Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems

Scuffi, Cosimo

doi:10.17925/ee.2014.10.01.36

Cited by 13 publications

(12 citation statements)

References 170 publications

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“…In all 20 cats, the sensor read IG 60 minutes after successful application. The overall median wearing period of the sensor was 5.5 (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14) days. Sensors that were secured using tissue glue had a median wearing period of 6 days compared to 5 days for sensors in which glue was not used (P = .5).…”

Section: Sensor Application and Maintenance In Clientowned Diabetic Catsmentioning

confidence: 99%

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Accuracy of a flash glucose monitoring system in cats and determination of the time lag between blood glucose and interstitial glucose concentrations

Baldo

Fracassi

Pires

et al. 2021

Veterinary Internal Medicne

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Background: The FreeStyle Libre (Abbott Laboratories) is a flash glucose monitoring system (FGMS) that measures interstitial glucose concentration (IG). The system is factory-calibrated, easy to use, inexpensive, and could be useful for monitoring diabetic cats.Objectives: To evaluate the analytical and clinical accuracy of the FGMS in cats and establish the lag-time between IG and blood glucose concentration (BG).Animals: Twenty client-owned diabetic cats and 7 purpose-bred healthy cats.Methods: Prospective study. Blood glucose concentration was measured using a portable glucose meter validated for use in cats that served as a reference method for IG, as measured by FGMS. In diabetic cats, data were collected for sensor wearing time with different methods of application and accuracy across glycemic ranges. Accuracy was determined by fulfillment of ISO15197:2013 criteria. In healthy cats, lag-time between IG and BG was established after IV administration of exogenous glucose.Results: Good agreement between IG and BG was obtained (r = .93). Analytical accuracy was not achieved, whereas clinical accuracy was demonstrated with 100% of the results in zones A + B of the Parkes consensus error grid analysis. In the immediate 30 minutes after an IV bolus of glucose, when BG was increasing rapidly (approximately 2%/min), IG increased slowly, resulting in a difference of as much as 579 mg/ dL, and no positive correlation between BG and IG was found.Conclusions and Clinical Importance: The FGMS did not fulfill ISO requirements but is sufficiently accurate for glucose monitoring in cats, while considering the lag between IG and BG during periods of rapid changes in BG.

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Section: Sensor Application and Maintenance In Clientowned Diabetic Catsmentioning

confidence: 99%

“…These devices measure interstitial glucose concentration (IG), which correlates well with BG 7,8 . However, a lag‐time occurs between changes in BG and IG and the latter also is affected by local factors specific to the tissue in which it is measured 9 . The accuracy of some CGMS units has been described in cats 10‐16 .…”

Section: Introductionmentioning

confidence: 99%

Accuracy of a flash glucose monitoring system in cats and determination of the time lag between blood glucose and interstitial glucose concentrations

Baldo

Fracassi

Pires

et al. 2021

Veterinary Internal Medicne

View full text Add to dashboard Cite

show abstract

“…However, studies have noted strong correlations between CGM interstitial glucose and venous plasma or capillary glucose levels [ 29 – 31 ]. Studies have reported a less than the acceptable correlation between CGM interstitial glucose results and venous plasma or capillary glucose levels [ 32 , 33 ]. In this study, we determined that CGM may correlate well with HbA1c values over 3 months before and 3 months after CGM.…”

Section: Discussionmentioning

confidence: 99%

Correlation between short- and mid-term hemoglobin A1c and glycemic control determined by continuous glucose monitoring

Huang

Lin

Lee

et al. 2021

Diabetol Metab Syndr

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Background Glucose monitoring is vital for glycemic control in patients with diabetes mellitus (DM). Continuous glucose monitoring (CGM) measures whole-day glucose levels. Hemoglobin A1c (HbA1c) is a vital outcome predictor in patients with DM. Methods This study investigated the relationship between HbA1c and CGM, which remained unclear hitherto. Data of patients with DM (n = 91) who received CGM and HbA1c testing (1–3 months before and after CGM) were retrospectively analyzed. Diurnal and nocturnal glucose, highest CGM data (10%, 25%, and 50%), mean amplitude of glycemic excursions (MAGE), percent coefficient of variation (%CV), and continuous overlapping net glycemic action were compared with HbA1c values before and after CGM. Results The CGM results were significantly correlated with HbA1c values measured 1 (r = 0.69) and 2 (r = 0.39) months after CGM and 1 month (r = 0.35) before CGM. However, glucose levels recorded in CGM did not correlate with the HbA1c values 3 months after and 2–3 months before CGM. MAGE and %CV were strongly correlated with HbA1c values 1 and 2 months after CGM, respectively. Diurnal blood glucose levels were significantly correlated with HbA1c values 1–2 months before and 1 month after CGM. The nocturnal blood glucose levels were significantly correlated with HbA1c values 1–3 months before and 1–2 months after CGM. Conclusions CGM can predict HbA1c values within 1 month after CGM in patients with DM.

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“…The glucose concentration in the tissue interstitial fluid was estimated using a two-point calibration method similar to those previously described for electrochemical CGM sensors 38,39 . This method assumes that interstitial fluid concentrations show similar concentrations and excursions to the blood glucose levels (albeit with a time lag), which is typically observed in healthy subjects 35,74 . A similar estimation technique is employed by the commercially available Menarini Glucoday sensor (which uses microdialysis and an electrochemical sensor in the dialysate stream) and does not measure in vivo probe recovery 23 .…”

Section: Methodsmentioning

confidence: 99%

Monitoring biomolecule concentrations in tissue using a wearable droplet microfluidic-based sensor

et al. 2019

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Knowing how biomarker levels vary within biological fluids over time can produce valuable insight into tissue physiology and pathology, and could inform personalised clinical treatment. We describe here a wearable sensor for monitoring biomolecule levels that combines continuous fluid sampling with in situ analysis using wet-chemical assays (with the specific assay interchangeable depending on the target biomolecule). The microfluidic device employs a droplet flow regime to maximise the temporal response of the device, using a screw-driven push-pull peristaltic micropump to robustly produce nanolitre-sized droplets. The fully integrated sensor is contained within a small (palm-sized) footprint, is fully autonomous, and features high measurement frequency (a measurement every few seconds) meaning deviations from steady-state levels are quickly detected. We demonstrate how the sensor can track perturbed glucose and lactate levels in dermal tissue with results in close agreement with standard off-line analysis and consistent with changes in peripheral blood levels.

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Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems

Cited by 13 publications

References 170 publications

Accuracy of a flash glucose monitoring system in cats and determination of the time lag between blood glucose and interstitial glucose concentrations

Accuracy of a flash glucose monitoring system in cats and determination of the time lag between blood glucose and interstitial glucose concentrations

Correlation between short- and mid-term hemoglobin A1c and glycemic control determined by continuous glucose monitoring

Monitoring biomolecule concentrations in tissue using a wearable droplet microfluidic-based sensor

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