Evidence map›Paper›PMID 30453761›Full record

ReviewJournal of diabetes science and technology2019

Measures of Accuracy for Continuous Glucose Monitoring and Blood Glucose Monitoring Devices.

Guido Freckmann, Stefan Pleus, Mike Grady, Steven Setford, Brian Levy

Open access · bronzeAbstract readReview
In one paragraph

Review in Journal of diabetes science and technology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
93citing papers in PubMed, 5 pooled it
4.7field-weighted citation impact, top 4% 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

93 citing papers in PubMed, 5 syntheses or guidelines pooled it, 182 citations in OpenAlex.

  1. Guideline
  2. Pooled it
  3. American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2022
    Guideline
  4. Pooled it
  5. Guideline
  6. Trial
  7. Trial
  8. Trial
  9. Article
  10. Article
  11. Review
  12. Review
  13. Review
  14. Review
  15. Letter to the Editor regarding "Accuracy and Reliability of the Sinocare iCan i3 Continuous Glucose Monitoring System".Diabetes therapy : research, treatment and education of diabetes and related disorders · 2026
    Article
  16. Review
  17. Review
  18. Article
  19. Article
  20. Artificial pancreas: the past and the future.Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs · 2025
    Review

33 more citing papers are in PubMed but not listed here.

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

5 authors at 1 institution in 1 country.

Guido Freckmann1 Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany.
Stefan Pleus1 Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany.ORCID 0000-0003-4629-7754
Mike Grady2 LifeScan Scotland Ltd, Inverness, Scotland, UK.
Steven Setford2 LifeScan Scotland Ltd, Inverness, Scotland, UK.
Brian Levy3 LifeScan Inc, Wayne, PA, USA.
Universität Ulm · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, patients with diabetes may choose between two major types of system for glucose measurement: blood glucose monitoring (BGM) systems measuring glucose within capillary blood and continuous glucose monitoring (CGM) systems measuring glucose within interstitial fluid. Although BGM and CGM systems offer different functionality, both types of system are intended to help users achieve improved glucose control. Another area in which BGM and CGM systems differ is measurement accuracy. In the literature, BGM system accuracy is assessed mainly according to ISO 15197:2013 accuracy requirements, whereas CGM accuracy has hitherto mainly been assessed by MARD, although often results from additional analyses such as bias analysis or error grid analysis are provided. The intention of this review is to provide a comparison of different approaches used to determine the accuracy of BGM and CGM systems and factors that should be considered when using these different measures of accuracy to make comparisons between the analytical performance (ie, accuracy) of BGM and CGM systems. In addition, real-world implications of accuracy and its relevance are discussed.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringDevice ApprovalDiabetes MellitusGuideline AdherenceHumansMedical Device LegislationReproducibility of ResultsSensitivity and SpecificityUnited StatesUnited States Food and Drug AdministrationBlood Glucoseaccuracyblood glucose monitoringcontinuous glucose monitoringISO 15197MARDperformance

Identifiers

PMID30453761
PMCPMC6501529
OpenAlexW2900697170

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.