ReviewDiabetes technology & therapeutics2020
A Review of Continuous Glucose Monitoring-Based Composite Metrics for Glycemic Control.
Review in Diabetes technology & therapeutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03508934 (Continuous Glucose Monitoring in Insulin Treated Hospitalized Veterans With DM2 at Higher Risk for Hypoglycemia), which is not on this map. Cited by 27 papers.
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.
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.
Continuous Glucose Monitoring in Insulin Treated Hospitalized Veterans With DM2 at Higher Risk for Hypoglycemia
Who cites it
27 citing papers in PubMed, 49 citations in OpenAlex.
- Effect of continuous glucose monitoring compared with self-monitoring of blood glucose in gestational diabetes patients with HbA1c<6%: a randomized controlled trial.Frontiers in endocrinology · 2023Trial
- The Evolving Landscape of Continuous Glucose Monitoring Metrics in Type 1 Diabetes: Narrative Literature Review.JMIR diabetes · 2026Review
- Advances in diabetes technology: clinical implications, limitations, and future perspectives.Hormones (Athens, Greece) · 2026Review
- Defining a glycemic persistence index (GPI) for continuous glucose monitoring.Research square · 2026Article
- A deep learning-derived digital biomarker of dysglycemia and its association with genetic risk of type 2 diabetes.npj metabolic health and disease · 2025Article
- Continuous Glucose Monitoring Data Analysis 2.0: Functional Data Pattern Recognition and Artificial Intelligence Applications.Journal of diabetes science and technology · 2025Article
- Glucodensity functional profiles outperform traditional continuous glucose monitoring metrics.Scientific reports · 2025Article
- Glucostats: an efficient Python library for glucose time series feature extraction and visual analysis.BMC bioinformatics · 2025Article
- Noninvasive Glucose Measurements in Tissue Simulating Phantoms Using a Solid-State Near-Infrared Sensor.Sensors (Basel, Switzerland) · 2025Article
- Parameters of glycemic variability in continuous glucose monitoring as predictors of diabetes: a prospective evaluation in a non-diabetic general population.Advances in laboratory medicine · 2025Article
- Article
- Editorial: Continuous glucose monitoring: beyond diabetes management.Frontiers in endocrinology · 2025Article
- Development of a three-dimensional scoring model for the assessment of continuous glucose monitoring data in type 1 diabetes.BMJ open diabetes research & care · 2024Article
- Impact of Continuous Glucose Monitoring and its Glucometrics in Clinical Practice in Spain and Future Perspectives: A Narrative Review.Advances in therapy · 2024Review
- A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings.Journal of diabetes science and technology · 2023Article
- CGM Metrics Identify Dysglycemic States in Participants From the TrialNet Pathway to Prevention Study.Diabetes care · 2023Article
- The Need for Data Standards and Implementation Policies to Integrate CGM Data into the Electronic Health Record.Journal of diabetes science and technology · 2023Review
- The Use of Extreme Value Statistics to Characterize Blood Glucose Curves and Patient Level Risk Assessment of Patients With Type I Diabetes.Journal of diabetes science and technology · 2023Article
- Investigating the value of glucodensity analysis of continuous glucose monitoring data in type 1 diabetes: an exploratory analysis.Frontiers in clinical diabetes and healthcare · 2023Article
- Selenium-based nanomaterials for biosensing applications.Materials advances · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
We performed a literature review of composite metrics for describing the quality of glycemic control, as measured by continuous glucose monitors (CGMs). Nine composite metrics that describe CGM data were identified. They are described in detail along with their advantages and disadvantages. The primary benefit to using composite metrics in clinical practice is to be able to quickly evaluate a patient's glycemic control in the form of a single number that accounts for multiple dimensions of glycemic control. Very little data exist about (1) how to select the optimal components of composite metrics for CGM; (2) how to best score individual components of composite metrics; and (3) how to correlate composite metric scores with empiric outcomes. Nevertheless, composite metrics are an attractive type of scoring system to present clinicians with a single number that accounts for many dimensions of their patients' glycemia. If a busy health care professional is looking for a single-number summary statistic to describe glucose levels monitored by a CGM, then a composite metric has many attractive features.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.