Nuno Cardim
Luis Rocha Lopes
Giovanni Quarta- 1Cardiology Department, Hospital CUF Descobertas, Lisbon, Portugal
- 2Nova Medical School, Lisbon, Portugal
- 3Barts Heart Centre, St. Bartholomew’s Hospital, London, United Kingdom
- 4Institute of Cardiovascular Science, University College London, London, United Kingdom
- 5Cardiovascular department, Papa Giovanni XXIII Hospital, Bergamo, Italy
Editorial on the Research Topic
Comprehensive risk prediction in cardiomyopathies: new genetic and imaging markers of risk, volume II
Risk prediction is relevant to many questions in medicine and specifically in cardiology, and the predicted risk is used to support preventive clinical decisions with the goal of saving lives. However, the success of these initiatives obviously depends on the adequate performance of the risk prediction markers and models (1–3).
The different types of cardiomyopathies collectively represent a substantial burden of disease around the world, causing sudden cardiac death, heart failure and thromboembolism (1). Many of these complications and deaths could be prevented if an adequate risk prediction becomes standard practice.
In the era of precision medicine, risk prediction plays a major role. In patiens with similar clinical presentation, identification of specific characteristics that allow precise definition of prognosis and the selection of preventive individualized strategies is critical. This accurate phenotyping implies the use of “diagnosis tools of precision” such as data from genetics (4) and imaging (5, 6), among others. Data provided by these fine-tuning strategies, when combined with modern data analysis techniques (big data analytics), promise an individualized preventive approach, tailored to the specific characteristics of each patient, with impact on their outcomes.
Cardiomyopathies are important areas of cardiology, in which genetics and cardiac imaging can successfully contribute as “diagnosis tools of precision” to predict risk. Despite recent approaches and advances in this area, risk prediction in these diseases is still far from perfect and clearly there is a lot of room for improvement.
In this research topic of Frontiers in Cardiovascular Medicine, the input of cardiomyopathy investigators on new genetics and imaging markers in comprehensive risk prediction in cardiomyopathies is provided. After the success of the first volume, this new volume introduces interesting new insights on the field.
In a review paper, Galli et al. provide a nice overview of the evolution of cardiac imaging for the assessment of left ventricular dyssynchrony and its role in the selection of patients undergoing cardiac resynchronization therapy. They highlight the main pitfalls and advantages of the application of cardiac imaging for dyssynchrony assessment and provide perspectives for clinical application and future research in this field.
In another elegant paper on dilated cardiomyopathy, Amin et al. demonstrate how genetics and cardiac magnetic resonance frequently change the classification of etiology in dilated cardiomyopathy, improve accuracy and interobserver variability in determining the diagnosis and have an impact on proposed management.
Also on the topic of dilated cardiomyopathy, Zhu et al. show that the “summed motion score” assessed by gated SPECT myocardial perfusion imaging is an independent predictor of cardiac death in these patients and provides incremental prognostic value, challenging the predictive value of left ventricular ejection fraction for early cardiac death.
In Anderson-Fabry disease patients, Parisi et al. discuss the important role of the electrocardiogram in this challenging disease, not only as a sensitive tool for diagnosis, but also for the long-term follow-up of these patients.
Finally, a paper from Zaidi et al. assesses the current role of machine learning in the analysis of complex late gadolinium enhancement patterns to improve risk prediction of major arrhythmic events in stable coronary artery disease patients; these findings highlight a potential novel approach to identifying candidates for implantable cardioverter defibrillators.
Author contributions
NC: Writing – original draft. LL: Writing – review & editing. GQ: Writing – review & editing.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
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References
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2. Writing Committee M, Ommen SR, Mital S, Burke MA, Day SM, Deswal A, et al. 2020 AHA/ACC guideline for the diagnosis and treatment of patients with hypertrophic cardiomyopathy: a report of the American college of cardiology/American heart association joint committee on clinical practice guidelines. Circulation. (2020) 142:e533–57. doi: 10.1161/CIR.0000000000000938
3. Aktaa S, Tzeis S, Gale CP, Ackerman MJ, Arbelo E, Behr ER, et al. European society of cardiology quality indicators for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death. Europace. (2023) 25(1):199–210. doi: 10.1093/europace/euac114
4. Joy G, Moon JC, Lopes LR. Detection of subclinical hypertrophic cardiomyopathy. Nat Rev Cardiol. (2023) 20(6):369–70. doi: 10.1038/s41569-023-00853-7
5. Quarta G, Aquaro GD, Pedrotti P, Pontone G, Dellegrottaglie S, Iacovoni A, et al. Cardiovascular magnetic resonance imaging in hypertrophic cardiomyopathy: the importance of clinical context. Eur Heart J Cardiovasc Imaging. (2018) 19(6):601–10. doi: 10.1093/ehjci/jex323
6. Cardim N, Galderisi M, Edvardsen T, Plein S, Popescu BA, D’Andrea A, et al. Role of multimodality cardiac imaging in the management of patients with hypertrophic cardiomyopathy: an expert consensos of the European association of cardiovascular imaging endorsed by the Saudi heart association. Eur Heart J Cardiovasc Imaging. (2015) 16:280. doi: 10.1093/ehjci/jeu291
Citation: Cardim N, Lopes LR and Quarta G (2023) Editorial: Comprehensive risk prediction in cardiomyopathies: new genetic and imaging markers of risk, volume II. Front. Cardiovasc. Med. 10:1282587. doi: 10.3389/fcvm.2023.1282587
Received: 24 August 2023; Accepted: 5 September 2023;
Published: 13 September 2023.
Edited and Reviewed by: Ana Garcia-Alvarez, Hospital Clinic of Barcelona, Spain
© 2023 Cardim, Lopes and Quarta. 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.
*Correspondence: Nuno Cardim cardimnuno@gmail.com