Evidence map›Paper›PMID 42087798›Full record

SynthesisEpidemiology and infection2026

Serial cycle threshold to assess the infectious potential of SARS-CoV-2: A systematic review.

Elena Cecilia Rosca, Jason Oke, Tom Jefferson, Jon Brassey, Igho Onakpoya, Annette Plüddemann, Sara Gandini, Susanna Maltoni, David Evans, John Conly and 1 more

Abstract readSystematic ReviewMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Epidemiology and infection, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Elena Cecilia RoscaVictor Babes University of Medicine and Pharmacy, Timisoara, Romania.ORCID https://orcid.org/0000-0003-2412-1942
Jason OkeCentre for Evidence-Based Medicine, University of Oxford, UK.
Tom JeffersonDepartment for Continuing Education, University of Oxford, UK.
Jon BrasseyTrip Database Ltd, Newport, UK.
Igho OnakpoyaDepartment for Continuing Education, University of Oxford, UK.
Annette PlüddemannCentre for Evidence-Based Medicine, University of Oxford, UK.
Sara GandiniDepartment of Experimental Oncology, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.ORCID https://orcid.org/0000-0002-1348-4548
Susanna MaltoniClinical Trial Centre Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy.
David EvansLi Ka Shing Institute of Virology and Dept. of Medical Microbiology & Immunology, University of Alberta, Canada.
John ConlyDepartments of Medicine, Microbiology, Immunology & Infectious Diseases, and Pathology & Laboratory Medicine, Synder Institute for Chronic Diseases and O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, Canada.
Carl HeneghanCentre for Evidence-Based Medicine, University of Oxford, UK.

Funding

University of Calgary
6 · The paper itself

Abstract

We sought to assess predictive factors for SARS-CoV-2 infectiousness using a meta-analytic approach. We searched LitCovid, medRxiv, Google Scholar, and the WHO COVID-19 database until June 30 2025, including studies which cultured SARS-CoV-2, relating them to clinico-epidemiologic and laboratory variables and RT-PCR cycle threshold (Ct) values. Using linear mixed-effects regression models, we tested for independent associations with Ct values with 95%CIs and adjusted

Indexed as

COVID-19SARS-CoV-2HumansCOVID-19cycle thresholdinfectiousnessmonitoringSARS-CoV-2transmission

Identifiers

PMID42087798
PMCPMC13366375

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.