Evidence mapPaperPMID 28748705Full record

Trial reportJournal of diabetes science and technology2018

The Comprehensive Glucose Pentagon: A Glucose-Centric Composite Metric for Assessing Glycemic Control in Persons With Diabetes.

Robert A Vigersky, John Shin, Boyi Jiang, Thorsten Siegmund, Chantal McMahon, Andreas Thomas

Open access · bronzeAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of diabetes science and technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.5field-weighted citation impact, top 6% 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

16 citing papers in PubMed, 42 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Observational
  6. Article
  7. Article
  8. Article
  9. Spousal Influence on Diabetes Self-care: Moderating Effects of Distress and Relationship Quality on Glycemic Control.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2021
    Observational
  10. Glycemic Status Assessment by the Latest Glucose Monitoring Technologies.International journal of molecular sciences · 2020
    Review
  11. Review
  12. Article
  13. Review
  14. Review
  15. Article
  16. Review
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

6 authors at 3 institutions in 2 countries.

Robert A Vigersky1 Medtronic Diabetes, Northridge, CA, USA.
John Shin1 Medtronic Diabetes, Northridge, CA, USA.
Boyi Jiang1 Medtronic Diabetes, Northridge, CA, USA.
Thorsten Siegmund3 Isar Klinikum, Munich, Germany.
Chantal McMahon1 Medtronic Diabetes, Northridge, CA, USA.
Andreas Thomas2 Medtronic GmbH, Meerbusch, Germany.
Medtronic (United States) · USKlinikum rechts der Isar · DEMedtronic (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComposite metrics have the potential to provide more complete and clinically useful information about glycemic control than traditional individual metrics such as hemoglobin A1C, %/time/area under curve of hypoglycemia and hyperglycemia.

methodsUsing five key metrics that are derived from continuous glucose monitoring, we developed a new, multicomponent composite metric, the Comprehensive Glucose Pentagon (CGP) that demonstrates glycemic control both numerically and visually. Two of its axes are composite metrics-the intensity of hypoglycemia and intensity of hyperglycemia. This approach eliminates the use of the surrogate marker, hemoglobin A1C (A1C), and replaces it with glucose-centric metrics.

resultsWe reanalyzed the data from two randomized control trials, the STAR 3 and ASPIRE In-Home studies using the CGP. It provided new insights into the effect of sensor-augmented pumping (SAP) in the STAR 3 trial and sensor-integrated pumping with low-glucose threshold suspend (SIP+TS) in the ASPIRE In-Home trial.

conclusionsThe CGP has the potential to enable health care providers, investigators and patients to better understand the components of glycemic control and the effect of various interventions on the individual elements of that control. This can be done on a daily, weekly, or monthly basis. It also allows direct comparison of the effects on different interventions among clinical trials which is not possible using A1C alone. This new composite metric approach requires validation to determine if it provides a better predictor of long-term outcomes than A1C and/or better predictor of severe hypoglycemia than the low blood glucose index (LBGI).

Indexed as

Blood Glucose Self-MonitoringAlgorithmsBlood GlucoseDiabetes MellitusGlycated HemoglobinHumansHypoglycemic AgentsInsulinBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanHypoglycemic AgentsInsulincomposite metricscontinuous glucose monitoringglycemic controlhemoglobin A1Chypoglycemia

Identifiers

PMID28748705
PMCPMC5761978
OpenAlexW2740263795

What Socratic 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 Socratic graph.