Major ongoing clinical trials for COVID-19 treatment and studies currently being conducted or scheduled in Japan
Bibliographic record
Abstract
The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious threat to global public health and economies. Currently, hundreds of clinical trials on a wide variety of treatments against COVID-19 are being conducted around the world. Here, we conducted a search for ongoing clinical trials for the treatment of COVID-19 at the clinicaltrials.gov database on April 2, 2020. In total, 48 clinical trials were identified, and of these, 41 trials adopted drug intervention and the other 7 trials utilized biological intervention. The number of trials stratified by a chief country conducting the investigation were 18 in China, 5 in the United States, 4 in Canada, 3 in Italy, 2 in France and Brazil, and 4 trials are being performed multinationally. The drugs utilized in more than one trials were remdesivir (6 trials), lopinavir/ritonavir (6 trials), hydroxychloroquine (6 trials), interferon (5 trials), methylprednisolone (3 trials), nitric oxide gas (3 trials), oseltamivir (2 trials), arbidol (2 trials), and vitamin C (2 trials). We also described the Japanese trials which are now being conducted or scheduled, utilizing lopinavir/ritonavir, remdesivir, favipiravir, ciclesonide and nafamostat.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".