Evidence map›Paper›PMID 42430025›Full record

ReviewCurrent diabetes reports2026

Digital Management of Early-Onset Type 2 Diabetes: Empowerment, Challenges, and Future Outlook.

Li-Jun Guo, Kah-Seng Low, Sok-Kun Tae, Lee-Ling Lim

Abstract readReview
In one paragraph

Review in Current diabetes reports, 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.

Li-Jun GuoDepartment of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, 50603, Malaysia.
Kah-Seng LowDepartment of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, 50603, Malaysia.
Sok-Kun TaeDepartment of Pediatrics, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, 50603, Malaysia. taesokkun@um.edu.my.
Lee-Ling LimDepartment of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, 50603, Malaysia. limleeling@um.edu.my.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewEarly-onset type 2 diabetes (EOT2D), defined as a diabetes diagnosis before 40 years of age, is rising globally and associated with an aggressive disease course and early complications. This review examines the role of digital health technologies (DHT) in addressing the unique clinical and life-course challenges of EOT2D. RECENT

findingsDHT, including continuous glucose monitoring, mobile health applications, digital therapeutics, telemedicine, remote patient monitoring, wearable devices, and artificial intelligence-based analytics, have demonstrated modest improvements in glycemic control, weight management, and patient engagement in people with type 2 diabetes. However, evidence in adults with EOT2D remains limited. Compared with usual-onset T2D, people with EOT2D may derive particular benefits due to higher digital literacy, greater lifestyle variability, and longer anticipated disease duration. Although DHT shows promise for improving empowerment and care integration in EOT2D, important gaps persist, including a lack of EOT2D-specific trials, digital divide-related inequities, interoperability challenges, and reimbursement barriers. Future research should prioritize tailored interventions and hybrid care models to optimize long-term outcomes in this high-risk population.

Indexed as

Diabetes Mellitus, Type 2Age of OnsetBlood Glucose Self-MonitoringContinuous Glucose MonitoringDigital HealthHumansRemote Patient MonitoringTelemedicineArtificial IntelligenceContinuous Glucose MonitoringDigital HealthDigital TherapeuticsEarly-Onset Type 2 DiabetesEmpowerment

Identifiers

PMID42430025
PMCPMC13354610

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.