The use of selenium-containing drugs in the prevention and treatment of complications in patients with COVID-19
Bibliographic record
Abstract
Objective. To study literature data reflecting the use of selenium (Se) and selenium-containing drugs in the complex prophylaxis and treatment of complications in patients with COVID-19. Material and methods. Data analysis of 37 publications of scientists from Russian Federation, United States of America, People's Republic of China, Great Britain, India, France, Germany, Italy, Sweden, Canada, Brazil, United Arab Emirates, Saudi Arabia, Ireland, Holland, Greece, Australia, Poland, Pakistan, Sudan, Nepal was performed. The authors reflected on the epidemiology, diagnosis, pathogenesis, clinic, risk of acute respiratory distress syndrome, multiple organ failure, cardiovascular complications, mortality in patients with COVID-19, the importance of Se deficiency in the body and the preventive use of selenium-containing drugs in novel coronavirus infection. Results. Low dietary Se intake was associated with the development of acute respiratory distress syndrome in men and women with COVID-19. Deficiencies were associated with increased risk of morbidity and mortality. Organic forms of Se had the best bioavailability. Se had antioxidant, anti-inflammatory, antithrombotic, antiviral, immunomodulatory effects in patients with COVID-19. Conclusions. Thus, control and optimization of the selenium status in population of selenium-deficient areas with addition of Se-enriched food to the diet, as well as SELENBIO for women complex of Russian company "Parapharm" could be one of the directions of prevention and treatment of complications in patients with COVID-19.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".