Prediction of electrophysiological myocardial instability in the acute period of acute coronary syndrome with ST-segment elevation as an effectiveness indicator of the sudden cardiac death prevention

Осипова, О. А.; Шеховцова, Л. В.; Shepel, R. N.; Radzishevskaya, Evgenia; Головин, А И

doi:10.17116/profmed20212405181

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…Представлены данные его активного использования для создания алгоритмов прогнозирования внезапной сердечной смерти [2], при остром коронарном синдроме [3,4], смерти пациентов с острой сердечной недостаточностью [5], показателей сердечно-сосудистой визуализации для стратификации риска при ишемической болезни сердца (ИБС) [6], что открыло новое перспективное направление в кардиологии [7].…”

Section: Introductionunclassified

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Elements of artificial intelligence in a predictive personalized model of pharmacotherapy choice in patients with heart failure with mildly reduced ejection fraction of ischemic origin

Osipova,

Kontsevaya,

Demko

et al. 2023

Cardiovasc Ther Prev

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Aim. To create and train a neural network (NN) of a predictive personalized model of pharmacotherapy choice in patients with heart failure with mildly reduced ejection fraction (HFmrEF) of ischemic origin.Material and methods. The study included 170 people with HFmrEF of ischemic origin, who on the background standard pharmacotherapy, received a beta-blocker (BB) or BB+mineralocorticoid receptor antagonist eplerenone (EP): bisoprolol (BIS); BIS+EP; nebivolol (NEB); NEB+EP. Patients underwent echocardiography and were analyzed for serum aldosterone (AL), tumor necrosis factor-α (TNF-α), matrix metalloproteinase 9 (MMP-9). To create the NN model, the following approximate predictive function of parameters was used: age, AL, TNF-α, MMP-9, sphericity index (SI), type of pharmacotherapy. The result of this function is a parameter vector: AL, TNF-α, MMP-9, SI and quality of life (QOL). The designed NN model is implemented in the Matlab software package for solving machine learning and Data Science problems. The NN model is represented as a connected graph and NN function. Dichotomous analysis was used to compare the effect of treatment types in pairs. For intergroup comparison of therapy, the Wilcoxon W test method. The critical significance (p) was considered <0,05.Results. As a result of model inference, the predicted clinical parameters of patients were obtained, depending on the influence of pharmacotherapy type on the levels of AL, TNF-α, MMP-9, and SI. Function approximation of the distribution was constructed. Determination coefficient R2 of approximating functions was ≥0,92. The calculated values for the BIS therapy groups were obtained; BIS+EP — 169,59, 82,30, 15,26 and 52,92; NEB — 186,42, 87,65, 16,10 and 57,22; NEB+EP — 171,17, 71,90, 14,22 and 58,68, respectively. There were following mean values in the vector of initial states (before therapy): AL, MMP-9, TNF-α, and QOL — 205,84, 174,16, 18,32, and 50,71, respectively. The greatest negative changes of AL, MMP-9, TNF-α (p<0,05) was observed in the NEP+EP group.Conclusion. In the course of the study, using artificial intelligence, a predictive model of a personalized approach to pharmacotherapy choice in patients with HFmrEF of ischemic origin was developed and trained. It has been established that NEP+EP therapy has the greatest effect.

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Section: Introductionunclassified

“…Н. Н. Бурденко". Воронеж; 3 АНО "Научный центр Икарион". Белгород; 4 ФГАОУ ВО "Белгородский государственный национальный исследовательский университет".…”

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Elements of artificial intelligence in a predictive personalized model of pharmacotherapy choice in patients with heart failure with mildly reduced ejection fraction of ischemic origin

Osipova,

Kontsevaya,

Demko

et al. 2023

Cardiovasc Ther Prev

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Prediction of postoperative cognitive dysfunction in patients with coronary artery disease after onpump coronary artery bypass grafting

Осипова

Shepel

Shevtsov

et al. 2023

Cardiovasc Ther Prev

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Coronary artery disease is the most common cause of death worldwide. Onpump coronary artery bypass grafting and cardioplegia remains the gold standard for the treatment of multivessel coronary disease. However, this method of surgical treatment has a number of perioperative complications, the most common of which is postoperative cognitive dysfunction (POCD).Aim. To develop a mathematical model for predicting the binary outcome "presence/absence of POCD deterioration" using MiniMental State Examination (MMSE) and Frontal Assessment Battery (FAB) for timely prevention of cognitive impairment in the early postoperative period.Material and methods. The study included 180 patients with coronary artery disease with stable angina who underwent onpump coronary artery bypass grafting. The patients’ age [Me (Q25-Q75)] was 62 [56-67] years. After the operation, all patients were divided into 2 groups: 108 patients without POCD and 72 patients with cognitive deficit of various severity. The study was conducted in three stages: stage I — 2 days before surgery; stage II — during the operation; stage III — 7 days after the operation. Assessment of cognitive status using FAB, MMSE tests was carried out at stages I and III. At the second stage, biochemical parameters were assessed: in arterial blood — lactate and hemoglobin levels, in venous blood — pH, partial pressure of carbon dioxide (pCO2, mm Hg) and partial pressure of oxygen (pO2, mm Hg), as well as the duration of operation, cardiopulmonary bypass and myocardial anoxia. Discriminant analysis was used to develop a mathematical model for predicting a binary outcome.Results. Two groups of the most informative indicators were identified that were included in prediction algorithms for binary outcomes "presence/absence of negative dynamics of POCD" for MMSE and FAB. Group 1 included perioperative MMSE values, atrial fibrillation before surgery, cardiopulmonary bypass time and pO2. Group 2 included cardiopulmonary bypass time and intraoperative venous pH. Conclusion. Mathematical models have been developed for predicting the binary outcome "presence/absence of POCD deterioration" according to the MMSE and FAB cognitive tests, which make it possible to assess the possibility of postoperative cognitive dysfunction. The proposed algorithms are implemented using spreadsheets and a computer program.

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Prediction of electrophysiological myocardial instability in the acute period of acute coronary syndrome with ST-segment elevation as an effectiveness indicator of the sudden cardiac death prevention

Cited by 2 publications

References 7 publications

Elements of artificial intelligence in a predictive personalized model of pharmacotherapy choice in patients with heart failure with mildly reduced ejection fraction of ischemic origin

Elements of artificial intelligence in a predictive personalized model of pharmacotherapy choice in patients with heart failure with mildly reduced ejection fraction of ischemic origin

Prediction of postoperative cognitive dysfunction in patients with coronary artery disease after onpump coronary artery bypass grafting

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Prediction of electrophysiological myocardial instability in the acute period of acute coronary syndrome with ST-segment elevation as an effectiveness indicator of the sudden cardiac death prevention

Cited by 2 publications

References 7 publications

Elements of artificial intelligence in a predictive personalized model of pharmacotherapy choice in patients with heart failure with mildly reduced ejection fraction of ischemic origin

Elements of artificial intelligence in a predictive personalized model of pharmacotherapy choice in patients with heart failure with mildly reduced ejection fraction of ischemic origin

Prediction of postoperative cognitive dysfunction in patients with coronary artery disease after on­pump coronary artery bypass grafting

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Prediction of postoperative cognitive dysfunction in patients with coronary artery disease after onpump coronary artery bypass grafting