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Meditsinskiy Sovet ; 2022(1):134-141, 2022.
Article in Russian | Scopus | ID: covidwho-1766255


Introduction. Currently, the coronavirus infection pandemic caused by the SARS-CoV-2 virus continues around the world. Research data from domestic and foreign authors indicate that the kidneys are a target organ for a new infection, lesions vary from pro-teinuria and hematuria to acute kidney injury. Aim of the study – to determine the frequency and nature of kidney damage in children with confirmed coronavirus infection. Materials and methods. A retrospective and prospective analysis of cases of confirmed COVID-19 infection in children (n = 441) admitted to the Samara Regional Children’s Infectious Diseases Hospital from March 2020 to July 2021 was carried out. SARS-CoV-2 RNA was detected in all patients by a one-step reverse transcription reaction combined with a polymerase chain reaction. The changes in the kidneys that occurred in 57 children were studied. The research results were processed using the Statistica 7.0 software (StatSoft, USA). Results. The involvement of the kidneys in the infectious process was detected in every 8 children with COVID-19 (12.9%), more often in the form of isolated urinary syndrome, the detection rate of which correlated with the severity of the course of corona-virus infection: in severe cases, proteinuria was detected in 31.6% of patients, hematuria – in 21%, acute kidney injury – in 10.5%, diabetic nephropathy – in 5.3%. Kidney damage was combined with damage to the respiratory and gastrointestinal tract, charac-terized by rapid recovery of urine output and azotemia parameters without special renal therapy. A clinical case of the onset of nephrotic syndrome that developed 2 weeks after suffering a coronavirus infection is described. Conclusions. Children with COVID-19 require kidney function monitoring for early detection and correction in case of impairment. Patients with isolated urinary syndrome in the acute period require long-term observation in order to detect latent renal pathology. © 2022, Remedium Group Ltd. All rights reserved.

International Journal of Radiation Oncology, Biology, Physics ; 111(3):e503-e503, 2021.
Article in English | CINAHL | ID: covidwho-1428064
International Journal of Radiation Oncology, Biology, Physics ; 111(3):S94-S95, 2021.
Article in English | CINAHL | ID: covidwho-1428039
American Journal of Respiratory and Critical Care Medicine ; 203(9):2, 2021.
Article in English | Web of Science | ID: covidwho-1407330
American Journal of Respiratory and Critical Care Medicine ; 203(9), 2021.
Article in English | EMBASE | ID: covidwho-1277088


Rationale:Knowledge and awareness of COVID-19 likely results in better compliance with the guidelines set forth by local governments and may help prevent community spread of the disease. We designed a population-based survey to estimate the difference in knowledge among different groups of individuals based on sociodemographic diversities. The secondary objective was to identify significant determinants of knowledge on COVID-19. Methods: The survey questionnaire was built in Redcap. Knowledge-related questions were based on 34 metrics, including risk factors for severe infection, disease spread, prevention, treatment, and general information. Most of the questions were dichotomous ('Yes' or 'No' response). We used social media platforms, Studyfinder, and Researchmatch to send the survey link. Five sociodemographic determinants were considered potential predictors of knowledge, including age, race, education level, gender, and Healthcare Worker. Participants were also asked about their preferred source of information on COVID-19. The data was collected between June to November 2020. The 'Factor analysis' function in 'SPSS' was used to convert the 34-knowledge metrics into a single standardized scale of '0-10' for further analyses. Generalized Linear Model was built to measure the degree of association among the predictors and the knowledge score, based on 'model effect'. We further used the Machine learning tool 'Neural network' to generate a rank list of the knowledge determinants. Results: 1139 participants (male: female = 1:3) from all 50 US states participated in the survey. The generalized linear model demonstrated that the chosen determinants could precisely predict the knowledge score (χ2=93.68,p<0.001). All predictors, except healthcare workers, had significant associations with the knowledge score. Race had the highest association followed by Education, Gender, and Age (χ2=69.29,p<0.001;χ2=15.35,p<0.001;χ2=12.34,p=0.002 and χ2=4.04,p=0.044, respectively). Neural network reproduced the exact rank list with the normalized importance for Race, Education, Gender, and Age, which were 100%, 24.6%, 20%, 15.8%, respectively. Participants belonging to the 'White' race had a significantly higher score (7.71±1.13) compared to the 'Black' race (6.77±1.69) (p<0.001), while 'Female' participants performed better (7.60±1.39) compared to 'Male' (7.20±1.61) (p<0.001). Younger participants (18-44 years) had statistically significantly lower knowledge compared to older age groups (>60years) (p<0.05). Among available sources of information on COVID-19, 'City/State websites' was the most popular (67.9% favored 'Yes' vs. 'No'), followed closely by 'Television' (67.8%) and 'CDC website' (62.2%). Conclusions: 'Race' was the strongest sociodemographic predictor of COVID-related knowledge, and white, older, female participants with higher education (Masters/Ph.D.) demonstrated better knowledge than the rest of the population.