Author
Listed:
- Natalie Daya Malek
(Bloomberg School of Public Health, Johns Hopkins University)
- Dan Wang
(Bloomberg School of Public Health, Johns Hopkins University)
- Sui Zhang
(Bloomberg School of Public Health, Johns Hopkins University)
- Michael Fang
(Bloomberg School of Public Health, Johns Hopkins University)
- Amelia Wallace
(Bloomberg School of Public Health, Johns Hopkins University)
- Scott Zeger
(Bloomberg School of Public Health, Johns Hopkins University)
- Elizabeth Selvin
(Bloomberg School of Public Health, Johns Hopkins University)
Abstract
In this article, we present the cgmstats command, which analyzes continuous glucose monitoring (CGM) data. The use of wearable CGMs is growing rapidly. The latest generation of CGM systems does not require fingerstick calibration, is minimally invasive, and is frequently used in research studies. CGM sensors are typically worn for up to 2 weeks and record interstitial glucose measurements every minute to every 15 minutes, depending on the sensor used. CGM systems generate hundreds of measurements per day and thousands of measurements in one person over a single wear. There is a need for tools that allow researchers to efficiently organize and summarize the wealth of data on glucose patterns produced by CGM systems. The cgmstats command generates CGM summary measures for data from various CGM systems and allows the user to flexibly define ranges and generate data visualizations. In this article, we provide an overview of the cgmstats command and examples of its use. The cgmstats command supports rigorous and reproducible analyses of CGM data.
Suggested Citation
Natalie Daya Malek & Dan Wang & Sui Zhang & Michael Fang & Amelia Wallace & Scott Zeger & Elizabeth Selvin, 2026.
"Summarizing data from continuous glucose monitors using the cgmstats command,"
Stata Journal, StataCorp LLC, vol. 26(2), pages 274-290, June.
Handle:
RePEc:tsj:stataj:v:26:y:2026:i:2:p:274-290
DOI: 10.1177/1536867X261450271
Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj26-2/st0804/
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