Canadian Adaptive Platform Trial of Treatments for COVID in Community Settings (CanTreatCOVID): protocol for a randomized controlled adaptive platform trial of treatments for acute SARS-CoV-2 infection in community settings
Notice bibliographique
Résumé
ABSTRACT Introduction While effective vaccines and natural immunity have significantly reduced hospitalizations and the need for critical care, SARS-CoV-2 is now endemic and is expected to continue to pose a threat to health. New variants are expected to continue to emerge, and vaccines may become less effective. Effective and affordable therapeutics for SARS-CoV-2 that can be easily used in community settings are needed to accelerate recovery, reduce hospitalizations and mortality, and mitigate the development of post-acute sequelae of SARS-CoV-2, also known as “long COVID.” In this paper we present the design of the Canadian Adaptive Platform Trial of Treatments for COVID in Community Settings (CanTreatCOVID). Methods and analysis CanTreatCOVID is an open-label, individually randomized, multi-centre, national adaptive platform trial designed to evaluate the clinical and cost-effectiveness of therapeutics for non-hospitalized 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 multi-faceted public communication strategy and outreach through primary care, out-patient clinics, and emergency departments. Participants are randomized 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 twice daily 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 hospitalization or death within 28 days of randomization. Ethics and dissemination The CanTreatCOVID master protocol and sub-protocols 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 policymakers, presented at conferences, and published in peer-reviewed journals to ensure that findings are accessible to the broader scientific and medical communities. Trial registration number: NCT05614349 Strengths and Limitations Box The CanTreatCOVID community-focused design allows enrollment without in-person visits. The adaptive platform trial structure provides flexibility to add promising therapies and remove ineffective ones, which is critical in a rapidly changing pandemic environment CanTreatCOVID gathers real-world data on outpatient COVID-19 care The open-label design avoids logistical challenges associated with placebo controls in large-scale trials, though it may introduce bias related to subjective outcomes The reliance on self-reported adherence to study medications could lead to variability
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,020 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,002 |
| Méta-épidémiologie (sens large) | 0,005 | 0,004 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,050 | 0,005 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».