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Record W4310930458 · doi:10.21203/rs.3.rs-2045443/v1

Association of Molnupiravir and Nirmatrelvir-Ritonavir with Reduced Mortality and All-cause Sepsis in Hospitalized Patients Infected with Omicron Variant of SARS-CoV-2: A Territory-Wide Prospective Cohort Study

2022· preprint· en· W4310930458 on OpenAlexaff
Abraham Ka Chung Wai, Teddy Tai-loy LEE, Ching-long CHAN, Crystal Ying Chan, Edmond Tsz-fung Yip, Luke Yik-fung Luk, Joshua W. K. Ho, Kevin Wang-leong So, Omar Wai-Kiu Tsui, Man-lok Lam, Shi-yeow LEE, Tafu YAMMAMOTO, Chak Kwan Tong, Man Sing Wong, Eliza Lai‐Yi Wong, Timothy H. Rainer

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsPrincess Margaret Cancer Centre
FundersInnovation and Technology Commission
KeywordsMedicineHazard ratioInternal medicineIncidence (geometry)SepsisProspective cohort studyOrgan dysfunctionProportional hazards modelCohortGastroenterologyConfidence interval

Abstract

fetched live from OpenAlex

Abstract Object This study evaluates the association between antivirals (Molnupiravir and Nirmatrelvir-Ritonavir) and all-cause and respiratory mortality and organ dysfunction among high-risk COVID-19 patients during an Omicron outbreak. Methods Two cohorts, Nirmatrelvir-Ritonavir vs. control and Molnupiravir vs. control, were constructed with inverse probability treatment weighting to balance baseline characteristics. Cox proportional hazards models evaluated the association of their use with all-cause mortality, respiratory mortality, and all-cause sepsis (a composite of circulatory shock, respiratory failure, acute liver injury, coagulopathy, and acute liver impairment). Patients recruited were hospitalized and diagnosed with the COVID-19 Omicron variant between February 22, 2022 to April 15, 2022, and followed up until May 15, 2022. Results The study included 17,704 patients. There were 4.67 and 22.7 total mortalities per 1000 person-days in the Nirmatrelvir-Ritonavir and control groups respectively before adjustment (weighted incidence rate ratio, -18.1 [95%CI, -23.0 to -13.2]; hazard ratio, 0.18 [95%CI, 0.11–0.29]). There were 6.64 and 25.9 total mortalities per 1000 person-days in the Molnupiravir and control groups respectively before adjustment (weighted incidence rate ratio per 1000 person-days, -19.3 [95%CI, -22.6 to -15.9]; hazard ratio, 0.23 [95%CI, 0.18–0.30]). In all-cause sepsis, there were 13.7 and 35.4 organ dysfunction events per 1000 person-days in the Nirmatrelvir-Ritonavir and control groups respectively before adjustment (weighted incidence rate ratio per 1000 person-days, -21.7 [95%CI, -26.3 to -17.1]; hazard ratio, 0.44 [95%CI, 0.38–0.52]). There were 23.7 and 40.8 organ dysfunction events in the Molnupiravir and control groups respectively before adjustment (weighted incidence ratio per 1000 person-days, -17.1 [95%CI, -20.6 to -13.6]; hazard ratio, 0.63 [95%CI, 0.58–0.69]). Conclusions Among COVID-19 hospitalized patients, use of either Nirmatrelvir-Ritonavir or Molnupiravir compared with no antiviral use was associated with a significantly lower incidence of 28-day all-cause and respiratory mortality and sepsis.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.072
GPT teacher head0.458
Teacher spread0.387 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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