SummaryOver 12 years of cellular therapy in cardiology, some dictinct positive results are obtained in randomized studies. However, exact mechanisms of hematopoietic stem cell actions are still unclear under these clinical conditions. Paracrine effects of cell therapy cannot explain all these effects. Enhanced neoangiogenesis upon stem cell injection is a proven mechanism for improvement of blood supply to the heart. Meanwhile, a decreased revascularization effect 3-4 years after cell therapy is followed by repeated myocardial improvement 6-9 mo after repeated cell infusions with active development of collateral vessels, thus suggesting an additional mechanism for improvement of coronary blood supply. Restoration of regulatory functions of endothelium and smooth muscle cells, including increased NO synthase activity of endothelium and its interactions with myocardiocytes may represent a probable mechanism for this action.
Objective:to develop algorithm of independent groups comparison for nominal data of prospective non-randomized clinical trial AMIRI CABG (ClinicalTrials.gov Identifier: NCT03050489) using SAS Enterprise Guide 6.1. Materials and methods.Data collection was performed according to prospective non-randomized clinical trial AMIRI CABG in Pavlov First St. Petersburg State Medical University, Saint Petersburg, Russia between 2016-2019years with 336 patients. Patients were allocated into three groups of treatment. There is database which include following information: gender, myocardial infarction, stroke and postoperative bleeding. Comparison for nominal data (gender and incidence of myocardial infarction, stroke and bleeding) were calculated with SAS Enterprise Guide6.1 software with Chi-squared test and exact Fisher test. Results.There was developed algorithm of two independent groups comparison for nominal data. Conclusion.Presented algorithm of data analysis allows to compare independent groups for nominal data.
The analysis of the epidemic process associated with COVID-19 is carried out, possible scenarios of the development of events are presented. The most common anamnestic data, symptoms of infection, clinical picture and possible complications are described in detail. The features of the COVID-19 course in risk groups and the algorithms of administrative and medical actions that should underlie the provision of medical care to patients with cardiovascular, oncological, rheumatological diseases, pregnant women, etc. The section of diagnostics and examination features is of particular importance, since it includes not only the definition of the causative agent of the disease, but also the main indicators that determine the severity of the clinical picture, prognosis, the nature and extent of medical care. Considerable experience is presented in the clinical practice of computed tomography of the lungs, the method, the primary and early method for identifying not only lung lesions, but also the underlying disease — COVID-19. Information is presented from literary sources based on the experience of overcoming this formidable disease and its consequences by our colleagues, as well as the experience of domestic clinicians and scientists.
Objective: to develop algorithm of multiple comparisons data of prospective non-randomized clinical trial AMIRI CABG (ClinicalTrials.gov Identifier: NCT03050489) using SAS Enterprise Guide 6.1. Materials and methods. Data collection was performed according prospective non-randomized clinical trial AMIRI CABG (ClinicalTrials.gov Identifier: NCT03050489) in 1Pavlov First St. Petersburg State Medical University, Saint-Petersburg, Russia between 2016-2019 years with 336 patients. There is database with clinical, laboratory and instrumental data. Multiple comparisons test was performed with SAS Enterprise Guide 6.1. Results. There was developed algorithm of multiple comparisons data of prospective non-randomized clinical trial AMIRI CABG (ClinicalTrials.gov Identifier: NCT03050489). This algorithm could be useful for physicians and researchers for data analysis. Conclusion. Presented algorithm of data analysis could make easier and improve efficient data analysis. SAS Enterprise Guide 6.1 allows fast and accurate process data Key words: SAS Enterprise Guide 6.1, statistical analysis, clinical trials, multiple comparisons, Bonferroni adjustment, Kruskal-Wallis test, Wilcoxon test, Tukey test.
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