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Record W4388111493 · doi:10.2217/fvl-2023-0115

Oral Bemnifosbuvir (AT-527) Vs Placebo in Patients With mild-to-moderate COVID-19 in an Outpatient Setting (MORNINGSKY)

2023· article· en· W4388111493 on OpenAlexaff
Arantxa Horga, Rebecca Saenz, Gürdal Yılmaz, Jesus Abraham Simón Campos, Keith Pietropaolo, William Stubbings, Neil Collinson, Laura Ishak, Bruce Belanger, Catherine Granier, Kai Lin, Aeron C. Hurt, Xiao‐Jian Zhou, Steffen Wildum, Janet Hammond

Bibliographic record

VenueFuture Virology · 2023
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsRoche (Canada)
FundersF. Hoffmann-La Roche
KeywordsCoronavirus disease 2019 (COVID-19)MedicinePlaceboSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakInternal medicineVirologyPathologyAlternative medicineOutbreakDisease

Abstract

fetched live from OpenAlex

Aim: This phase III study assessed the efficacy/safety/antiviral activity/pharmacokinetics of bemnifosbuvir, a novel, oral nucleotide analog to treat COVID-19. Patients & methods: Outpatient adults/adolescents with mild-to-moderate COVID-19 were randomized 2:1 to bemnifosbuvir/placebo. Time to symptom alleviation/improvement (primary outcome), risk of hospitalization/death, viral load and safety were evaluated. Results: Although the study was discontinued prematurely and did not meet its primary end point, bemnifosbuvir treatment resulted in fewer hospitalizations (71% relative risk reduction), COVID-19-related medically attended hospital visits, and COVID-19-related complications compared with placebo. No reduction in viral load was observed. The proportion of patients with adverse events was similar; no deaths occurred. Conclusion: Bemnifosbuvir showed hospitalization reduction in patients with variable disease progression risk and was well tolerated. Clinical Trial Registration: NCT04889040 (ClinicalTrials.gov).

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)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.034
GPT teacher head0.389
Teacher spread0.354 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations19
Published2023
Admission routes1
Has abstractyes

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