Evidence map›Paper›PMID 37287404›Full record

ArticleJournal of medical virology2023

A mathematical model of SARS-CoV-2 immunity predicts paxlovid rebound.

Benjamin L Ranard, Carson C Chow, Murad Megjhani, Shadnaz Asgari, Soojin Park, Yoram Vodovotz

Open access · bronzeAbstract read
In one paragraph

Article in Journal of medical virology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 5 institutions in 1 country.

Benjamin L RanardDivision of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, Columbia University/Columbia University Irving Medical Center/NewYork-Presbyterian, New York, USA.ORCID 0000-0002-9565-6939
Carson C ChowMathematical Biology Section, Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, USA.
Murad MegjhaniProgram for Hospital and Intensive Care Informatics, Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons, New York, USA.
Shadnaz AsgariDepartment of Biomedical Engineering, California State University, Long Beach, California, USA.
Soojin ParkProgram for Hospital and Intensive Care Informatics, Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons, New York, USA.
Yoram VodovotzDepartment of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Columbia University Irving Medical Center · USCalifornia State University, Long Beach · USColumbia University · USNational Institute of Diabetes and Digestive and Kidney Diseases · USUniversity of Pittsburgh · US

Funding

Patient Safety and Health Services Research TrainingT32HS026121 · AHRQ · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI ADELMAN, JASON STUART, BARR, R GRAHAM · 2018 to 2024
$2.4M
AHRQ HHS T32 HS026121
6 · The paper itself

Abstract

Nirmatrelvir/ritonavir (Paxlovid), an oral antiviral medication targeting SARS-CoV-2, remains an important treatment for COVID-19. Initial studies of nirmatrelvir/ritonavir were performed in SARS-CoV-2 unvaccinated patients without prior confirmed SARS-CoV-2 infection; however, most individuals have now either been vaccinated and/or have experienced SARS-CoV-2 infection. After nirmatrelvir/ritonavir became widely available, reports surfaced of "Paxlovid rebound," a phenomenon in which symptoms (and SARS-CoV-2 test positivity) would initially resolve, but after finishing treatment, symptoms and test positivity would return. We used a previously described parsimonious mathematical model of immunity to SARS-CoV-2 infection to model the effect of nirmatrelvir/ritonavir treatment in unvaccinated and vaccinated patients. Model simulations show that viral rebound after treatment occurs only in vaccinated patients, while unvaccinated (SARS-COV-2 naïve) patients treated with nirmatrelvir/ritonavir do not experience any rebound in viral load. This work suggests that an approach combining parsimonious models of the immune system could be used to gain important insights in the context of emerging pathogens.

Indexed as

COVID-19SARS-CoV-2Antiviral AgentsDrug CombinationsHumansLactamsLeucineNitrilesProlineRitonavirAntiviral AgentsDrug CombinationsLactamsLeucinenirmatrelvirnirmatrelvir and ritonavir drug combinationNitrilesProlineRitonavirantiviral agentscomputer modeling: biostatistics & bioinformaticsimmune responsesSARS coronavirus: virus classification

Identifiers

PMID37287404
PMCPMC10264150
OpenAlexW4379768042

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.