Evidence map›Paper›PMID 26330485›Full record

ArticleJournal of diabetes science and technology2015

Performance Comparison of CGM Systems: MARD Values Are Not Always a Reliable Indicator of CGM System Accuracy.

Harald Kirchsteiger, Lutz Heinemann, Guido Freckmann, Volker Lodwig, Günther Schmelzeisen-Redeker, Michael Schoemaker, Luigi Del Re

Abstract readComparative Study
In one paragraph

Article in Journal of diabetes science and technology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Optimizing Continuous Glucose Monitoring Adoption in India: From Current Challenges to Future Solutions.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Monitoring of Pediatric Type 1 Diabetes.Frontiers in endocrinology · 2020
    Review
  17. Article
  18. Article
  19. Review
  20. 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

7 authors.

Harald KirchsteigerInstitute for Design and Control of Mechatronical Systems, Johannes Kepler University, Linz, Austria harald.kirchsteiger@jku.at.
Lutz HeinemannScience & Co, Düsseldorf, Germany.
Guido FreckmannInstitute for Diabetes-Technology GmbH, at Ulm University, Ulm, Germany.
Volker LodwigRoche Diagnostics GmbH, Mannheim, Germany.
Günther Schmelzeisen-RedekerRoche Diagnostics GmbH, Mannheim, Germany.
Michael SchoemakerRoche Diagnostics GmbH, Mannheim, Germany.
Luigi Del ReInstitute for Design and Control of Mechatronical Systems, Johannes Kepler University, Linz, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe ongoing progress of continuous glucose monitoring (CGM) systems results in an increasing interest in comparing their performance, in particular in terms of accuracy, that is, matching CGM readings with reference values measured at the same time. Most often accuracy is evaluated by the mean absolute relative difference (MARD). It is frequently overseen that MARD does not only reflect accuracy, but also the study protocol and evaluation procedure, making a cross-study comparison problematic.

methodsWe evaluate the effect of several factors on the MARD statistical properties: number of paired reference and CGM values, distribution of the paired values, accuracy of the reference measurement device itself and the time delay between data pairs. All analysis is done using clinical data from 12 patients wearing 6 sensors each.

resultsWe have found that a few paired points can have a potentially high impact on MARD. Leaving out those points for evaluation thus reduces the MARD. Similarly, accuracy of the reference measurements greatly affects the MARD as numerical and graphical data show. Results also show that a log-normal distribution of the paired references provides a significantly different MARD than, for example, a uniform distribution.

conclusionsMARD is a reasonable parameter to characterize the performance of CGM systems when keeping its limitations in mind. To support clinicians and patients in selecting which CGM system to use in a clinical setting, care should be taken to make MARD more comparable by employing a standardized evaluation procedure.

Indexed as

Biosensing TechniquesBlood GlucoseBlood Glucose Self-MonitoringDiabetes Mellitus, Type 1HumansMaterials TestingReproducibility of ResultsBlood GlucoseaccuracyCGMcontinuous glucose monitoringMARDperformance comparisonperformance evaluationprecision

Identifiers

PMID26330485
PMCPMC4667347

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.