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Antonopoulos M, Bonios MJ, Dimopoulos S, Leontiadis E, Gouziouta A, Kogerakis N, Koliopoulou A, Elaiopoulos D, Vlahodimitris I, Chronaki M, Chamogeorgakis T, Drakos SG, Adamopoulos S. Advanced Heart Failure: Therapeutic Options and Challenges in the Evolving Field of Left Ventricular Assist Devices. J Cardiovasc Dev Dis 2024; 11:61. [PMID: 38392275 PMCID: PMC10888700 DOI: 10.3390/jcdd11020061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 02/06/2024] [Accepted: 02/09/2024] [Indexed: 02/24/2024] Open
Abstract
Heart Failure is a chronic and progressively deteriorating syndrome that has reached epidemic proportions worldwide. Improved outcomes have been achieved with novel drugs and devices. However, the number of patients refractory to conventional medical therapy is growing. These advanced heart failure patients suffer from severe symptoms and frequent hospitalizations and have a dismal prognosis, with a significant socioeconomic burden in health care systems. Patients in this group may be eligible for advanced heart failure therapies, including heart transplantation and chronic mechanical circulatory support with left ventricular assist devices (LVADs). Heart transplantation remains the treatment of choice for eligible candidates, but the number of transplants worldwide has reached a plateau and is limited by the shortage of donor organs and prolonged wait times. Therefore, LVADs have emerged as an effective and durable form of therapy, and they are currently being used as a bridge to heart transplant, destination lifetime therapy, and cardiac recovery in selected patients. Although this field is evolving rapidly, LVADs are not free of complications, making appropriate patient selection and management by experienced centers imperative for successful therapy. Here, we review current LVAD technology, indications for durable MCS therapy, and strategies for timely referral to advanced heart failure centers before irreversible end-organ abnormalities.
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Affiliation(s)
- Michael Antonopoulos
- Heart Failure, Transplant and Mechanical Circulatory Support Units, Onassis Cardiac Surgery Center, 17674 Athens, Greece
- Cardiac Surgery Intensive Care Unit, Onassis Cardiac Surgery Center, 17674 Athens, Greece
| | - Michael J Bonios
- Heart Failure, Transplant and Mechanical Circulatory Support Units, Onassis Cardiac Surgery Center, 17674 Athens, Greece
- Division of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Stavros Dimopoulos
- Cardiac Surgery Intensive Care Unit, Onassis Cardiac Surgery Center, 17674 Athens, Greece
| | - Evangelos Leontiadis
- Heart Failure, Transplant and Mechanical Circulatory Support Units, Onassis Cardiac Surgery Center, 17674 Athens, Greece
| | - Aggeliki Gouziouta
- Heart Failure, Transplant and Mechanical Circulatory Support Units, Onassis Cardiac Surgery Center, 17674 Athens, Greece
| | - Nektarios Kogerakis
- Heart Failure, Transplant and Mechanical Circulatory Support Units, Onassis Cardiac Surgery Center, 17674 Athens, Greece
| | - Antigone Koliopoulou
- Heart Failure, Transplant and Mechanical Circulatory Support Units, Onassis Cardiac Surgery Center, 17674 Athens, Greece
- Division of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Dimitris Elaiopoulos
- Cardiac Surgery Intensive Care Unit, Onassis Cardiac Surgery Center, 17674 Athens, Greece
| | - Ioannis Vlahodimitris
- Heart Failure, Transplant and Mechanical Circulatory Support Units, Onassis Cardiac Surgery Center, 17674 Athens, Greece
| | - Maria Chronaki
- Cardiac Surgery Intensive Care Unit, Onassis Cardiac Surgery Center, 17674 Athens, Greece
| | - Themistocles Chamogeorgakis
- Heart Failure, Transplant and Mechanical Circulatory Support Units, Onassis Cardiac Surgery Center, 17674 Athens, Greece
| | - Stavros G Drakos
- Division of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Stamatis Adamopoulos
- Heart Failure, Transplant and Mechanical Circulatory Support Units, Onassis Cardiac Surgery Center, 17674 Athens, Greece
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Balcioglu O, Ozgocmen C, Ozsahin DU, Yagdi T. The Role of Artificial Intelligence and Machine Learning in the Prediction of Right Heart Failure after Left Ventricular Assist Device Implantation: A Comprehensive Review. Diagnostics (Basel) 2024; 14:380. [PMID: 38396419 PMCID: PMC10888030 DOI: 10.3390/diagnostics14040380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024] Open
Abstract
One of the most challenging and prevalent side effects of LVAD implantation is that of right heart failure (RHF) that may develop afterwards. The purpose of this study is to review and highlight recent advances in the uses of AI in evaluating RHF after LVAD implantation. The available literature was scanned using certain key words (artificial intelligence, machine learning, left ventricular assist device, prediction of right heart failure after LVAD) was scanned within Pubmed, Web of Science, and Google Scholar databases. Conventional risk scoring systems were also summarized, with their pros and cons being included in the results section of this study in order to provide a useful contrast with AI-based models. There are certain interesting and innovative ML approaches towards RHF prediction among the studies reviewed as well as more straightforward approaches that identified certain important predictive clinical parameters. Despite their accomplishments, the resulting AUC scores were far from ideal for these methods to be considered fully sufficient. The reasons for this include the low number of studies, standardized data availability, and lack of prospective studies. Another topic briefly discussed in this study is that relating to the ethical and legal considerations of using AI-based systems in healthcare. In the end, we believe that it would be beneficial for clinicians to not ignore these developments despite the current research indicating more time is needed for AI-based prediction models to achieve a better performance.
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Affiliation(s)
- Ozlem Balcioglu
- Department of Cardiovascular Surgery, Faculty of Medicine, Near East University, TRNC Mersin 10, Nicosia 99138, Turkey;
- Operational Research Center in Healthcare, Near East University, TRNC Mersin 10, Nicosia 99138, Turkey;
| | - Cemre Ozgocmen
- Department of Biomedical Engineering, Faculty of Engineering, Near East University, TRNC Mersin 10, Nicosia 99138, Turkey;
| | - Dilber Uzun Ozsahin
- Operational Research Center in Healthcare, Near East University, TRNC Mersin 10, Nicosia 99138, Turkey;
- Medical Diagnostic Imaging Department, College of Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates
| | - Tahir Yagdi
- Department of Cardiovascular Surgery, Faculty of Medicine, Ege University, Izmir 35100, Turkey
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