Norrish, Gabrielle;
Niemiec, Małgorzata;
Kaski, Juan P;
Mizia-Stec, Katarzyna;
(2024)
How to assess sudden cardiac death risk in hypertrophic cardiomyopathy? Current challenges and directions for the future.
Kardiologia Polska
10.33963/v.phj.104052.
(In press).
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Abstract
Over the past decade, knowledge about the risk of sudden cardiac death (SCD) in patients with hypertrophic cardiomyopathy (HCM) has advanced significantly. A standard well-recognised approach to risk stratification is based on the fundamental risk factors and SCD risk models that should be incorporated into the shared decision-making process. More detailed analysis including additional indicators, such as reduced left ventricular systolic function, the presence of late gadolinium enhancement or in some cases genetic variants, may provide valuable insights for intermediate-risk patients, enabling more personalized diagnosis and treatment. Risk stratification remains challenging in specific groups, such as patients who have undergone septal reduction therapy, those taking mavacamten, or those with phenocopies of HCM. The advancement of modern methodologies, including multifactorial approaches supported by artificial intelligence algorithms, offers hope for more precise and individualized SCD risk assessment in individuals with HCM.
| Type: | Article |
|---|---|
| Title: | How to assess sudden cardiac death risk in hypertrophic cardiomyopathy? Current challenges and directions for the future |
| Location: | Poland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.33963/v.phj.104052 |
| Publisher version: | https://doi.org/10.33963/v.phj.104052 |
| Language: | English |
| Additional information: | This article is available in open access under the Creative Common Attribution International (CC BY) license, which allows copying, distributing, and transmitting work, adapting work, and making commercial use of the work under the condition that the user must attribute the work in the manner specified by the author or licensor (but not in any way that suggests they endorse the user or their use of the work). |
| Keywords: | artificial intelligence, hypertrophic cardiomyopathy, prediction, risk, sudden cardiac death |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10203160 |
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