop a deep learning model based on retinal fundus images for optimized detection of mild cognitive impairment in individuals with Coronary Artery Disease. The research involved Coronary Artery Disease patients, defined by at least one 50 percent stenosis, from Beijing Anzhen Hospital between 2021 and 2023. This methodology establishes a non-invasive approach to screen for mild cognitive impairment, which is commonly associated with Coronary Artery Disease. The development of such a model could facilitate early intervention and improve prognostic outcomes for this vulnerable patient group.
Article 3: Predictive performance of cardiovascular disease risk prediction models in older adults: a validation and updating study.
Journal: Heart (British Cardiac Society)
PubMed Link: https://pubmed.ncbi.nlm.nih.gov/40368453
Summary: This study aimed to validate, update, and assess the utility of several prominent Cardiovascular Disease risk prediction models in an Australian older adult population. Researchers specifically evaluated models originally developed for middle-aged individuals, such as the American College of Cardiology/American Heart Association and 2008 Framingham models, alongside an age-specific Systematic COronary Risk Evaluation 2-Older Person model. The methodology established a comprehensive framework for assessing these models’ predictive performance in older adults. This research addresses current inadequacies in risk prediction for the elderly, contributing to improved, age-appropriate prevention strategies for Cardiovascular Disease.
Article 4: Clinical implementation of an AI-enabled ECG for hypertrophic cardiomyopathy detection.
Journal: Heart (British Cardiac Society)
PubMed Link: https://pubmed.ncbi.nlm.nih.gov/40240132
Summary: for hypertrophic cardiomyopathy detection. This open-label, multicenter prospective cohort study assessed the clinical implementation of an Artificial Intelligence-enabled 12-lead electrocardiogram software for detecting suspected Hypertrophic Cardiomyopathy. The Viz H.C.M. (Viz.ai) software, which alerts clinicians to potential Hypertrophic Cardiomyopathy cases, was implemented across five healthcare systems from January to December 2023. This research successfully demonstrated the real-world utility of A.I.-E.C.G. tools in assisting with early patient identification and evaluation. The findings offer a pathway to improve diagnosis rates for this often underdiagnosed cardiac condition.
Article 5: Pacemaker implantation after cardiac surgery: a contemporary, nationwide perspective.
Journal: Heart (British Cardiac Society)
PubMed Link: https://pubmed.ncbi.nlm.nih.gov/40157746
Summary: This nationwide population-based study explored the contemporary incidence and indications for permanent pacemaker implantation following various cardiac surgical procedures. Conducted in Sweden, the research primarily investigated implantation rates at 30 days and one year post-surgery, with secondary outcomes including 10-year incidence. The study provides crucial, modern data on bradyarrhythmia complications after cardiac surgery. This information is vital for patient risk stratification, counseling, and optimizing post-operative management strategies.
Transcript
Today’s date is October 15, 2025. Welcome to Cardiology Today. Here are the latest research findings.
Article number one. Left atrial pressure normalisation by graded radiofrequency atrial septostomy in heart failure with preserved ejection fraction: a single-arm pilot study. This single-arm pilot study explored the use of a personalized approach, combining radiofrequency ablation and balloon dilation (C.U.R.B.), to establish interatrial communication in patients with Heart Failure with Preserved Ejection Fraction. The research was conducted at Fuwai Hospital in patients exhibiting elevated resting mean left atrial pressure of 18 millimeters of mercury or higher. This study aimed to normalize left atrial pressure, offering a potential new therapeutic strategy for Heart Failure with Preserved Ejection Fraction management. It successfully investigated the methodology for this intervention, providing a foundation for future larger studies on its efficacy and safety.
Article number two. Retinal image-based deep learning for mild cognitive impairment detection in coronary artery disease population. This study aimed to develop a deep learning model based on retinal fundus images for optimized detection of mild cognitive impairment in individuals with Coronary Artery Disease. The research involved Coronary Artery Disease patients, defined by at least one 50 percent stenosis, from Beijing Anzhen Hospital between 2021 and 2023. This methodology establishes a non-invasive approach to screen for mild cognitive impairment, which is commonly associated with Coronary Artery Disease. The development of such a model could facilitate early intervention and improve prognostic outcomes for this vulnerable patient group.
Article number three. Predictive performance of cardiovascular disease risk prediction models in older adults: a validation and updating study. This study aimed to validate, update, and assess the utility of several prominent Cardiovascular Disease risk prediction models in an Australian older adult population. Researchers specifically evaluated models originally developed for middle-aged individuals, such as the American College of Cardiology/American Heart Association and 2008 Framingham models, alongside an age-specific Systematic COronary Risk Evaluation 2-Older Person model. The methodology established a comprehensive framework for assessing these models’ predictive performance in older adults. This research addresses current inadequacies in risk prediction for the elderly, contributing to improved, age-appropriate prevention strategies for Cardiovascular Disease.
Article number four. Clinical implementation of an A.I.-enabled E.C.G. for hypertrophic cardiomyopathy detection. This open-label, multicenter prospective cohort study assessed the clinical implementation of an Artificial Intelligence-enabled 12-lead electrocardiogram software for detecting suspected Hypertrophic Cardiomyopathy. The Viz H.C.M. (Viz.ai) software, which alerts clinicians to potential Hypertrophic Cardiomyopathy cases, was implemented across five healthcare systems from January to December 2023. This research successfully demonstrated the real-world utility of A.I.-E.C.G. tools in assisting with early patient identification and evaluation. The findings offer a pathway to improve diagnosis rates for this often underdiagnosed cardiac condition.
Article number five. Pacemaker implantation after cardiac surgery: a contemporary, nationwide perspective. This nationwide population-based study explored the contemporary incidence and indications for permanent pacemaker implantation following various cardiac surgical procedures. Conducted in Sweden, the research primarily investigated implantation rates at 30 days and one year post-surgery, with secondary outcomes including 10-year incidence. The study provides crucial, modern data on bradyarrhythmia complications after cardiac surgery. This information is vital for patient risk stratification, counseling, and optimizing post-operative management strategies.
Thank you for listening. Don’t forget to subscribe.
Keywords
Systematic COronary Risk Evaluation 2, bradyarrhythmias, Hypertrophic Cardiomyopathy, deep learning, older adults, Pacemaker implantation, model validation, radiofrequency ablation, E.C.G. interpretation, retinal imaging, post-operative complications, clinical implementation, cardiac surgery, mild cognitive impairment, Cardiovascular Disease, left atrial pressure, risk prediction models, balloon dilation, nationwide study, Heart Failure with Preserved Ejection Fraction, atrial septostomy, Artificial Intelligence, Coronary Artery Disease, electrocardiogram, fundus images.
About
Concise summaries of cardiovascular research for professionals.
Subscribe • Share • FollowThe post AI ECG Boosts Hypertrophic Cardiomyopathy Detection. 10/15/25 first appeared on Cardiology Today.
Article Links:
Article 1: Left atrial pressure normalisation by graded radiofrequency atrial septostomy in heart failure with preserved ejection fraction: a single-arm pilot study. (Heart (British Cardiac Society))
Article 2: Retinal image-based deep learning for mild cognitive impairment detection in coronary artery disease population. (Heart (British Cardiac Society))
Article 3: Predictive performance of cardiovascular disease risk prediction models in older adults: a validation and updating study. (Heart (British Cardiac Society))
Article 4: Clinical implementation of an AI-enabled ECG for hypertrophic cardiomyopathy detection. (Heart (British Cardiac Society))
Article 5: Pacemaker implantation after cardiac surgery: a contemporary, nationwide perspective. (Heart (British Cardiac Society))
Full episode page: https://podcast.explainheart.com/podcast/ai-ecg-boosts-hypertrophic-cardiomyopathy-detection-10-15-25/
Featured Articles
Article 1: Left atrial pressure normalisation by graded radiofrequency atrial septostomy in heart failure with preserved ejection fraction: a single-arm pilot study.
Journal: Heart (British Cardiac Society)
PubMed Link: https://pubmed.ncbi.nlm.nih.gov/40425275
Summary: This single-arm pilot study explored the use of a personalized approach, combining radiofrequency ablation and balloon dilation (C.U.R.B.), to establish interatrial communication in patients with Heart Failure with Preserved Ejection Fraction. The research was conducted at Fuwai Hospital in patients exhibiting elevated resting mean left atrial pressure of 18 millimeters of mercury or higher. This study aimed to normalize left atrial pressure, offering a potential new therapeutic strategy for Heart Failure with Preserved Ejection Fraction management. It successfully investigated the methodology for this intervention, providing a foundation for future larger studies on its efficacy and safety.
Article 2: Retinal image-based deep learning for mild cognitive impairment detection in coronary artery disease population.
Journal: Heart (British Cardiac Society)
PubMed Link: https://pubmed.ncbi.nlm.nih.gov/40379470
Summary: This study aimed to develop a deep learning model based on retinal fundus images for optimized detection of mild cognitive impairment in individuals with Coronary Artery Disease. The research involved Coronary Artery Disease patients, defined by at least one 50 percent stenosis, from Beijing Anzhen Hospital between 2021 and 2023. This methodology establishes a non-invasive approach to screen for mild cognitive impairment, which is commonly associated with Coronary Artery Disease. The development of such a model could facilitate early intervention and improve prognostic outcomes for this vulnerable patient group.
Article 3: Predictive performance of cardiovascular disease risk prediction models in older adults: a validation and updating study.
Journal: Heart (British Cardiac Society)
PubMed Link: https://pubmed.ncbi.nlm.nih.gov/40368453
Summary: This study aimed to validate, update, and assess the utility of several prominent Cardiovascular Disease risk prediction models in an Australian older adult population. Researchers specifically evaluated models originally developed for middle-aged individuals, such as the American College of Cardiology/American Heart Association and 2008 Framingham models, alongside an age-specific Systematic COronary Risk Evaluation 2-Older Person model. The methodology established a comprehensive framework for assessing these models’ predictive performance in older adults. This research addresses current inadequacies in risk prediction for the elderly, contributing to improved, age-appropriate prevention strategies for Cardiovascular Disease.
Article 4: Clinical implementation of an AI-enabled ECG for hypertrophic cardiomyopathy detection.
Journal: Heart (British Cardiac Society)
PubMed Link: https://pubmed.ncbi.nlm.nih.gov/40240132
Summary: for hypertrophic cardiomyopathy detection. This open-label, multicenter prospective cohort study assessed the clinical implementation of an Artificial Intelligence-enabled 12-lead electrocardiogram software for detecting suspected Hypertrophic Cardiomyopathy. The Viz H.C.M. (Viz.ai) software, which alerts clinicians to potential Hypertrophic Cardiomyopathy cases, was implemented across five healthcare systems from January to December 2023. This research successfully demonstrated the real-world utility of A.I.-E.C.G. tools in assisting with early patient identification and evaluation. The findings offer a pathway to improve diagnosis rates for this often underdiagnosed cardiac condition.
Article 5: Pacemaker implantation after cardiac surgery: a contemporary, nationwide perspective.
Journal: Heart (British Cardiac Society)
PubMed Link: https://pubmed.ncbi.nlm.nih.gov/40157746
Summary: This nationwide population-based study explored the contemporary incidence and indications for permanent pacemaker implantation following various cardiac surgical procedures. Conducted in Sweden, the research primarily investigated implantation rates at 30 days and one year post-surgery, with secondary outcomes including 10-year incidence. The study provides crucial, modern data on bradyarrhythmia complications after cardiac surgery. This information is vital for patient risk stratification, counseling, and optimizing post-operative management strategies.
Transcript
Today’s date is October 15, 2025. Welcome to Cardiology Today. Here are the latest research findings.
Article number one. Left atrial pressure normalisation by graded radiofrequency atrial septostomy in heart failure with preserved ejection fraction: a single-arm pilot study. This single-arm pilot study explored the use of a personalized approach, combining radiofrequency ablation and balloon dilation (C.U.R.B.), to establish interatrial communication in patients with Heart Failure with Preserved Ejection Fraction. The research was conducted at Fuwai Hospital in patients exhibiting elevated resting mean left atrial pressure of 18 millimeters of mercury or higher. This study aimed to normalize left atrial pressure, offering a potential new therapeutic strategy for Heart Failure with Preserved Ejection Fraction management. It successfully investigated the methodology for this intervention, providing a foundation for future larger studies on its efficacy and safety.
Article number two. Retinal image-based deep learning for mild cognitive impairment detection in coronary artery disease population. This study aimed to develop a deep learning model based on retinal fundus images for optimized detection of mild cognitive impairment in individuals with Coronary Artery Disease. The research involved Coronary Artery Disease patients, defined by at least one 50 percent stenosis, from Beijing Anzhen Hospital between 2021 and 2023. This methodology establishes a non-invasive approach to screen for mild cognitive impairment, which is commonly associated with Coronary Artery Disease. The development of such a model could facilitate early intervention and improve prognostic outcomes for this vulnerable patient group.
Article number three. Predictive performance of cardiovascular disease risk prediction models in older adults: a validation and updating study. This study aimed to validate, update, and assess the utility of several prominent Cardiovascular Disease risk prediction models in an Australian older adult population. Researchers specifically evaluated models originally developed for middle-aged individuals, such as the American College of Cardiology/American Heart Association and 2008 Framingham models, alongside an age-specific Systematic COronary Risk Evaluation 2-Older Person model. The methodology established a comprehensive framework for assessing these models’ predictive performance in older adults. This research addresses current inadequacies in risk prediction for the elderly, contributing to improved, age-appropriate prevention strategies for Cardiovascular Disease.
Article number four. Clinical implementation of an A.I.-enabled E.C.G. for hypertrophic cardiomyopathy detection. This open-label, multicenter prospective cohort study assessed the clinical implementation of an Artificial Intelligence-enabled 12-lead electrocardiogram software for detecting suspected Hypertrophic Cardiomyopathy. The Viz H.C.M. (Viz.ai) software, which alerts clinicians to potential Hypertrophic Cardiomyopathy cases, was implemented across five healthcare systems from January to December 2023. This research successfully demonstrated the real-world utility of A.I.-E.C.G. tools in assisting with early patient identification and evaluation. The findings offer a pathway to improve diagnosis rates for this often underdiagnosed cardiac condition.
Article number five. Pacemaker implantation after cardiac surgery: a contemporary, nationwide perspective. This nationwide population-based study explored the contemporary incidence and indications for permanent pacemaker implantation following various cardiac surgical procedures. Conducted in Sweden, the research primarily investigated implantation rates at 30 days and one year post-surgery, with secondary outcomes including 10-year incidence. The study provides crucial, modern data on bradyarrhythmia complications after cardiac surgery. This information is vital for patient risk stratification, counseling, and optimizing post-operative management strategies.
Thank you for listening. Don’t forget to subscribe.
Keywords
Systematic COronary Risk Evaluation 2, bradyarrhythmias, Hypertrophic Cardiomyopathy, deep learning, older adults, Pacemaker implantation, model validation, radiofrequency ablation, E.C.G. interpretation, retinal imaging, post-operative complications, clinical implementation, cardiac surgery, mild cognitive impairment, Cardiovascular Disease, left atrial pressure, risk prediction models, balloon dilation, nationwide study, Heart Failure with Preserved Ejection Fraction, atrial septostomy, Artificial Intelligence, Coronary Artery Disease, electrocardiogram, fundus images.
About
Concise summaries of cardiovascular research for professionals.
Subscribe • Share • FollowThe post AI ECG Boosts Hypertrophic Cardiomyopathy Detection. 10/15/25 first appeared on Cardiology Today.
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