SARS-CoV-2 accelerated clearance using a novel nitric oxide nasal spray (NONS) treatment: A randomized trial
Bibliographic record
Abstract
Additional outpatient therapies which are readily accessible will be essential to reduce COVID-19 illness progression in high risk individuals. Especially as the virus continues to mutate with greater transmissibility despite increased global vaccination. A randomized, double-blind, multicentre, parallel group, placebo-controlled phase III clinical trial evaluated the ability of nitric oxide (NO) to rapidly eradicate nasal SARS-CoV-2 RNA. Adults (18–70 years) with mild symptomatic COVID-19 were randomized, confirmed by laboratory SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) nasal swab. Randomisation was 1:1, NONS (N = 153) vs placebo (N = 153). NO generated by a nasal spray (NONS) was self-administered six times daily as two sprays per nostril (0⋅45 mL of solution/dose) for seven days. Patients at high risk of illness progression, defined as unvaccinated, ≥ 45 years of age or having comorbidities, were the primary analysis population. Overall, mean SARS-CoV-2 RNA concentrations (6·96 log10 copies/mL in the NONS group and 7·16 log10 copies/mL in the placebo group) were comparable at baseline. Primary endpoint mean treatment difference SARS-CoV-2 RNA change from baseline to the end of treatment (EOT) was -0·52 copies/mL (SE 0·202, 95% CI -0·92 to -0·12; p = 0·010) with NONS compared to placebo. Secondary endpoint assessments demonstrated a greater proportion of patients receiving NONS (82·8%) cleared SARS-CoV-2 (RT-PCR negative) by EOT compared to placebo (66·7%, p = 0·046), with no virus RNA detected a median of four days earlier compared to placebo (three vs seven days; p = 0·044). Use of NONS in patients recently infected with SARS-CoV-2 accelerates nasal virus clearance. Funding provided by Glenmark Pharmaceuticals Limited. Study medication provided by SaNOtize.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".