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Biomedicines
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Saving Lives from Myocardial Infarction: Prevention vs. Therapy
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Saving Lives from Myocardial Infarction: Prevention vs. Therapy

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Molecular and Translational Medicine".

Deadline for manuscript submissions: 31 March 2026 | Viewed by 9199

Special Issue Editor

Dr. Dong Wang

E-Mail Website
Guest Editor
Department of Internal Medicine, University of Arizona College of Medicine-Phoenix, Phoenix, AZ 85004, USA
Interests: cardiovascular disease; myocardial infarction; cell death; fibroblast; heart failure; ischemic stroke; atrial thrombosis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Myocardial infarction (MI), commonly known as a heart attack, remains one of the leading causes of morbidity and mortality worldwide. Despite significant advancements in diagnosing and treating MI, such as with percutaneous coronary intervention (PCI), myocardial cells are terminally differentiated, making regeneration an ongoing challenge even with advancements in stem cell therapies. This makes it crucial for us to reconsider our strategies to save the lives of those affected by MI.

In recent years, artificial intelligence (AI) has emerged as a transformative tool in the cardiovascular field, offering the potential to significantly enhance our understanding, diagnosis, and management of myocardial infarction. By integrating AI and machine learning approaches, we can move towards more personalized and proactive healthcare—identifying patients at risk, enabling early intervention, and providing precision in treatment planning.

This Special Issue aims to explore the latest discoveries, advancements, and breakthroughs in the prevention, diagnosis, and treatment of MI, with a strong focus on the potential of artificial intelligence to revolutionize care. We seek contributions on a wide range of topics, including, but not limited to, the following:

  1. Identification and Characterization of Molecular Markers
    Novel molecular markers for early prediction, diagnosis, and risk stratification of myocardial infarction.
  2. AI-Powered Early Detection and Wearable Devices
    The development of AI-aided wearable devices for predicting and providing early warnings of myocardial infarction, with the goal of minimizing the time between symptom onset and treatment.
  3. Harnessing Artificial Intelligence for MI Care
    Applications of AI and machine learning models in cardiovascular health, including early risk prediction, real-time diagnostics, patient monitoring via wearables, and optimizing treatment strategies for MI patients.
  4. Molecular Mechanisms in Myocardial Injury
    Exploring molecular pathways involved in myocardial ischemia–reperfusion injury and myocardial remodeling.
  5. Inflammation and Immune Regulation in Myocardial Infarction
    Understanding how inflammation and the immune response contribute to myocardial damage and subsequent repair mechanisms.
  6. Therapeutic Approaches to Ventricular Remodeling
    Innovative therapeutic strategies to target ventricular remodeling and control fibrosis following myocardial infarction.
  7. Omics Integration for Deeper Insights
    The integration of omics approaches—such as genomics, transcriptomics, proteomics, and metabolomics—to unravel the complex molecular networks associated with myocardial infarction.

We invite researchers and scientists from diverse disciplines to contribute their original research, reviews, and perspectives to this Special Issue. By collectively sharing and discussing these latest insights, we aim to deepen our understanding of myocardial infarction and pave the way for innovative strategies in prevention, early detection, and treatment—especially by leveraging the power of artificial intelligence.

Dr. Dong Wang
Guest Editor

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. Biomedicines 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
  • molecular markers
  • AI-powered early detection
  • wearable devices
  • ischemia–reperfusion injury
  • artificial intelligence
  • ventricular remodeling
  • fibrosis control
  • molecular imaging
  • genomics
  • transcriptomics
  • proteomics
  • metabolomics
  • MI prevention

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Related Special Issue

Published Papers (3 papers)

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Research

19 pages, 822 KB  
Article
Impact of Sacubitril/Valsartan (ARNI) Compared with ACEI/ARB in Patients with Acute Myocardial Infarction on Post-Infarction Left Ventricular Systolic Dysfunction: A Retrospective Analysis
by Rafał Niemiec, Małgorzata Niemiec, Martyna Nowak, Barbara Gurba, Monika Bujak, Katarzyna Chowaniec-Rybka, Magdalena Sowier, Agnieszka Nowotarska, Bartosz Gruchlik, Adam Pytlewski and Katarzyna Mizia-Stec
Biomedicines 2025, 13(9), 2265; https://doi.org/10.3390/biomedicines13092265 - 15 Sep 2025
Viewed by 731
Abstract
Background/Objectives: Angiotensin receptor–neprilysin inhibitor (ARNI) has a well-established advantage over angiotensin-converting enzyme inhibitor or angiotensin receptor blocker (ACEI/ARB) therapy in patients (pts) with heart failure with reduced ejection fraction (HFrEF), but in pts after acute myocardial infarction (AMI) with left ventricular (LV) [...] Read more.
Background/Objectives: Angiotensin receptor–neprilysin inhibitor (ARNI) has a well-established advantage over angiotensin-converting enzyme inhibitor or angiotensin receptor blocker (ACEI/ARB) therapy in patients (pts) with heart failure with reduced ejection fraction (HFrEF), but in pts after acute myocardial infarction (AMI) with left ventricular (LV) systolic dysfunction, the advantage of ARNI has not been clearly proven. The efficacy of ARNI is compared with that of ACEI/ARB therapy in patients with their first AMI in terms of improvement of post-infarction LV systolic function. Methods: The study was conducted as a retrospective one-center cross-sectional analysis. Overall, 1473 pts (990 M, median age 71 [64; 77]) with AMI (their first AMI, complete coronary revascularization, no prior coronary revascularization or history of HF) hospitalized in 2022–2024 were enrolled in a retrospective cross-sectional analysis. The study population was categorized into pts receiving ARNI and ACEI/ARB. Then, based on the ARNI subgroup, matching that included age, sex, and LV ejection fraction (LVEF) was performed by using the 1:1 nearest neighbor method without returning. Finally, two groups (ARNI vs. ACEI/ARB) of 30 pts were obtained and analyzed at baseline and at a 6-week follow-up. The improvement of post-infarction LV systolic function was obtained in terms of LVEF, ΔLVEF, and relative ΔLVEF values (ΔLVEF/baseline LVEF). Results: The comparison of baseline characteristics revealed borderline lower initial LVEF (30 vs. 36%, p = 0.076) and a higher frequency of SGLT-2 inhibitor use (70% vs. 36.7%, p = 0.01) in the ARNI subgroup. At the 6-week follow-up, in both subgroups, a significant improvement in the median LVEF values was achieved—from a median LVEF value of 30% (27.3; 38) to 37% (30; 43; p = 0.0008) in the ARNI subgroup and from a median LVEF value of 36% (33; 39) to 45% (42; 52; p < 0.0001) in the ACEI/ARB subgroup. The median ΔLVEF in the ACEI/ARB subgroup was higher [10% (6; 12)] than in the ARNI subgroup [6% (2; 10.25), p = 0.018]. Similarly, the median relative ΔLVEF was higher in the ACEI/ARB subgroup [30% (15.4; 40)] than in the ARNI group [17.5% (7; 31.9), p = 0.047]. The vast majority of patients, particularly in the ARNI group (99.7%), were treated with the lowest available dose of the drug. Conclusions: Our current experience in ARNI therapy after AMI is promising; however, it is limited to a small group of patients with severe impairment of LV systolic function. Regardless of the significant improvement in the baseline LVEF observed in patients receiving both ACEI/ARB and ARNI at the 6-week follow-up, the absolute and relative increases in the LVEF were higher in subjects treated with ACEI/ARB. However, the clinical benefits of ARNI therapy may emerge more gradually, and its advantages could become more apparent over a longer follow-up period. The clinical efficacy of early use of ARNI in the setting of AMI needs further evaluation. Full article
(This article belongs to the Special Issue Saving Lives from Myocardial Infarction: Prevention vs. Therapy)
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12 pages, 701 KB  
Article
P2Y12 Inhibitor Pretreatment in Non-ST-Segment Elevation Acute Coronary Syndromes Undergoing a Late Invasive Strategy—A Portuguese Multicenter Nationwide Registry Analysis
by Adriana Vazão, Carolina Miguel Gonçalves, André Martins, Mariana Ferreira Carvalho, Margarida Cabral, Luís Graça Santos, Sidarth Pernencar, João Filipe Carvalho, João Morais and on behalf of the Portuguese Registry on Acute Coronary Syndromes (ProACS) Investigators
Biomedicines 2025, 13(9), 2212; https://doi.org/10.3390/biomedicines13092212 - 9 Sep 2025
Viewed by 509
Abstract
Background/Objectives: Current guidelines do not specifically address the use of P2Y12 inhibitor (P2Y12i) pretreatment in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) who are expected to undergo a late invasive strategy. Nevertheless, such pretreatment may be considered in patients without a high [...] Read more.
Background/Objectives: Current guidelines do not specifically address the use of P2Y12 inhibitor (P2Y12i) pretreatment in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) who are expected to undergo a late invasive strategy. Nevertheless, such pretreatment may be considered in patients without a high bleeding risk (Class of Recommendation, IIb; Level of Evidence, C). Despite this ambiguity, P2Y12i pretreatment remains a common clinical practice. The present study aimed to evaluate the in-hospital prognostic impact of P2Y12i treatment prior to coronary angiography (CAG) in NSTE-ACS patients undergoing a late invasive strategy (CAG > 24 h after hospital admission). Methods: A retrospective analysis was conducted on NSTE-ACS patients undergoing a late invasive strategy included in the Portuguese Registry on Acute Coronary Syndromes between 2010 and 2023. The primary endpoint was a composite of in-hospital events, including all-cause mortality, non-fatal re-infarction, non-fatal stroke, and heart failure (HF). Secondary endpoints included the individual components of the primary endpoint and major bleeding (BARC types 3 and 4). Results: A total of 3776 patients were included (mean age, 66 ± 12 yrs; 29% female), of whom 1530 (41%) received P2Y12i pretreatment (group 1). Group 1 had a lower prevalence of prior myocardial infarction (16% vs. 21%) and prior percutaneous coronary intervention (12% vs. 15%) (both p ≤ 0.001). Although obstructive coronary artery disease was more frequent in group 1 (84% vs. 77%, p < 0.001), the presence of multivessel disease did not differ (52% vs. 52%, p = 0.667). Considering in-hospital antithrombotic therapy, group 1 had higher prescriptions of clopidogrel (68% vs. 56%), aspirin (99% vs. 81%), unfractionated heparin (21% vs. 8%), and enoxaparin (80% vs. 56%) (all p < 0.001). There was no significant difference in the primary composite endpoint between groups (9% vs. 9%, p = 0.906). Similarly, the secondary endpoints of all-cause mortality (0.6% vs. 0.7%), re-infarction (1.3% vs. 0.7%), stroke (0.7% vs. 0.4%), and HF (7% vs. 8%) did not differ significantly between groups (all p > 0.05). Nevertheless, group 1 exhibited higher rates of major bleeding (0.8 vs. 0.2%, OR 3.48, CI 95% 1.22–9.89, p = 0.013). Conclusions: Pretreatment with a P2Y12i in NSTE-ACS patients undergoing a late invasive strategy was not associated with reduction in the primary endpoint, although it was associated with higher rates of major bleeding. Full article
(This article belongs to the Special Issue Saving Lives from Myocardial Infarction: Prevention vs. Therapy)
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12 pages, 934 KB  
Article
Machine Learning-Based Prediction of Short-Term Mortality After Coronary Artery Bypass Grafting: A Retrospective Cohort Study
by Islam Salikhanov, Volker Roth, Brigitta Gahl, Gregory Reid, Rosa Kolb, Daniel Dimanski, Bettina Kowol, Brian M. Mawad, Oliver Reuthebuch and Denis Berdajs
Biomedicines 2025, 13(8), 2023; https://doi.org/10.3390/biomedicines13082023 - 19 Aug 2025
Viewed by 609
Abstract
Objectives: This study aimed to develop and validate a machine learning (ML) algorithm to predict 30-day mortality following isolated coronary artery bypass grafting (CABG) and to compare its performance against the widely used European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) [...] Read more.
Objectives: This study aimed to develop and validate a machine learning (ML) algorithm to predict 30-day mortality following isolated coronary artery bypass grafting (CABG) and to compare its performance against the widely used European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) risk prediction model. Methods: In this retrospective study, we included consecutive adult patients who underwent isolated CABG between January 2009 and December 2022. Three predictive models were compared: (1) EuroSCORE II variables alone (baseline), (2) EuroSCORE II combined with additional preoperative variables (Model I), and (3) EuroSCORE II plus preoperative and postoperative variables available within five days after surgery (Model II). Logistic Regression (LR), Random Forest (RF), and Neural Network (NN) were employed and validated. Predictive accuracy was assessed using the area under the receiver operating characteristic curve (AUC) and specificity at 85% sensitivity. Results: Among the 3483 patients included, the mean age was 66.2 years (SD 10.3), with an overall 30-day mortality rate of 2.5%. The mean EuroSCORE II was 3.12 (SD 4.8). Integrating additional preoperative variables significantly improved specificity at 85% sensitivity for both random forest (from 42% to 51%; p < 0.001) and NN (from 28% to 43%; p < 0.001) but not for LR. Incorporating preoperative along with postoperative data (Model II) further improved specificity to approximately 70% across all ML methods (p < 0.001). The most influential postoperative predictors included kidney failure, pulmonary complications, and myocardial infarction. Conclusions: ML models incorporating preoperative and postoperative variables significantly outperform the traditional EuroSCORE II in predicting short-term mortality following isolated CABG. Full article
(This article belongs to the Special Issue Saving Lives from Myocardial Infarction: Prevention vs. Therapy)
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