Evidence map›Paper›PMID 35071686›Full record

ArticleOpen forum infectious diseases2022

Ivermectin for COVID-19: Addressing Potential Bias and Medical Fraud.

Andrew Hill, Manya Mirchandani, Victoria Pilkington

Abstract read
In one paragraph

Article in Open forum infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 5 pooled it
–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

30 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Trial
  7. The effect of ivermectin on the viral load and culture viability in early treatment of nonhospitalized patients with mild COVID-19 - a double-blind, randomized placebo-controlled trial.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
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  15. Assessing the Integrity of Clinical Trials Included in Evidence Syntheses.International journal of environmental research and public health · 2023
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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

3 authors.

Andrew HillDepartment of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK.
Manya MirchandaniFaculty of Medicine, Imperial College London, London, UK.
Victoria PilkingtonOxford University Clinical Academic Graduate School, University of Oxford, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ivermectin has become a controversial potential medicine for coronavirus disease 2019. Some early studies suggested clinical benefits in treatment of infection. However, the body of evidence includes studies of varying quality. Furthermore, some trials have now been identified as potentially fraudulent. We present a subgroup meta-analysis to assess the effects of stratifying by trial quality on the overall results. The stratification is based on the Cochrane Risk of Bias measures and raw data analysis where possible. The results suggest that the significant effect of ivermectin on survival was dependent on largely poor-quality studies. According to the potentially fraudulent study (risk ratio [RR], 0.08; 95% CI, 0.02-0.35), ivermectin improved survival ~12 times more in comparison with low-risk studies (RR, 0.96; 95% CI, 0.56-1.66). This highlights the need for rigorous quality assessments, for authors to share patient-level data, and for efforts to avoid publication bias for registered studies. These steps are vital to facilitate accurate conclusions on clinical treatments.

Indexed as

COVID-19ivermectinSARS-CoV-2

Identifiers

PMID35071686
PMCPMC8774052

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.