Evidence map›Paper›PMID 41343539›Full record

ArticlePLoS medicine2025

Setting the standard for high-quality studies using open health datasets.

Andreia Cunha, Suzanne de Bruijn, Alison Farrell, Helen Lumbard, Alexandra Tosun, Daniel Routledge

Abstract readEditorial
In one paragraph

Article in PLoS medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Andreia CunhaPublic Library of Science, Cambridge, United Kingdom.ORCID https://orcid.org/0009-0001-4072-173X
Suzanne de BruijnPublic Library of Science, Cambridge, United Kingdom.
Alison FarrellPublic Library of Science, San Francisco, United States of America.
Helen LumbardPublic Library of Science, Cambridge, United Kingdom.
Alexandra TosunPublic Library of Science, Berlin, Germany.
Daniel RoutledgePublic Library of Science, Cambridge, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large open health datasets present unique opportunities for studies that when well-designed, conducted, and reported, can offer valuable contributions to health and medicine. However, recent years have seen a concerning proliferation of analyses lacking robust or novel findings. In this Editorial, we provide guidance to authors for conducting and reporting high-quality secondary analyses using these datasets.

Indexed as

Databases, FactualDatasets as TopicResearch DesignHumans

Identifiers

PMID41343539
PMCPMC12677557

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.