ArticleJournal of diabetes science and technology2023
Optimal Data Collection Period for Continuous Glucose Monitoring to Assess Long-Term Glycemic Control: Revisited.
Article in Journal of diabetes science and technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- The impact of frailty on glycaemic control in older adults with type 1 diabetes: An observational study.Diabetic medicine : a journal of the British Diabetic Association · 2026Observational
- The Relationship between Hemoglobin A1c and the Glucose Management Indicator and Glucose Metrics in Children and Adolescents with Type 1 Diabetes Mellitus Using Automated Insulin Delivery SystemsJournal of clinical research in pediatric endocrinology · 2026Observational
- Psychological Aspects and Implications of Food Addiction and Glucose Control in Type 2 Diabetes: A Pilot Mixed-Methods Study.Healthcare (Basel, Switzerland) · 2026Article
- The Relationship Between Clinical Profiles, Glycemic Parameters, and Hypoglycemia in Pediatric Patients with Type 1 Diabetes.Journal of clinical medicine · 2026Article
- A Longitudinal Multimodal Dataset of Type 1 Diabetes.Scientific data · 2025Article
- Associations Between HbA1c and Glucose Time in Range Using Continuous Glucose Monitoring in Type 1 Diabetes: Cross-Sectional Population-Based Study.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2024Article
- Best practices in collecting and reporting continuous glucose monitoring data in research settings.Nature metabolism · 2024Article
- Time in range and complications of diabetes: a cross-sectional analysis of patients with Type 1 diabetes.Diabetology & metabolic syndrome · 2023Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveIt is not clear how the short-term continuous glucose monitoring (CGM) sampling time could influence the bias in estimating long-term glycemic control. A large bias could, in the worst case, lead to incorrect classification of patients achieving glycemic targets, nonoptimal treatment, and false conclusions about the effect of new treatments. This study sought to investigate the relation between sampling time and bias in the estimates.
methodsWe included a total of 329 type 1 patients (age 14-86 years) with long-term CGM (90 days) data from three studies. The analysis calculated the bias from estimating long-term glycemic control based on short-term sampling. Time in range (TIR), time above range (TAR), time below range (TBR), correlation, and glycemic target classification accuracy were assessed.
resultsA sampling time of ten days is associated with a high bias of 10% to 47%, which can be reduced to 4.9% to 26.4% if a sampling time of 30 days is used (
conclusionsOur results suggest that the proposed 10-14 day CGM sampling time may be associated with a high correlation with three-month CGM. However, these estimates are subject to large intersubject bias, which is clinically relevant. Clinicians and researchers should consider using assessments of longer durations of CGM data if possible, especially when assessing time in hypoglycemia or while testing a new treatment.
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