Evidence map›Paper›PMID 37603158›Full record

ReviewInflammopharmacology2023

Ibuprofen, other NSAIDs and COVID-19: a narrative review.

William Laughey, Imran Lodhi, Graham Pennick, Lucinda Smart, Olutoba Sanni, Suneet Sandhu, Bruce Charlesworth

Open access · hybridAbstract readReview
In one paragraph

Review in Inflammopharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

14 citing papers in PubMed, 21 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

7 authors at 1 institution in 1 country.

William LaugheyReckitt Health Care UK Ltd, Hull, UK. bill.laughey@reckitt.com.ORCID http://orcid.org/0000-0003-4076-2299
Imran LodhiReckitt Health Care UK Ltd, Hull, UK.
Graham PennickReckitt Health Care UK Ltd, Hull, UK.
Lucinda SmartReckitt Health Care UK Ltd, Hull, UK.
Olutoba SanniReckitt Health Care UK Ltd, Hull, UK.
Suneet SandhuReckitt Health Care UK Ltd, Hull, UK.
Bruce CharlesworthReckitt Health Care UK Ltd, Hull, UK.
Care UK (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

At the start of the coronavirus disease 2019 (COVID-19) pandemic (March 2020), there was speculation that non-steroidal anti-inflammatory drugs (NSAIDs) such as ibuprofen, used to manage some of the symptoms of COVID-19, could increase the susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and negatively impact clinical outcomes. In the absence of any robust mechanistic and clinical evidence, this speculation led to confusion about the safety of ibuprofen, contributing to the so-called 'infodemic' surrounding COVID-19. A wealth of evidence has been generated in subsequent years, and this narrative review aims to consider the body of in vitro and in vivo research, observational studies, systematic reviews and meta-analyses on the use of NSAIDs, including ibuprofen, in COVID-19. Overall, the direction of evidence supports that NSAIDs do not increase susceptibility to infection, nor worsen disease outcomes in patients with COVID-19. Neither do they impact the immune response to COVID-19 vaccines. There is no basis to limit the use of NSAIDs, and doing so may deprive patients of effective self-care measures to control symptoms.

Indexed as

COVID-19IbuprofenAnti-Inflammatory Agents, Non-SteroidalCOVID-19 VaccinesHumansSARS-CoV-2Anti-Inflammatory Agents, Non-SteroidalCOVID-19 VaccinesIbuprofenCOVID-19IbuprofenNSAIDs

Identifiers

PMID37603158
PMCPMC10518289
OpenAlexW4386020007

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.