Canadian Adaptive Platform Trial of Treatments for COVID in Community Settings (CanTreatCOVID): protocol for a randomised controlled adaptive platform trial of treatments for acute SARS-CoV-2 infection in community settings
Bibliographic record
Abstract
INTRODUCTION: SARS-CoV-2 is now endemic and expected to remain a health threat, with new variants continuing to emerge and the potential for vaccines to become less effective. While effective vaccines and natural immunity have significantly reduced hospitalisations and the need for critical care, outpatient treatment options remain limited, and real-world evidence on their clinical and cost-effectiveness is lacking. In this paper, we present the design of the Canadian Adaptive Platform Trial of Treatments for COVID in Community Settings (CanTreatCOVID). By evaluating multiple treatment options in a pragmatic adaptive platform trial, this study will generate high-quality, generalisable evidence to inform clinical guidelines and healthcare decision-making. METHODS AND ANALYSIS: CanTreatCOVID is an open-label, individually randomised, multicentre, national adaptive platform trial designed to evaluate the clinical and cost-effectiveness of therapeutics for non-hospitalised SARS-CoV-2 patients across Canada. Eligible participants must present with symptomatic SARS-CoV-2 infection, confirmed by PCR or rapid antigen testing (RAT), within 5 days of symptom onset. The trial targets two groups that are expected to be at higher risk of more severe disease: (1) individuals aged 50 years and older and (2) those aged 18-49 years with one or more comorbidities. CanTreatCOVID uses numerous approaches to recruit participants to the study, including a multifaceted public communication strategy and outreach through primary care, outpatient clinics and emergency departments. Participants are randomised to receive either usual care, including supportive and symptom-based management, or an investigational therapeutic selected by the Canadian COVID-19 Outpatient Therapeutics Committee. The first therapeutic arm evaluates nirmatrelvir/ritonavir (Paxlovid), administered two times per day for 5 days. The second therapeutic arm investigates a combination antioxidant therapy (selenium 300 µg, zinc 40 mg, lycopene 45 mg and vitamin C 1.5 g), administered for 10 days. The primary outcome is all-cause hospitalisation or death within 28 days of randomisation. ETHICS AND DISSEMINATION: The CanTreatCOVID master protocol and subprotocols have been approved by Health Canada and local research ethics boards in the participating provinces across Canada. The results of the study will be disseminated to policy-makers, presented at conferences and published in peer-reviewed journals to ensure that findings are accessible to the broader scientific and medical communities. This study was approved by the Unity Health Toronto Research Ethics Board (#22-179) and Clinical Trials Ontario (Project ID 4133). TRIAL REGISTRATION NUMBER: NCT05614349.
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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 | 0.029 | 0.028 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.059 | 0.008 |
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".