Evidence map›Paper›PMID 31998381›Full record

ArticleInternational journal of endocrinology and metabolism2019

Data Extraction from Graphs Using Adobe Photoshop: Applications for Meta-Analyses.

Sevda Gheibi, Alireza Mahmoodzadeh, Khosrow Kashfi, Sajad Jeddi, Asghar Ghasemi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of endocrinology and metabolism, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 6 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

27 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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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

5 authors.

Sevda GheibiEndocrine Physiology Research Center, Research institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Alireza MahmoodzadehDepartment of Business Management, Kharazmi University, Tehran, Iran.
Khosrow KashfiDepartment of Molecular, Cellular and Biomedical Sciences, Sophie Davis School of Biomedical Education, School of Medicine, City University of New York, New York, United States.ORCID https://orcid.org/0000-0002-4060-7283
Sajad JeddiEndocrine Physiology Research Center, Research institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Asghar GhasemiEndocrine Physiology Research Center, Research institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0001-6867-2151

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Graphs, an effective form of data presentation, are used for summarizing complex information and making them easier to understand. Extracting numerical data from graphs, which is commonly required in systematic reviews and meta-analyses, is however a challenging issue. Since this kind of results presentation is common, ignorance of such data may result in publication bias when conducting meta-analyses. On the other hand, contacting the authors of a particular publication in order to retrieve the data may take a long time and is often not very fruitful. In this case, there are a few software and methods that may be used for data extraction; however, using these software is costly and not simple as well as different types of graphs need different extraction methods. Here, we have described a simple reproducible method for extracting data from graphs using Adobe Photoshop.

Indexed as

Adobe PhotoshopData ExtractionGraphMeta-Analysis.

Identifiers

PMID31998381
PMCPMC6942170

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.