2013
DOI: 10.1177/193229681300700110
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Minding the Gaps in Continuous Glucose Monitoring: A Method to Repair Gaps to Achieve More Accurate Glucometrics

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 an… Show more

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Cited by 21 publications
(14 citation statements)
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References 17 publications
(21 reference statements)
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“…The sensors were well tolerated in these preterm infants despite the babies’ low birth weight, limited subcutaneous tissue and potential risk of infection. The lack of data collection in two of the control babies is in keeping with problems in other study populations 25 26. The size and position of the transmitter was not felt to interfere with care and staff reported the intervention lead to improved care.…”
Section: Discussionmentioning
confidence: 66%
“…The sensors were well tolerated in these preterm infants despite the babies’ low birth weight, limited subcutaneous tissue and potential risk of infection. The lack of data collection in two of the control babies is in keeping with problems in other study populations 25 26. The size and position of the transmitter was not felt to interfere with care and staff reported the intervention lead to improved care.…”
Section: Discussionmentioning
confidence: 66%
“…Although more than one missing sample can be found consecutively (missing epochs), that case is easily detected and usually addressed splitting the record at that point (the longer the gap, the less reliable the calculations become [ 11 ]), and therefore, only the most frequent case of a single missing sample was analyzed.…”
Section: Experiments and Resultsmentioning
confidence: 99%
“…In addition, devices of CGM need to be recalibrated, up to several times per day [ 10 ], and mainly at the beginning of the ambulatory monitoring. Missing values are also frequently found in these records, due to device or sensor errors [ 11 ]. Other problems encountered in blood glucose time series are sensor out-of-range or sensor disconnection values, causing a signal saturation or a flat reading during a time interval usually involving several contiguous samples.…”
Section: Introductionmentioning
confidence: 99%
“…Similarly, continuous glucose monitoring technology has shown promise for longer term physiological outcomes (including glycated haemoglobin (HbA1c)), 18 supporting the suggestion that more frequent engagement leads to better health outcomes. 19 Self-monitoring of both behaviour and outcomes are listed within the taxonomy alongside 91 other ingredients (ie, feedback and goal setting) in behavioural interventions. 20 As well as delivering key behaviour change techniques, self-monitoring technologies also support Control Theory.…”
Section: Introductionmentioning
confidence: 99%