Evidence map›Paper›PMID 42012592›Full record

ReviewDiabetes therapy : research, treatment and education of diabetes and related disorders2026

Technology in Diabetes: A Year in Review.

Subhankar Chatterjee, Subhodip Pramanik, Nitin Kapoor, Sanjay Kalra

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Diabetes therapy : research, treatment and education of diabetes and related disorders, 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.

Subhankar ChatterjeeDepartment of Endocrinology and Metabolism, Medical College and Hospital, Kolkata, West Bengal, India.ORCID http://orcid.org/0000-0002-3555-4412
Subhodip PramanikDepartment of Endocrinology, Neotia Getwel Multispecialty Hospital, Siliguri, West Bengal, India.ORCID http://orcid.org/0000-0002-3196-1192
Nitin KapoorUnit-I, Department of Endocrinology, Christian Medical College, Vellore, Tamil Nadu, India.ORCID http://orcid.org/0000-0002-9520-2072
Sanjay KalraDepartment of Endocrinology, Bharti Hospital, Karnal, Haryana, India. brideknl@gmail.com.ORCID http://orcid.org/0000-0003-1308-121X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The past year has continued the rapid evolution of diabetes technology across the monitoring, delivery, analytics, and patient-support domains. Improvements in continuous glucose monitoring (CGM) accuracy and wear-time options, widening use and regulatory expansion of automated insulin delivery (AID) systems, growth in connected insulin pens, maturation of digital therapeutics, and an influx of artificial intelligence (AI)-driven decision support tools have together shifted diabetes care toward tighter, more personalized, and more remote models of management. At the same time, device safety events, persistent affordability and access gaps, and data-interoperability and privacy challenges remind clinicians and policymakers that technology alone is not a panacea. This review summarizes the most important developments from last year (2025), highlights evidence from recent trials and regulatory actions, and discusses implications for practice and future directions.

Indexed as

Artificial intelligenceAutomated insulin deliveryContinuous glucose monitoring systemDiabetes technologyDigital therapeuticsSmart insulin pen

Identifiers

PMID42012592
PMCPMC13253910

What Socratic 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 Socratic graph.