Evidence map›Paper›PMID 42885326›Full record

SynthesisDiabetes/metabolism research and reviews2026

Real-World Databases in Diabetes: A Systematic Review.

Jonah J C Thomas, Anna Meffen, Alessandro Rizzi, Andrew P Kingsnorth, Beatrice Pieri, Ying He, Shirley Konnor, Clare Gillies, Kamlesh Khunti, Jonathan Valabhji and 6 more

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Diabetes/metabolism research and reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Jonah J C ThomasUniversity of Leicester, University Road, Leicester, UK.ORCID https://orcid.org/0000-0002-9886-0169
Anna MeffenUniversity of Leicester, University Road, Leicester, UK.ORCID https://orcid.org/0000-0002-9491-6110
Alessandro RizziUniversity of Leicester, University Road, Leicester, UK.ORCID https://orcid.org/0000-0002-8309-4051
Andrew P KingsnorthSchool of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK.
Beatrice PieriUniversity of Leicester, University Road, Leicester, UK.ORCID https://orcid.org/0000-0002-7062-9811
Ying HeDepartment of Mathematics and Statistics, University of Strathclyde, Glasgow, UK.
Shirley KonnorUniversity of Leicester, University Road, Leicester, UK.ORCID https://orcid.org/0009-0005-9707-3816
Clare GilliesUniversity of Leicester, University Road, Leicester, UK.ORCID https://orcid.org/0000-0002-8417-9700
Kamlesh KhuntiUniversity of Leicester, University Road, Leicester, UK.
Jonathan ValabhjiDepartment of Metabolism, Digestion & Reproduction, Faculty of Medicine, Imperial, London, UK.ORCID https://orcid.org/0000-0001-9756-4061
Shivani MisraDepartment of Metabolism, Digestion & Reproduction, Faculty of Medicine, Imperial, London, UK.
Amanda AdlerDiabetes Trials Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
Christian Torp-PedersenCopenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark.
Martina VettorettiDepartment of Information Engineering, University of Padova, Padova, Italy.ORCID https://orcid.org/0000-0002-5020-1818
Julia K MaderDivision of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria.ORCID https://orcid.org/0000-0001-7854-4233
Pratik ChoudharyUniversity of Leicester, University Road, Leicester, UK.

Funding

European Commission 101095556
6 · The paper itself

Abstract

aimTo identify publications that describe RWD databases in the field of diabetes and map their key characteristics.

methodsDatabases were searched (MEDLINE, SCOPUS, CINAHL from January 2018 to October 2025) to identify relevant publications describing RWD databases. Eligible studies were identified as RWD databases that contained more than 1000 adults and were followed up for one year or longer. Metadata including population, sample size, and outcomes were then extracted.

resultsA total of 610 eligible RWD databases were identified from 1779 included articles. Databases were identified in 74 countries, with the majority collected in Europe (n = 193). Only 22 databases were identified in lower- and- middle income countries (as defined by the World Bank). Demographics, prescription, diagnosis, and biochemical information were collected frequently; however, mortality and technology related variables (CGM usage) were found in fewer datasets. Very few databases were open access however 205 mentioned having the possibility for data sharing.

conclusionWe have produced an online dashboard to summarise the RWD databases available in the field of diabetes. We found many RWD databases globally that contain a range of variables related to individuals' health; however, lower- and middle-income nations are underrepresented within these data.

Indexed as

Databases, FactualDiabetes MellitusHumansdatabase characteristicsmeta datareal‐world evidence

Identifiers

PMID42885326
PMCPMC13673215

What OpenQuestion holds

Textmetadata
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.