NSAIDs/Nitazoxanide/Azithromycin Immunomodulatory Protocol Used in Adults, Geriatric, Pediatric, Pregnant, and Immunocompromised COVID-19 Patients: A Prospective Observational Study and Case-Series
Bibliographic record
Abstract
Updated, peer reviewed and published at Canadian journal of medicinehttps://cjm.cikd.ca/article_60573.htmlIntroduction: COVID-19 management still lacks a protocol of proven efficacy and we present a novel COVID-19 immunomodulatory protocol basing on our early pioneering article that justified repurposing nitazoxanide/azithromycin combination for early COVID-19 which was followed by two articles to justify addition of non-steroidal anti-inflammatory drugs to nitazoxanide/azithromycin as well as by our recent article that illustrates the potential immunomodulatory mechanisms by which all the drugs used in this manuscript might benefit COVID-19 patients.Methods: We present a case series of 38 confirmed and highly suspected COVID-19 consented native Arabic speaking patients, including 12 confirmed by PCR, and the others diagnosed by other measures who were managed by telemedicine. The patients included 15 adult males including an immunocompromised patient, 16 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 / nitazoxanide/ azithromycin +/- cefoperazone either in full or in part. The primary endpoint of this protocol was a full relief of all serious COVID-19 clinical manifestations. Results: The primary endpoint was fully achieved within two weeks. Most of the patients who were treated early, have fully recovered during its described five days; the leucocytic/lymphocytic count was significantly improved for those with prior leucopenia or leucocytosis/lymphopenia. Neither significant adverse effects, nor post/para COVID syndrome was reported. Conclusions: 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.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".