ArticleJournal of diabetes science and technology2009
Display of glucose distributions by date, time of day, and day of week: new and improved methods.
Article in Journal of diabetes science and technology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Self-adjustment of insulin dose using graphically depicted self-monitoring of blood glucose measurements in patients with type 1 diabetes mellitus.Journal of diabetes science and technology · 2013Trial
- Glucose360: An Open-Source Python Platform with Event-Based Integration for Continuous Glucose Monitoring Data Analysis.Diabetes technology & therapeutics · 2026Article
- Comprehensive blood glucose level prediction from HbAScientific reports · 2026Article
- Relationship Between Moderate-to-Vigorous Physical Activity and Glycemia Among Young Adults with Type 1 Diabetes and Overweight or Obesity: Results from the Advancing Care for Type 1 Diabetes and Obesity Network (ACT1ON) Study.Diabetes technology & therapeutics · 2022Article
- Diabetes Technology Meeting 2021.Journal of diabetes science and technology · 2022Article
- More Green, Less Red: How Color Standardization May Facilitate Effective Use of CGM Data.Journal of diabetes science and technology · 2022Article
- Interpreting blood GLUcose data with R package iglu.PloS one · 2021Article
- Comparison of the effects of lockdown due to COVID-19 on glucose patterns among children, adolescents, and adults with type 1 diabetes: CGM study.BMJ open diabetes research & care · 2020Article
- Positioning time in range in diabetes management.Diabetologia · 2020Review
- How Knowledge Emerges From Artificial Intelligence Algorithm and Data Visualization for Diabetes Management.Journal of diabetes science and technology · 2019Article
- New Paradigm of Personalized Glycemic Control Using Glucose Temporal Density Histograms.Journal of diabetes science and technology · 2019Article
- The Relationships Between Time in Range, Hyperglycemia Metrics, and HbA1c.Journal of diabetes science and technology · 2019Article
- Evaluating quality of glycemic control: graphical displays of hypo- and hyperglycemia, time in target range, and mean glucose.Journal of diabetes science and technology · 2015Article
- Approaches to display of multiple-point glucose profiles: A UK patient's perspective.Journal of diabetes science and technology · 2014Review
- Consensus report: the current role of self-monitoring of blood glucose in non-insulin-treated type 2 diabetes.Journal of diabetes science and technology · 2011Article
- Design of a decision support system to help clinicians manage glycemia in patients with type 2 diabetes mellitus.Journal of diabetes science and technology · 2011Article
- A semilogarithmic scale for glucose provides a balanced view of hyperglycemia and hypoglycemia.Journal of diabetes science and technology · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThere is a need for improved methods for display of glucose distributions to facilitate comparisons by date, time of day, day of the week, and other variables for data obtained using self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM).
methodStacked bar charts are utilized for multiple ranges of glucose values, e.g., very low, low, borderline low, target range, borderline high, high, and very high. Glucose ranges for these categories can be defined by the user, e.g., <40, 40-70, 71-80, 81-140, 141-180, 181-250, and 251-400 mg/dl. Glucose distributions can be displayed by time of day, in relation to meals, by date, or by day of week. The graphic display can be generated using general purpose spreadsheet software such as Microsoft Excel or with special purpose software.
resultStacked bar charts are extremely compact and effective. They facilitate comparison of multiple days, multiple time segments within a day, preprandial and postprandial glucose levels, days of the week, treatment periods, patients, and groups of patients. They are superior to use of pie charts in terms of compactness and in their ability to facilitate comparisons using multiple criteria and multiple subsets of the data. One can identify episodes of hypoglycemia and hyperglycemia and can display standard errors of estimates of percentages. Interpretation of these graphs is readily learned and requires minimal training.
conclusionUse of stacked bar charts is generally superior to use of pie charts for display of glucose distributions and can potentially facilitate the analysis and interpretation of SMBG and CGM data.
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.