Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

How good is your glucose control?

A Michael Albisser1, Rodolfo Alejandro, Luigi F Meneghini

  • 1Bioengineering Department, University of California San Diego, La Jolla, California, USA. albisser@NIDM.org

Diabetes Technology & Therapeutics
|January 3, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Corrigendum to Correction of diabetes mellitus by transplanting minimal mass of syngeneic islets into vascularized small intestinal segment American Journal of Transplantation. Volume 13, Issue 10, October 2013, Pages 2550-2557.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons·2026
Same author

Optimizing 3D-printed Scaffold Geometry Decreases Foreign Body Response and Enhances Allogeneic Islet Transplant Outcomes.

bioRxiv : the preprint server for biology·2026
Same author

Pancreatic Islet Transplantation in Extrahepatic Sites: Evaluation of the Venous Sac in Large Mammal Models.

Diabetes & metabolism journal·2025
Same author

Combined Use of Vitamin D and DPP-4 Inhibitors as a Potential Adjuvant Treatment Strategy to Enhance the Efficacy of Novel Beta-Cell Replacement Therapies for Type 1 Diabetes.

Medical sciences (Basel, Switzerland)·2025
Same author

Choosing the right calcium channel blocker for patients with hypertension and proteinuric chronic kidney disease.

Current medical research and opinion·2025
Same author

Pancreatic β-cell regeneration in situ by the ALK3 agonist THR-123.

Nature communications·2025
Same journal

Continuous Glucose Monitoring Metrics and Perinatal Outcomes in Pregnant Women with Type 2 Diabetes.

Diabetes technology & therapeutics·2026
Same journal

Invited Commentary: Using Large Clinical Databases.

Diabetes technology & therapeutics·2026
Same journal

Impact of Technology Introduction on Glycemic Control of People Living with Type 1 Diabetes in Belgium: An Observational, Real-World Study.

Diabetes technology & therapeutics·2026
Same journal

Differences in Achieving Stringent Glycemic Targets Among Youth with Type 1 Diabetes: A SWEET Registry Study.

Diabetes technology & therapeutics·2026
Same journal

<i>Letter:</i> "Nocturnal Hypoglycemia: Characterization with Continuous Glucose Monitoring in a Real-World Setting".

Diabetes technology & therapeutics·2026
Same journal

Transient Benign Ketosis Is Common in Type 1 Diabetes During Very-Low Carbohydrate States: Novel Data from Continuous Ketone Sensor.

Diabetes technology & therapeutics·2026
See all related articles

A novel lag plot visually assesses glycemic control in diabetes management, offering a clearer performance measure than A1c or self-monitoring of blood glucose. This tool aids patients and providers in optimizing diabetes care and interventions.

Area of Science:

  • Diabetes Management
  • Medical Informatics
  • Statistical Analysis

Background:

  • Effective glycemic control is crucial for diabetes management and overall health.
  • Current performance measures like A1c and self-monitoring of blood glucose (SMBG) have limitations.
  • A need exists for a comprehensive, visual measure of diabetes management performance.

Purpose of the Study:

  • To adapt a statistical graphical method, the lag plot, as a visual tool for assessing glycemic control.
  • To create a method utilizing SMBG data for evaluating diabetes management performance.

Main Methods:

  • Adapted a statistical lag plot for analyzing self-monitoring of blood glucose (SMBG) data.
  • Developed a process to retrieve, process, format, and plot SMBG data visually.

Related Experiment Videos

  • Generated lag plots to characterize glucose control performance over user-selectable periods (days to months).

    • Main Results:

    • Illustrated clinical application of lag plots across diverse diabetes cases, from healthy individuals to islet cell transplant recipients.
    • Demonstrated visual comparisons before and after interventions, highlighting impacts on hypoglycemia and glycemic variability.
    • Quantified statistical significance of observed changes in glycemic control.

    Conclusions:

    • The lag plot provides a simple, visual method for assessing glycemic control.
    • Empowers patients and providers to identify issues, take action, and evaluate interventions.
    • Facilitates proactive diabetes management and helps rule out ineffective treatments.