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Record W4412957766 · doi:10.1136/bmjopen-2024-097134

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

2025· article· en· W4412957766 on OpenAlexafffundabout
Banafshe Hosseini, Amanda Condon, Bruno R. da Costa, Peter Daley, Michelle Greiver, Peter Jüni, Todd C. Lee, Kerry McBrien, Emily G. McDonald, Srinivas Murthy, Peter Selby, Melissa K. Andrew, Kris Aubrey‐Bassler, David Barber, Brendan J. Barrett, Christopher Butler, Noah Crampton, Simone Dahrouge, Ali Damji, Robert Fowler, Stephanie Garies, Catherine Hudon, Jennifer Hulme, Jennifer E. Isenor, David J.A. Jenkins, Rosemarie Lall, Annie LeBlanc, Christine Leong, Paul Little, Aïsha Lofters, Sarvesh Logsetty, Sylvain Lother, Marie‐Thérèse Lussier, Laura Maclaren, Dee Mangin, Emily Gard Marshall, John C. Marshall, Rita McCracken, Rahim Moineddin, Brianna Orava, Jean‐Sébastien Paquette, Jay Jae Hee Park, Navindra Persaud, Valeria E. Rac, Vivian R. Ramsden, Jennifer Rayner, Diana C. Sanchez‐Ramirez, Lynora Saxinger, Haolun Shi, Alexander Singer, Rae Spiwak, Anita Srivastava, Abhimanyu Sud, Jean‐Éric Tarride, Deanna Telner, Ross Upshur, Sakina Walji, Rachel Walsh, Machelle Wilchesky, Sabrina T. Wong, Brianne Wood, Ryan Zarychanski, Barb Zelek, Yoav Keynan, Jolanta Piszczek, Daniel Warshafsky, Andrew D. Pinto

Bibliographic record

VenueBMJ Open · 2025
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsMinistry of Health and Long Term CareThunder Bay Regional Research InstituteNOSM UniversityThunder Bay Regional Health Sciences CentreSunnybrook Health Science CentreEast Wellington Family Health TeamManitoba HealthResearch ManitobaUniversity of SaskatchewanUniversity of AlbertaUniversity Health NetworkMcMaster UniversityAccess Alliance Multicultural Health and Community ServicesUniversité LavalProvidence Health CareHumber River Regional HospitalUniversité de MontréalCentre Hospitalier de l’Université de MontréalUniversité de SherbrookeImpactSouth Health CampusWomen's College HospitalNorth York General HospitalSt. Michael's HospitalQueen's UniversityUniversity of OttawaDalhousie UniversityUniversity of ManitobaJewish General HospitalSimon Fraser UniversityMontreal General HospitalUniversity of CalgaryInstitute for Clinical Evaluative SciencesMcGill UniversityCentre for Addiction and Mental HealthÉlisabeth Bruyère HospitalUniversity of TorontoMemorial University of NewfoundlandUniversity of British ColumbiaToronto General HospitalPublic Health Ontario
FundersCanadian Institutes of Health ResearchHealth CanadaUniversity of TorontoPublic Health AgencyPublic Health Agency of Canada
KeywordsMedicineCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Randomized controlled trial2019-20 coronavirus outbreakProtocol (science)PandemicTrial registrationSars virusAlternative medicineVirologyOutbreakInfectious disease (medical specialty)SurgeryInternal medicineDiseasePathology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.099
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.269
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.099
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.539
GPT teacher head0.606
Teacher spread0.066 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designRandomized trial
Domainnot available
GenreProtocol

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".

Quick stats

Citations2
Published2025
Admission routes3
Has abstractyes

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