Objective. To develop methods for a rapid distance computer diagnosis of COVID-19 based on the analysis of breath sounds. It is known that changes in breath sounds can be the indicators of respiratory organs diseases. Computer analysis of these sounds can indicate their typical changes caused by COVID-19, and can be used for a rapid preliminary diagnosis of this disease. Materials and methods. The method of fast Fourier transform (FFT) was used for computer analysis of breath sounds, recorded near the mouth of 14 COVID-19 patients (aged 1880 years) and 17 healthy volunteers (aged 548 years). The frequency of breath sound records ranged from 44 to 96 kHz. Unlike the conventional methods of computer analysis for diagnosis of diseases based on respiratory sound studying, we offer to test a high-frequency part of FFT (20006000 kHz). Results. While comparing the breath sound FFT in patients and healthy volunteers, we developed the methods for COVID-19 computer diagnosis and determined the numerical criteria in patients and healthy persons. These criteria do not depend on sex and age of the examined persons. Conclusions. The offered computer methods based on the analysis of breath sound FFT in patients and volunteers permit to diagnose COVID -19 with relatively high diagnostic parameters. These methods can be used in development of noninvasive means for preliminary self-express diagnosis of COVID-19.

Background: Respiratory sounds have been recognized as a possible indicator of behavior and health. Computer analysis of these sounds can indicate of characteristic sound changes caused by COVID-19 and can be used for diagnosis of this illness. Purpose: The communication aim is development of fast remote computer-assistance diagnosis of COVID-19, based on analysis of respiratory sounds. Materials and Methods: Fast Fourier transform (FFT) was applied for analyses of respiratory sounds recorded near the mouth of 9 COVID-19 patients and 4 healthy volunteers. Sampling rate was 48 kHz. Results: Comparing of FFT spectrums of the respiratory sounds of the patients and volunteers we proposed numerical healthy-ill criterions. Conclusions: The proposed computer method, based on analysis of the FFT spectrums of respiratory sounds of the patients and volunteers, allows one to automatically diagnose COVID-19 with sufficiently high diagnostic values. This method can be applied at development of noninvasive self-testing kits for COVID-19.

Oropharyngeal candidiasis in 512 HIV-infected patients at the late stages of the disease was studied with special reference to the clinical and microbiological characteristics of this condition. The diagnosis was established based on the results of the clinical and microbiological examination of the patients including investigation of the tissue samples taken from the oral cavity and the throat with the use of the device specially developed for this purpose. It was shown that the disease existed in various clinical forms the most common of which were monocomponent pathology represented by pseudomembranous candidiasis in 37.5±2.14% of the patients, the two-component mixed form (pseudomembranous candidiasis with concomitant angular chelitis) diagnosed in 27.5±1.97% cases, and the ternary form (the combination of pseudomembranous candidiasis, acute atrophic process, and angular chelitis) documented in 11.9±1.43% patients. The main clinical features of the disease included the combination of its various forms, multiple localization of the pathological process, and its polymorphous manifestations. Changes in the clinical course of oropharyngeal candidiasis associated with the progression of HIV from the 4A to the 4B stage were detected for the first time. They were shown to be accompanied by variations in the species composition and concentration of fungal flora in the crypts of the palatine tonsils and its sensitivity to fluconazole therapy.

Background Respiratory sounds have been recognized as a possible indicator of behavior and health. Computer analysis of these sounds can indicate characteristic sound changes caused by COVID-19 and can be used for diagnostics of this illness. Objective The aim of the study is to develop 2 fast, remote computer-assisted diagnostic methods for specific acoustic phenomena associated with COVID-19 based on analysis of respiratory sounds. Methods Fast Fourier transform (FFT) was applied for computer analysis of respiratory sound recordings produced by hospital doctors near the mouths of 14 patients with COVID-19 (aged 18-80 years) and 17 healthy volunteers (aged 5-48 years). Recordings for 30 patients and 26 healthy persons (aged 11-67 years, 34, 60%, women), who agreed to be tested at home, were made by the individuals themselves using a mobile telephone; the records were passed for analysis using WhatsApp. For hospitalized patients, the illness was diagnosed using a set of medical methods; for outpatients, polymerase chain reaction (PCR) was used. The sampling rate of the recordings was from 44 to 96 kHz. Unlike usual computer-assisted diagnostic methods for illnesses based on respiratory sound analysis, we proposed to test the high-frequency part of the FFT spectrum (2000-6000 Hz). Results Comparing the FFT spectra of the respiratory sounds of patients and volunteers, we developed 2 computer-assisted methods of COVID-19 diagnostics and determined numerical healthy-ill criteria. These criteria were independent of gender and age of the tested person. Conclusions The 2 proposed computer-assisted diagnostic methods, based on the analysis of the respiratory sound FFT spectra of patients and volunteers, allow one to automatically diagnose specific acoustic phenomena associated with COVID-19 with sufficiently high diagnostic values. These methods can be applied to develop noninvasive screening self-testing kits for COVID-19.

Цель. Выделение периодов развития эпидемического процесса при ВИЧ-инфекции на территории Пермского края, характеристика структуры основных СПИД-ассоциированных заболеваний. Методы. Проведён анализ заболеваемости ВИЧ-инфекцией и СПИД-ассоциированными заболеваниями на территории Пермского края на основании данных официальной статистики за 1988-2015 гг. Для этого использованы данные ретроспективного изучения первичной медицинской документации (индивидуальные карты амбулаторных больных); форма №61, утверждённая Постановлением Росстата №1 от 09.01.2008 «Сведения о контингентах больных ВИЧ-инфекцией». Определены частота и структура основных оппортунистических инфекций в различные периоды эпидемического процесса. Результаты. Выделено пять периодов развития эпидемического процесса при ВИЧ-инфекции на террито