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Record W3022025532 · doi:10.1007/s12630-020-01684-7

Post-exposure prophylaxis or pre-emptive therapy for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): study protocol for a pragmatic randomized-controlled trial

2020· article· en· W3022025532 on OpenAlexaffabout
Sylvain Lother, Mahsa Abassi, Alyssa Agostinis, Ananta Bangdiwala, Matthew P. Cheng, Glen Drobot, Nicole Engen, Kathy Huppler Hullsiek, Lauren E. Kelly, Todd C. Lee, Sarah M Lofgren, Lauren J MacKenzie, Nicole Marten, Emily G. McDonald, Elizabeth C Okafor, Katelyn A Pastick, Matthew F Pullen, Radha Rajasingham, Ilan S. Schwartz, Caleb P Skipper, Alexis F. Turgeon, Ryan Zarychanski, David R. Boulware

Bibliographic record

VenueCanadian Journal of Anesthesia/Journal canadien d anesthésie · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsCancerCare ManitobaSt. Boniface HospitalMcGill UniversityInstitute of Infection and ImmunityMcGill University Health CentreUniversité LavalUniversity of AlbertaUniversity of Manitoba
FundersNational Institute of Allergy and Infectious DiseasesNational Center for Advancing Translational SciencesNational Institute of Mental Health
KeywordsMedicineHydroxychloroquineRandomized controlled trialAsymptomaticClinical trialPlaceboPandemicIntensive careIntensive care medicineSeverity of illnessInternal medicinePediatricsDiseaseCoronavirus disease 2019 (COVID-19)PathologyAlternative medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 causing the coronavirus disease (COVID-19) pandemic. Currently, there is a lack of evidence-based therapies to prevent COVID-19 following exposure to the virus, or to prevent worsening of symptoms following confirmed infection. We describe the design of a clinical trial of hydroxychloroquine for post-exposure prophylaxis (PEP) and pre-emptive therapy (PET) for COVID-19. METHODS: We will conduct two nested multicentre international double-blind randomized placebo-controlled clinical trials of hydroxychloroquine for: 1) PEP of asymptomatic household contacts or healthcare workers exposed to COVID-19 within the past four days, and 2) PET for symptomatic outpatients with COVID-19 showing symptoms for less than four days. We will recruit 1,500 patients each for the PEP and PET trials. Participants will be randomized 1:1 to receive five days of hydroxychloroquine or placebo. The primary PEP trial outcome will be the incidence of symptomatic COVID-19. The primary PET trial outcome will be an ordinal scale of disease severity (not hospitalized, hospitalized without intensive care, hospitalization with intensive care, or death). Participant screening, informed consent, and follow-up will be exclusively internet-based with appropriate regulatory and research ethics board approvals in Canada and the United States. DISCUSSION: These complementary randomized-controlled trials are innovatively designed and adequately powered to rapidly answer urgent questions regarding the effectiveness of hydroxychloroquine to reduce virus transmission and disease severity of COVID-19 during a pandemic. In-person participant follow-up will not be conducted to facilitate social distancing strategies and reduce risks of exposure to study personnel. Innovative trial approaches are needed to urgently assess therapeutic options to mitigate the global impact of this pandemic. TRIALS REGISTRATION: clinicaltrials.gov (NCT04308668); registered 16 March, 2020.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.040
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.084
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.041
Meta-epidemiology (narrow)0.0090.004
Meta-epidemiology (broad)0.0160.007
Bibliometrics0.0030.004
Science and technology studies0.0040.005
Scholarly communication0.0050.005
Open science0.0040.003
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0840.016

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 head0.059
GPT teacher head0.388
Teacher spread0.329 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations26
Published2020
Admission routes2
Has abstractyes

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