Diclofenac potassium/Nitazoxanide/Azithromycin Used in Adults, Children and Pregnant Patients: A Novel Potential Game Changer COVID-19 Protocol.
Bibliographic record
Abstract
Updated, peer reviewed and published at Canadian Journal of Medicinehttps://cjm.cikd.ca/article_60573.html To date no treatment protocol of proven efficacy was approved to manage COVID-19. We have developed a novel COVID-19 immunomodulatory protocol basing on our early pioneering article that justified repurposing of nitazoxanide/azithromycin combination for early cases of COVID-19 which was followed by two articles to justify addition of non-steroidal anti-inflammatory drugs to nitazoxanide/azithromycin. We are presenting a prospective telemedicine protocol that managed more than 50 documented COVID-19 patients while fully presenting a case series of 36 patients/legal guardians COVID-19 Arab patients including 12 confirmed by PCR and 23 diagnosed by other measures. The patients included 14 adult males including an immunocompromised patient, 15 adult females including one lactating, 3 pregnant patients including one confirmed by PCR as well as 4 children. All patients have received a short 5-day-regimen of NSAIDs (diclofenac potassium in most of cases, ibuprofen, lornoxicam, meloxicam, celecoxib, naproxen, ketoprofen or ketorolac)/nitazoxanide/azithromycin +/- cefoperazone either in full or in part as illustrated in the manuscript. The primary endpoint of this protocol was full relief of all serious COVID-19 clinical manifestations and it was fully achieved in all patients within two weeks. Most of the patients treated early have fully recovered during its described five days; the leucocytic/lymphocytic count was significantly improved for those with prior leucopenia/lymphopenia. No significant adverse effects were reported. A novel 5-day-protocol to safely and effectively cure COVID-19 using repurposed immunomodulatory safe and inexpensive FDA approved drugs is illustrated and we recommend performing sufficiently powered double blind randomized clinical trials against any current standard protocol.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".