Evidence map›Paper›PMID 42661266›Full record

ArticleJournal of diabetes science and technology2026

ReplayBG-Web: A Novel Web Interface to Ease the Creation and Use of Digital Twins for Type 1 Diabetes.

Luca Cossu, Anna Ghiotto, Andrea Facchinetti, Giacomo Cappon

Abstract read
In one paragraph

Article in Journal of diabetes science and technology, 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

4 authors.

Luca CossuDepartment of Information Engineering, University of Padova, Italy.ORCID 0000-0002-8804-0722
Anna GhiottoDepartment of Information Engineering, University of Padova, Italy.
Andrea FacchinettiDepartment of Information Engineering, University of Padova, Italy.ORCID 0000-0001-8041-2280
Giacomo CapponDepartment of Information Engineering, University of Padova, Italy.ORCID 0000-0003-4358-9268

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReplayBG is a recently released tool that acts as a digital twin (DT) of individuals with type 1 diabetes, learning glucose-insulin dynamics from real-world data and enabling users to test the effect of different therapeutic actions. However, its adoption remains limited by the technical expertise required to operate it.

methodsTo lower this barrier, we developed ReplayBG-web, a web-based interface built on ReplayBG that allows any user, without programming skills, to upload standardized CSV files and automatically generate DTs.

resultsReplayBG-web enables users to interactively visualize original data and metrics, create new scenarios by modifying the dose and timing of insulin and meals, obtain the resulting alternative glucose profiles and related control metrics, and export results for downstream analysis.

conclusionsReplayBG-web represents a step forward in filling the gap between research, clinical practice, self-learning, and potentially education, making digital twin technology for type 1 diabetes accessible to a wider range of users.

Indexed as

digital healthdigital twinglucose controlno-code environmenttherapy simulationuser-centered design

Identifiers

PMID42661266
PMCPMC13522252

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.