Trial reportJournal of diabetes science and technology2013
Minding the gaps in continuous glucose monitoring: a method to repair gaps to achieve more accurate glucometrics.
Trial report in Journal of diabetes science and technology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Small changes in glucose variability induced by low and high glycemic index diets are not associated with changes in β-cell function in adults with pre-diabetes.Journal of diabetes and its complications · 2020Trial
- Targeting glucose control in preterm infants: pilot studies of continuous glucose monitoring.Archives of disease in childhood. Fetal and neonatal edition · 2019Trial
- Trial
- Glucose levels are associated with mood, but the association is mediated by ratings of metabolic state.EBioMedicine · 2026Observational
- Metabolic Trajectories During Surgical Stress in Patients Undergoing Cardiac Surgery.bioRxiv : the preprint server for biology · 2025Article
- Benchmarking Missing Data Imputation Methods for Time Series Using Real-World Test Cases.Proceedings of machine learning research · 2025Article
- Predicting Glycated Hemoglobin Through Continuous Glucose Monitoring in Real-Life Conditions: Improved Estimation Methods.Journal of diabetes science and technology · 2023Article
- People with type 1 diabetes and impaired awareness of hypoglycaemia have a delayed reaction to performing a glucose scan during hypoglycaemia: a prospective observational study.Diabetic medicine : a journal of the British Diabetic Association · 2020Observational
- Functional data analysis and prediction tools for continuous glucose-monitoring studies.Journal of clinical and translational science · 2020Article
- Article
- Characterization of Artifact Influence on the Classification of Glucose Time Series Using Sample Entropy Statistics.Entropy (Basel, Switzerland) · 2018Article
- Continuous Glucose Monitoring: A Review of Successes, Challenges, and Opportunities.Diabetes technology & therapeutics · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Estimation of glycemic variability requires frequent measures of glucose and is greatly aided by continuous glucose monitoring (CGM); however, under real-world conditions, missing data or "gaps" of ≥ 10 minutes can occur in CGM data, affecting the reliability of certain estimates. Thus, we determined the magnitude of the gap problem as observed in a cohort of patients with type 2 diabetes and demonstrated an approach to fill the gaps. The approach takes the difference between readings before and after a gap and distributes the difference equally across the number of missing readings, as determined by the sensor's setting for reading frequency. The approach is easy to implement, conservative, and improves estimation of variability measures that reference time, namely, mean of daily differences and continuous overlapping net glycemic action.
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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 OpenQuestion graph.