The authors developed and substantiated the original methods of arterial oscillography, which were implemented in the developed Oranta-AO information system. The methods of application to the arterial oscillogram registered at measurement of arterial pressure gives the possibility to carry out the supplementary systematic assessment of health, functional state of cardiovascular system, its reserve possibilities etc. The authors also developed an Expert System (based on machine-learning methods) for the differential diagnosis of risks of heart, lung, mental illness and prognosis of some blood parameters. Oranta-AO software system was created based on research results due to methods and algorithms that were innovate. For the mathematical modeling of arterial oscillograms used cyclic random processes. Methods of arterial oscillograms processing based on its model in the form of a cyclic random process was developed. The method of evaluation of the rhythm function of arterial oscillograms and statistical methods for estimating the probabilistic characteristics of arterial oscillograms were developed. To solve the clustering problem, the Python
k
-means and
k
-means++ algorithm were used. Oranta-AO information system consists of three interrelated parts: mobile application, computing kernel and web system. Computing kernel and web system are deployed on AWS servers and have been tested already. The developed environment aims to be integrated into every new model of electronic meters in the world. Certification (EN 62304:2014, ISO 13485: 2018) in Ukraine is completed, PCT priority is completed. The next step will be to establish cooperation with manufacturers of electronic pressure monitors, patenting and certification in world.
An algorithm for constructing a correlation portrait of adaptation mechanisms of disease course during medical research is described in the article. The correlation portrait of the arterial oscillograms and electrocardiograms measurements for cardiovascular, pulmonary diseases, cerebral circulation disorders, and degenerative disc disease of the cervical spine and in healthy subjects is presented.
Patients with chronic kidney disease (CKD) have significantly poorer functional outcomes and greater mortality after suffering a stroke. The present study aimed to identify the prognostic factors of an unfavorable outcome of the ischemic stroke in patients with CKD.
Methods and subjects. The current study was designed retrospectively and performed with data of patients who were hospitalized due to ischemic stroke to the neurological department. A complex clinical and neuroimaging investigation was carried out in 65 patients (30 men and 35 women) aged 53 to 81 years (mean age – (67.7 ± 5.9) years) with acute stroke and CKD. Patients underwent all the necessary ancillary investigations according to guidelines. According to the clinical outcome on the 21-st day by the modified Rankin scale (mRS) all patients were divided into two groups: 1-st –favorable stroke outcome (mRS=0-3) – 34 (52.3%), 2-nd – unfavorable stroke outcome – (mRS=4-6) – 31 (47.7%).
Results. During comparing the basic characteristics of both groups, it was revealed that patients with unfavorable functional outcomes were almost twice as likely to have diabetes mellitus (51.6% vs. 26.5%, p<0.037) and atrial fibrillation (41.9% vs. 17.6%, p<0.032). In age-and sex-adjusted multifactor logistic regression it was found that ischemic stroke unfavorable outcome is associated with diabetes mellitus (OR – 2.5, CI: 1.6-8.3; p=0.014), atrial fibrillation – 2.7, CI: 0.7-9.6; p=0.043), dialysis therapy (OR – 3.4, CI: 2.3-8.1; p=0.007), GFR <42 ml/min/1.73 m2 (OR – 2.7, CI: 2.1-7.8; p=0.003).
Conclusions. Determining prognostic factors of unfavorable course of the ischemic stroke in patients with CKD allows to optimize the management of such patients in the acute period of ischemic stroke and improve the prognosis.
Structuring the knowledge and activities of a massage specialist will enable the further inclusion of the information in the web, mobile-oriented information system, which will improve the quality of training of future rehabilitation specialists.
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