NSAIDs/Nitazoxanide/Azithromycin Immunomodulatory Protocol Used in Adult, Geriatric, Pediatric, Pregnant, and Immunocompromised COVID-19 Patients: A Real-World Experience
Bibliographic record
Abstract
COVID-19 management still lacks a protocol of proven efficacy, and we present a novel COVID-19 immunomodulatory protocol based on our early pioneering article, re-purposing nitazoxanide/azithromycin combination for early COVID-19 diseases. Our findings were followed by two articles to justify the addition of non-steroidal anti-inflammatory drugs to nitazoxanide/azithromycin. Furthermore, another recent article of ours illustrated the potential immunomodulatory mechanisms by which all the drugs used in this manuscript might be beneficial for COVID-19 patients. We presented a case series of 34 confirmed and highly suspected COVID-19 patients. It is noteworthy that 13 PCR-confirmed COVID-19 patients were included while the others were diagnosed by other measures and all cases were managed by telemedicine. The patients included adult males and females as well as 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 debilitating COVID-19 clinical manifestations, and it was fully achieved within two weeks. Most of the patients who were treated early have fully recovered during their described five days; the leucocytic/lymphocytic counts were significantly improved for those with prior abnormalities. Neither significant adverse effects nor post/para COVID-19 syndrome was reported. In conclusion, we present a pioneering 5-day protocol for the safe and effective treatment of COVID-19 using economic FDA-approved immunomodulatory drugs. We recommend conducting double-blind, randomized clinical trials with sufficient strength at the earliest opportunity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".