Does fall in tissue glucose precede fall in blood glucose?

Sternberg, F; Meyerhoff, C; Mennel, FJ; Mayer, Hermann; Bischof, F; Pfeiffer, Ernst-Friedrich

doi:10.1007/bf00403309

Cited by 85 publications

(64 citation statements)

References 19 publications

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“…In one patient, bleeding was noted at the implantation site. Bleeding has been previously described as interfering with proper subcutaneous sensor function (9). Other sensors showed considerable drift in sensor signal although the reason for the drift is not obvious, possibly reflecting occult hemorrhage/thrombus formation, tissue protein adsorption, localized accumulation of inflammatory cells, or fibrous encapsulation at the sensor-tissue interface (7,16,17).…”

Section: Discussionmentioning

confidence: 99%

“…After insulin administration, the hypothesis has been advanced that cellular glucose utilization would precede and cause a drop in interstitial glucose, followed by a drop in blood glucose-hypoglycohistiosis (low tissue glucose) preceding hypoglycemia (9). This effect has apparently been demonstrated in diabetic rats (10), diabetic dogs (11), and in some patients with type 1 diabetes (9).…”

Section: Discussionmentioning

confidence: 99%

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Timing of Changes in Interstitial and Venous Blood Glucose Measured With a Continuous Subcutaneous Glucose Sensor

Boyne

Silver²,

Kaplan³

et al. 2003

Diabetes

365

275

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The objective of this study was to use a subcutaneous continuous glucose sensor to determine time differences in the dynamics of blood glucose and interstitial glucose. A total of 14 patients with type 1 diabetes each had two sensors (Medtronic/MiniMed CGMS) placed subcutaneously in the abdomen, acquiring data every 5 min. Blood glucose was sampled every 5 min for 8 h, and two liquid meals were given. A smoothing algorithm was applied to the blood glucose and interstitial glucose curves. The first derivatives of the glucose traces defined and quantified the timing of rises, peaks, falls, and nadirs. Altogether, 24 datasets were used for the analysis of time differences between interstitial and blood glucose and between sensors in each patient. Time differences between blood and interstitial glucose ranged from 4 to 10 min, with the interstitial glucose lagging behind blood glucose in 81% of cases (95% CIs 72.5 and 89.5%). The mean (؎SD) difference between the two sensors in each patient was 6.7 ؎ 5.1 min, representing random variation in sensor response. In conclusion, there is a time lag of interstitial glucose behind blood glucose, regardless of whether glycemia is rising or falling, but intersensor variability is considerable in this sensor system. Comparisons of interstitial and blood glucose kinetics must take statistical account of variability between sensors. Diabetes 52:2790 -2794, 2003

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Timing of Changes in Interstitial and Venous Blood Glucose Measured With a Continuous Subcutaneous Glucose Sensor

Boyne

Silver²,

Kaplan³

et al. 2003

Diabetes

365

275

View full text Add to dashboard Cite

show abstract

“…Several groups have postulated that ISF glucose could fall in advance of plasma glucose following insulin treatment [11,16,17]. This hypothesis, commonly referred to as 'push-pull', maintains that an increase in plasma glucose pushes glucose into the ISF space, and an increase in tissue glucose uptake lowers the ISF-glucose and pulls Following a 30-min basal period (−30<t<0), plasma glucose was clamped at basal (0<t<90 min), 4.2 mmol/l (90<t<180 min) and 3.1 mmol/l (180<t<270 min) and then allowed to return to normal levels (270<t<380 min).…”

Section: Discussionmentioning

confidence: 99%

“…In the absence of such a measure, microdialysis has been the primary source from which ISF glucose has been determined [4,6,10,11]. To this end, the glucose concentration in the effluent-i.e.…”

Section: Introductionmentioning

confidence: 99%

Interstitial fluid glucose dynamics during insulin-induced hypoglycaemia

et al. 2005

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Aims/hypothesis: Glucose sensors often measure s.c. interstitial fluid (ISF) glucose rather than blood or plasma glucose. Putative differences between plasma and ISF glucose include a protracted delay during the recovery from hypoglycaemia and an increased gradient during hyperinsulinaemia. These have often been investigated using sensor systems that have delays due to signal smoothing, or require long equilibration times. The aim of the present study was to define these relationships during hypoglycaemia in a well-equilibrated system with no smoothing. Methods: Hypoglycaemia was induced by i.v. insulin infusion (360 pmol·m −2 ·min −1 ) in ten non-diabetic subjects. Glucose was sequentially clamped at ∼5, 4.2 and 3

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“…[9][10][11][12][13] It appears as if this physiological time delay may work both ways, with BG changes preceding interstitial glucose changes as well as interstitial glucose changes preceding BG changes. 11,14 Further research assessing this time delay on a large scale and in a systematic manner could help clarify this issue. An additional time delay is introduced through the sensor architecture because the glucose has to pass through the membranes surrounding the electrodes and, for sensors using a glucose oxidase enzyme, the hydrogen peroxide that is created through the glucose oxidase reaction has to move to the electrode.…”

mentioning

confidence: 99%

Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Swings

Pleus

Schoemaker

Morgenstern

et al. 2015

J Diabetes Sci Technol

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Introduction: The accuracy of continuous glucose monitoring (CGM) systems is often assessed with respect to blood glucose (BG) readings. CGM readings are affected by a physiological and a technical time delay when compared to BG readings. In this analysis, the dependence of CGM performance parameters on the BG rate of change was investigated for 2 CGM systems. Methods: Data from a previously published study were retrospectively analyzed. An established CGM system (Dexcom G4, Dexcom, San Diego, CA; system A) and a prototype system (Roche Diagnostics GmbH, Mannheim, Germany; system B) with 2 sensors each were worn by 10 subjects in parallel. Glucose swings were induced to achieve rapidly changing BG concentrations. Mean absolute relative differences (MARD) were calculated in different BG rate-of-change categories. In addition, sensor-to-sensor precision was assessed. Results: At BG rates of change of –1 mg/dl/min to 0 mg/dl/min and 0 mg/dl/min to +1 mg/dl/min, MARD results were 12.6% and 11.3% for system A and 8.2% and 10.0% for system B. At rapidly changing BG concentrations (<–3 mg/dl/min and ≥+3 mg/dl/min), higher MARD results were found for both systems, but system B was less affected (system A: 24.9% and 29.6%, system B: 10.6% and 16.3%). The impact of rate of change on sensor-to-sensor precision was less pronounced. Conclusions: Both systems were affected by rapidly changing BG concentrations to some degree, although system B was mostly unaffected by decreasing BG concentrations. It would seem that technological advancements in CGM systems might allow for a more precise tracking of BG concentrations even at rapidly changing BG concentrations.

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Does fall in tissue glucose precede fall in blood glucose?

Cited by 85 publications

References 19 publications

Timing of Changes in Interstitial and Venous Blood Glucose Measured With a Continuous Subcutaneous Glucose Sensor

Timing of Changes in Interstitial and Venous Blood Glucose Measured With a Continuous Subcutaneous Glucose Sensor

Interstitial fluid glucose dynamics during insulin-induced hypoglycaemia

Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Swings

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