Evidence map›Paper›PMID 24876592›Full record

ReviewJournal of diabetes science and technology2014

Current Trends in Continuous Glucose Monitoring.

Volker Lodwig, Bernhard Kulzer, Oliver Schnell, Lutz Heinemann

Open access · bronzeAbstract readReview
In one paragraph

Review in Journal of diabetes science and technology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
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

12 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. SPECTRUM.Journal of diabetes science and technology · 2017
    Article
  9. Article
  10. Designing an artificial pancreas architecture: the AP@home experience.Medical & biological engineering & computing · 2015
    Article
  11. Routine use of continuous glucose monitoring in 10 501 people with diabetes mellitus.Diabetic medicine : a journal of the British Diabetic Association · 2015
    Article
  12. Article
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 at 3 institutions in 1 country.

Volker LodwigRoche Diagnostics, Mannheim, Germany.
Bernhard KulzerDiabetesklinik Bad Mergentheim, Bad Mergentheim, Germany.
Oliver SchnellForschergruppe Diabetes e.v. at the Helmholtz Center, Munich, Germany.
Lutz HeinemannScience & Co, Düsseldorf, Germany lutz.heinemann@profil.com.
German Diabetes Center Mergentheim · DEHelmholtz Zentrum München · DERoche Pharma AG (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The market introduction of systems for continuous glucose monitoring (CGM) some 15 years ago did not immediately revolutionize the treatment of diabetes; however, for a given group of patients, it would almost be inconceivable nowadays to imagine life without CGM. One day the development of insulin pumps together with CGM could culminate in an artificial pancreas system. The performance of the glucose sensors used for glucose measurement in the interstitial fluid in the subcutaneous tissue and the algorithms employed to analyze these data have improved so much over the past decade that current CGM systems by far outperform those of the first generations. This commentary discusses a number of aspects about what we have learned since CGM systems entered the market and what current trends exist in their usage. Some of these are major hurdles facing a more widespread usage of CGM.

Indexed as

artificial pancreascontinuous glucose monitoringdiabetes therapyglucose sensorshypoglycemiaquality of life

Identifiers

PMID24876592
PMCPMC4455393
OpenAlexW2149990120

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.