Photodynamic nasal SARS-CoV-2 decolonization shortens infectivity and influences specific T-Cell responses
Bibliographic record
Abstract
Background The main objective was to evaluate the efficacy of intranasal photodynamic therapy (PDT) in SARS-CoV-2 mildly symptomatic carriers on decreasing the infectivity period. SARS-CoV-2-specific immune-stimulating effects and safety were also analysed. Methods We performed a randomized, placebo-controlled, clinical trial in a tertiary hospital (NCT05184205). Patients with a positive SARS-CoV-2 PCR in the last 48 hours were recruited and aleatorily assigned to PDT or placebo. Patients with pneumonia were excluded. Participants and investigators were masked to group assignment. The primary outcome was the reduction in in vitro infectivity of nasopharyngeal samples at days 3 and 7. Additional outcomes included safety assessment and quantification of humoral and T-cell immune-responses. Findings Patients were recruited between December 2021 and February 2022. Most were previously healthy adults vaccinated against COVID-19 and most carried Omicron variant. 38 patients were assigned to placebo and 37 to PDT. Intranasal PDT reduced infectivity at day 3 post-treatment when compared to placebo with a β-coefficient of -812.2 (CI95%= -478660 – -1.3, p<0.05) infectivity arbitrary units. The probability of becoming PCR negative (ct>34) at day 7 was higher on the PDT-group, with an OR of 0.15 (CI95%=0.04-0.58). There was a decay in anti-Spike titre and specific SARS-CoV-2 T cell immunity in the placebo group 10 and 20 weeks after infection, but not in the PDT-group. No serious adverse events were reported. Interpretation Intranasal-PDT is safe in pauci-symptomatic COVID-19 patients, it reduces SARS-CoV-2 infectivity and decelerates the decline SARS-CoV-2 specific immune-responses.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".