Clinico-Virological Outcomes and Mutational Profile of SARS-CoV-2 in Adults Treated with Ribavirin Aerosol for COVID-19 Pneumonia
Bibliographic record
Abstract
The emergence of new SARS-CoV-2 variants can affect vaccine efficacy, laboratory diagnosis and the therapies already available, triggering interest in the search for antiviral agents for SARS-CoV-2 infections. Ribavirin (RBV) is a broad-spectrum antiviral with demonstrated in vitro activity against multiple viruses, including SARS-CoV-2. This retrospective study evaluated the dynamics and viral clearance of SARS-CoV-2 in hospitalised adult participants (PTs) with COVID-19 pneumonia who received an RBV aerosol within a compassionate use study. The impact of RBV on the clinical outcome and the mutational profile of SARS-CoV-2 was also assessed. The median RNA values measured in nine PTs included in this study decreased from baseline to discharge (at BL, threshold cycle (Ct) = 22.4, IQR 19.84–5.07; at discharge, Ct = 27.92, IQR 26.43–36.11), with a significant decline in the Ct value evaluated by Friedman rank ANOVA analysis, p = 0.032. Seven out of nine PTs experienced a clinical improvement, while two PTs deceased during hospitalisation. In PTs with a favourable outcome, the virus clearance rate at discharge was 28.6%. The cumulative clearance rate was 71.4% within 14 days from discharge. A mutational pattern after RBV was detected in three out of five PTs in whom whole-genome sequencing was available. Our findings suggest that RBV limits SARS-CoV-2 replication, possibly resulting in a favourable clinical outcome. Ribavirin may also contribute to the mutational spectrum of SARS-CoV-2.
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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 | 0.001 |
| 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) | 0.001 | 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".