Evidence map›Paper›PMID 42627545›Full record

ReviewInnere Medizin (Heidelberg, Germany)2026

[Continuous glucose monitoring and automated insulin dosing systems in clinical routine].

Annie Mathew, Dagmar Führer

Abstract readEnglish AbstractReview
PubMed Publisher
In one paragraph

Review in Innere Medizin (Heidelberg, Germany), 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

2 authors.

Annie MathewKlinik für Endokrinologie, Diabetologie und Stoffwechsel, Diabetes Exzellenzzentrum DDG, Ernährungsmedizinische Schwerpunktabteilung NutriZert, Universitätsklinikum Essen, Essen, Deutschland. annie.mathew@uk-essen.de.
Dagmar FührerKlinik für Endokrinologie, Diabetologie und Stoffwechsel, Diabetes Exzellenzzentrum DDG, Ernährungsmedizinische Schwerpunktabteilung NutriZert, Universitätsklinikum Essen, Essen, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundContinuous glucose monitoring (CGM), connected insulin pens, insulin pumps, and automated insulin delivery (AID) systems enable increasingly data-driven and partially automated diabetes management.

objectiveA practice-oriented evaluation of the indications, clinical benefits, and safety of modern diabetes technologies. MATERIALS AND

methodsAn analysis of current guidelines, position papers, randomized controlled trials, meta-analyses, and selected real-world data. RESULTS AND

conclusionDiabetes technologies should be offered according to individual needs, abilities, preferences, and life circumstances and, when appropriate, implemented early, including at the time of diagnosis. CGM supports diabetes treatment in individuals receiving insulin therapy, those at significant risk of hypoglycemia, and clinical situations in which CGM data improve clinical decision-making. Connected insulin pens facilitate the documentation and combined review of glucose and insulin data. AID systems are preferred for individuals with type 1 diabetes and also represent an effective therapeutic option for those with type 2 diabetes receiving intensive insulin therapy. Regular training, standardized data review, and a back-up plan are required. Patients may continue using their own diabetes devices in the hospital when clinically appropriate and institutional processes are in place. Future developments aim to reduce user burden, improve interoperability, and increase time in range (TIR).

Indexed as

Insulin pump therapyIntensive insulin therapySmart insulin pensType 1 Diabetes mellitusType 2 Diabetes mellitus

Identifiers

PMID42627545

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.