Evidence map›Paper›PMID 35820854›Full record

SynthesisBMC medical research methodology2022

Meta-analysis using Python: a hands-on tutorial.

Safoora Masoumi, Saeid Shahraz

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

Synthesis in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 9 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

13 citing papers in PubMed, 9 syntheses or guidelines pooled it.

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  6. Preventive clipping versus coiling in unruptured intracranial aneurysms: A comprehensive meta-analysis and systematic review to explore safety and efficacy.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Pooled it
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  13. Knowledge in Motion: A Comprehensive Review of Evidence-Based Human Kinetics.International journal of environmental research and public health · 2023
    Review
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

2 authors.

Safoora MasoumiPediatric Infectious Diseases Research Center, Mazandaran University of Medical Sciences, Boo- Ali Sina Hospital, Pasdaran Blvd, Sari, Mazandaran, 48158 38477, Iran. Safoora.Masoumi@mazums.ac.ir.ORCID 0000-0002-7343-1771
Saeid ShahrazInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeta-analysis is a central method for quality evidence generation. In particular, meta-analysis is gaining speedy momentum in the growing world of quantitative information. There are several software applications to process and output expected results. Open-source software applications generating such results are receiving more attention. This paper uses Python's capabilities to provide applicable instruction to perform a meta-analysis.

methodsWe used the PythonMeta package with several modifications to perform the meta-analysis on an open-access dataset from Cochrane. The analyses were complemented by employing Python's zEpid package capable of creating forest plots. Also, we developed Python scripts for contour-enhanced funnel plots to assess funnel plots asymmetry. Finally, we ran the analyses in R and STATA to check the cross-validity of the results.

resultsA stepwise instruction on installing the software and packages and performing meta-analysis was provided. We shared the Python codes for meta-analysts to follow and generate the standard outputs. Our results were similar to those yielded by R and STATA.

conclusionWe successfully produced standard meta-analytic outputs using Python. This programming language has several flexibilities to improve the meta-analysis results even further.

Indexed as

Programming LanguagesSoftwareHumansPublicationsResearch DesignHaloperidolMeta-analysisPythonPythonMetaTutorialzEpid

Identifiers

PMID35820854
PMCPMC9275021

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.