ObjectiveThe continuous uninterrupted feedback system is the essential part of any well-organized system. We propose aLYNX concept that is a possibility to use an artificial intelligence algorithm or a neural network model in decision-making system so as to avoid possible mistakes and to remind the doctors to review tactics once more in selected cases.MethodaLYNX system includes: registry with significant factors, decisions and results; machine learning process based on this registry data; the use of the machine learning results as the adviser. We show a possibility to build a computer adviser with a neural network model for making a choice between coronary aortic bypass surgery (CABG) and percutaneous coronary intervention (PCI) in order to achieve a higher 5-year survival rate in patients with angina based on the experience of 5107 patients.ResultsThe neural network was trained by 4679 patients who achieved 5-year survival. Among them, 2390 patients underwent PCI and 2289 CABG. After training, the correlation coefficient (r) of the network was 0.74 for training, 0.67 for validation, 0.71 for test and 0.73 for total. Simulation of the neural network function has been performed after training in the two groups of patients with known 5-year outcome. The disagreement rate was significantly higher in the dead patient group than that in the survivor group between neural network model and heart team [16.8% (787/4679) vs. 20.3% (87/428), P = 0.065)].ConclusionThe study shows the possibility to build a computer adviser with a neural network model for making a choice between CABG and PCI in order to achieve a higher 5-year survival rate in patients with angina.
Aim Analyzing a 5-year experience of surgical treatment of cardiosurgical patients with atrial fibrillation (AF).Material and methods The study analyzed results of surgical treatment with extracorporeal circulation in 132 patients with AF who underwent the Maze-IV procedure using a radiofrequency ablator with transmurality feedback from 2013 through 2018.Results Two fatal outcomes were observed in the study group. These outcomes took place in the early postoperative period and were associated with progressive acute heart failure in patients with repeated surgery for mitral valve restenosis. 61.2% of the patients had no AF. Recurrent AF was observed during the first three years after surgery in association with withdrawal of the antiarrhythmic medication, which confirmed a need for long-term antiarrhythmic therapy. Analysis of risk factors for AF relapse identified significant predictors, including left ventricular dilatation larger than 5.5 cm at baseline and more than two-year duration of a history of arrhythmias.Conclusion The Maze-IV procedure proved an effective and safe method of surgical treatment in AF patients with acquired heart defects and ischemic heart disease, which allowed maintaining sinus rhythm in 61.2% of patients for 5 years. Preventive amiodarone saturation reduced the risk of AF relapse by 24.2 % (p=0.038) and incidence of postoperative arrhythmic complications by 34.9 % (p=0.008) in cardiosurgical patients.
Introduction. The widespread adoption of Artificial Intelligence (AI) technologies forms the core of the so-called Industrial Revolution 4.0.The aim of this study is to examine qualitative changes occurring over the last two years in the development of AI through an examination of trends in PubMed publications.Materials. All abstracts with keyword “artificial intelligence” were downloaded from PubMed database https://www.ncbi.nlm.nih.gov/pubmed/ in the form of .txt files. In order to produce a generalisation of topics, we classified present applications of AI in medicine. To this end, 78,420 abstracts, 5558 reviews, 304 randomised controlled trials, 247 multicentre studies and 4137 other publication types were extracted. (Figure 1). Next, the typical applications were classified.Results. Interest in the topic of AI in publications indexed in the PubMed library is increasing according to general innovation development principles. Along with English publications, the number of non-English publications continued to increase until 2018, represented especially by Chinese, German and French languages. By 2018, the number of non-English publications had started to decrease in favour of English publications. Implementations of AI are already being adopted in contemporary practice. Thus, AI tools have moved out of the theoretical realm to find mainstream application.Conclusions. Tools for machine learning have become widely available to working scientists over the last two years. Since this includes FDA-approved tools for general clinical practice, the change not only affects to researchers but also clinical practitioners. Medical imaging and analysis applications already approved for the most part demonstrate comparable accuracy with the human specialist. A classification of developed AI applications is presented in the article.
Background Catheter-based closure has emerged as a less invasive alternative to surgery in high-risk patients with paravalvular leak (PVL) and clinically significant regurgitation with feasibility and efficacy demonstrated in multiple studies. Case summary A 72-year-old female with a past history of long-standing rheumatic heart disease underwent mechanical mitral valve replacement in 2008. Ten years later, redo surgery was performed due to a worsening mitral PVL and the leakage was closed by direct pledget-supported sutures, preserving the mechanical valve. She was recently admitted again for haemolytic anaemia and congestive heart failure (New York Heart Association Classes III–IV) due to a recurrent mitral PVL. We report our initial clinical experience using a novel software solution (EchoNavigator®-system) for intuitive guidance during a catheter-based transapical mitral PVL closure. Discussion Transapical mitral PVL closure with a specifically designed device demonstrated in our case to be a better option than redo surgery. Recently introduced fusion imaging modalities enhanced visualization of soft tissue anatomy and device location improving enormously the results of this challenging intervention.
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