Objective To study the prognostic role of current serum biomarkers in patients with myocardial infarction (MI) by constructing a multifactorial model for prediction of cardiovascular complications (CVC) in remote MI. Acute coronary syndrome is a major cause of death and disability in the Russian Federation. Introduction of current biomarkers, such as N-terminal pro-brain natriuretic peptide, stimulating growth factor (ST2), and centraxin-2 (Pentraxin, Ptx-3), provides more possibilities for diagnostics and calculation of risk for CVC.Materials and Methods Concentrations of biomarkers were measured in 180 patients with MI (mean age, 61.4±1.7) upon admission. At one year, specific and composite endpoints were determined (MI, acute cerebrovascular disease, admission for CVD, and cardiovascular death). Based on this information, a prognostic model for subsequent events was developed.Results A mathematical model was created for computing the development of a composite endpoint. In this model, the biomarkers NT-proBNP, Ptx-3 and, to a lesser extent, ST2 demonstrated their prognostic significance in diagnosis of CVC with a sensitivity of 78.79 % and specificity of 86.67 % (area under the curve, AUC 0.73).Conclusion In patients with remote MI, the biomarkers NT-proBNP, ST2, and Ptx-3 improve prediction of CVC.
The aim of this study is to develop a method for visual segmentation of various objects of endoscopic images based on a collection of endoscopic images. The method was developed on the basis of a collection of images obtained by ENVD LLC on a contractual basis with medical organizations of the Republic of Bashkortostan, Russia. The collection consists of 70 endoscopic images recording clinical cases diagnosed in accordance with the Paris Tumor Classification of Gastrointestinal Diseases. A number of machine vision operations were carried out, including image preprocessing, image sampling, and subsequent clustering for the purpose of image segmentation. Results: A technique for the analysis of endoscopic images was developed, which makes it possible to obtain the contours of objects of interest to a specialist performing endoscopy. Conclusion. The developed solution allows to speed up and improve the procedure for marking endoscopic images, which in turn prepares a platform for further processing of endoscopic images, for example, nosological classification of neoplasms.
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