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New Perspectives and Current Challenges in Myocardial Infarction
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New Perspectives and Current Challenges in Myocardial Infarction

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Clinical Medicine, Cell, and Organism Physiology".

Deadline for manuscript submissions: 31 October 2024 | Viewed by 1190

Special Issue Editors

Dr. Konrad Stępień

E-Mail Website
Guest Editor
1. Department of Coronary Artery Disease and Heart Failure, Jagiellonian University Medical College, Krakow, Poland
2. Department of Thromboembolic Disorders, Jagiellonian University Medical College, Krakow, Poland
Interests: myocardial infarction; myocardial infarction with non-obstructive coronary arteries (MINOCA); coronary artery aneurysm and ectasia; interventional cardiology; coagulation system; lipid-lowering treatment; heart failure
Dr. Wojciech Wańha

E-Mail Website
Guest Editor
Department of Cardiology and Structural Heart Diseases, Medical University of Silesia, Katowice, Poland
Interests: myocardial infarction; in-stent restenosis; intracoronary imaging; drug-eluting balloons; left atrial appendage occlusion

Special Issue Information

Dear Colleagues,

Myocardial infarction (MI) is the most severe clinical presentation of coronary artery disease. In accordance with current data more than 3 million individuals develop ST-segment elevation MI each year worldwide with the global prevalence of MI < 60 years—3.8% and > 60 years—9.5%. Despite the marked reduction in MI-associated mortality, it still remains unacceptably high. The economic impact of MI is also important. In 2010 more than 1.1 million MI hospitalizations were reported in the United States with an estimated direct cost of $450 billion. Therefore, this Special Issue aims to look for new perspectives and current challenges that can modify these unfavorable data.

We invite authors to submit original studies, reviews, and meta analysis focused on the interesting aspects of novelties and challenges in MI. We are soliciting broadly understood personalized or individualized medicine, also using artificial intelligence and genetics, including manuscripts devoted to novel and unconventional drugs, medical devices, or approaches dedicated to MI patients.

Dr. Konrad Stępień
Dr. Wojciech Wańha
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • myocardial infarction 
  • personalized medicine 
  • artificial intelligence
  • genetics 
  • targeted treatment
  • percutaneous coronary intervention

Published Papers (2 papers)

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Research

13 pages, 3361 KiB  
Article
Two-Year Outcomes for Patients with Non-ST-Elevation Acute Coronary Syndrome Treated with Magmaris and Absorb Bioresorbable Scaffolds in Large-Vessel Lesions
by Adrian Włodarczak, Piotr Rola, Szymon Włodarczak, Marek Szudrowicz, Katarzyna Giniewicz, Magdalena Łanocha, Joanna Jaroszewska-Pozorska, Mateusz Barycki, Łukasz Furtan, Michalina Kędzierska, Piotr Włodarczak, Adrian Doroszko and Maciej Lesiak
J. Pers. Med. 2024, 14(5), 540; https://doi.org/10.3390/jpm14050540 - 17 May 2024
Viewed by 398
Abstract
Background: The acute coronary syndrome (ACS) continues to be a fundamental indication for revascularization by percutaneous coronary intervention (PCI). Drug-eluting stent (DES) implantation remains a part of contemporary practice but permanent caging of the vascular structure with the metallic stent structure may increase [...] Read more.
Background: The acute coronary syndrome (ACS) continues to be a fundamental indication for revascularization by percutaneous coronary intervention (PCI). Drug-eluting stent (DES) implantation remains a part of contemporary practice but permanent caging of the vascular structure with the metallic stent structure may increase the rate of device-related adverse clinical events. As an alternative to classic metallic DESs, the bioresorbable scaffolds (BRSs) have emerged as a temporary vascular support technology. We evaluated the mid-term outcomes of two generations of bioresorbable scaffolds—Absorb (Abbott-Vascular, Chicago, IL, USA) and Magmaris (Biotronik, Germany)—in patients with non-ST-elevation ACS. Methods: The study cohort consisted of 193 subjects after Magmaris implantation and 160 patients following Absorb implantation in large-vessel lesions. Results: At 2 years, a significantly lower rate of a primary outcome (cardiac death, myocardial infarction, stent thrombosis) was observed with Magmaris (5.2% vs. 15%; p = 0.002). In addition, we observed a significantly lower rate of MI in the target vessel (2.6% vs. 9.4%; p = 0.009) and a lower rate of scaffold thrombosis (0% vs. 3.7%; p = 0.008). The TLF rate between the two groups was not significantly different. Conclusion: Magmaris demonstrated a good safety profile and more favorable clinical outcomes when compared to Absorb in patients with non-ST-elevation ACS. Full article
(This article belongs to the Special Issue New Perspectives and Current Challenges in Myocardial Infarction)
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14 pages, 1410 KiB  
Article
Machine Learning Modeling to Predict Atrial Fibrillation Detection in Embolic Stroke of Undetermined Source Patients
by Chua Ming, Geraldine J. W. Lee, Yao Hao Teo, Yao Neng Teo, Emma M. S. Toh, Tony Y. W. Li, Chloe Yitian Guo, Jiayan Ding, Xinyan Zhou, Hock Luen Teoh, Swee-Chong Seow, Leonard L. L. Yeo, Ching-Hui Sia, Gregory Y. H. Lip, Mehul Motani and Benjamin YQ Tan
J. Pers. Med. 2024, 14(5), 534; https://doi.org/10.3390/jpm14050534 - 16 May 2024
Viewed by 498
Abstract
Background: In patients with embolic stroke of undetermined source (ESUS), occult atrial fibrillation (AF) has been implicated as a key source of cardioembolism. However, only a minority acquire implantable cardiac loop recorders (ILRs) to detect occult paroxysmal AF, partly due to financial cost [...] Read more.
Background: In patients with embolic stroke of undetermined source (ESUS), occult atrial fibrillation (AF) has been implicated as a key source of cardioembolism. However, only a minority acquire implantable cardiac loop recorders (ILRs) to detect occult paroxysmal AF, partly due to financial cost and procedural inconvenience. Without the initiation of appropriate anticoagulation, these patients are at risk of increased ischemic stroke recurrence. Hence, cost-effective and accurate methods of predicting AF in ESUS patients are highly sought after. Objective: We aimed to incorporate clinical and echocardiography data into machine learning (ML) algorithms for AF prediction on ILRs in ESUS. Methods: This was a single-center cohort study that included 157 consecutive patients diagnosed with ESUS from October 2014 to October 2017 who had ILR evaluation. We developed four ML models, with hyperparameters tuned, to predict AF detection on an ILR. Results: The median age of the cohort was 67 (IQR 59–74) years old and the median monitoring duration was 1051 (IQR 478–1287) days. Of the 157 patients, 32 (20.4%) had occult AF detected on the ILR. Support vector machine predicted for AF with a 95% confidence interval area under the receiver operating characteristic curve (AUC) of 0.736–0.737, multilayer perceptron with an AUC of 0.697–0.708, XGBoost with an AUC of 0.697–0.697, and random forest with an AUC of 0.663–0.674. ML feature importance found that age, HDL-C, and admitting heart rate were important non-echocardiography variables, while peak mitral A-wave velocity and left atrial volume were important echocardiography parameters aiding this prediction. Conclusion: Machine learning modeling incorporating clinical and echocardiographic variables predicted AF in ESUS patients with moderate accuracy. Full article
(This article belongs to the Special Issue New Perspectives and Current Challenges in Myocardial Infarction)
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