scholarly journals Comparison of Glucose and HBA1C Values Between Finger-Piercing and Continuous Glucose Monitoring Sensor Using Gh-Method: Math-Physical Medicine (no. 293)

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Gerald C Hsu

This article discusses the fundamental characteristics of measured glucose levels and predicted glycated hemoglobin A1c (HbA1c) values among three sets of collected data, measured finger-piercing and continuous glucose monitoring (CGM) sensor device collected glucose levels at 15-minute (15-min) and 5-minute (5-min) intervals. The average glucose (in milligram per deciliter-mg/dL) is listed below: Finger glucose: 109 mg/dL (100%) Sensor at 15-min: 120 mg/dL (109%) Sensor at 5-min: 117 mg/dL (107%) Using candlestick chart, the comparison of average glucoses during this period between two sensor glucose (mg/dL) data (15-min/5-min) are as follows: Open glucose: 108/111 Close glucose: 115/115 Maximum (max) glucose: 170 /175 Minimum (min) glucose: 85/83 Average glucose: 120/117 Additional analysis of time above range (TAR)≥140 mg/dL for hyperglycemia, time within the range (TIR) from 70-140 mg/dL for normal, time below range (TBR)≤70 mg/dL for hypoglycemia based on two sensor candlesticks revealing the following information in a specific format of TAR%/ TIR%/TBR%. 15-min:18.3%, 80.5%, 1.2% 5-min: 17.0%, 81.9%, 1.1% By evaluating the results of the TIR analysis, the 5-min glucose levels appear to be marginally healthier (1.4%) than the 15-min ones. During the coronavirus pandemic (COVID 19) quarantine period, the author lived a rather unique lifestyle which is extremely calm with regular routines, such as eating home-cooked meals and exercising on a regular basis. As a result, his HbA1c has decreased from 6.6% to 6.3% with an average A1c of 6.4% without taking any diabetes medications. However, these three different measurement methods still provide three different sets of glucoses levels which are within a 10% margin of differences, while the HbA1c values are particularly close to each other between the finger-piercing and CGM 15-min.

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Mohammad Arifur Rahman

This article discusses the fundamental characteristics of measured glucose levels and predicted glycated hemoglobin A1c (HbA1c) values among three sets of collected data, measured finger-piercing and continuous glucose monitoring (CGM) sensor device collected glucose levels at 15-minute (15-min) and 5-minute (5-min) intervals. The average glucose (in milligram per deciliter-mg/dL) is listed below: Finger glucose: 109 mg/dL (100%) Sensor at 15-min: 120 mg/dL (109%) Sensor at 5-min: 117 mg/dL (107%) Using candlestick chart, the comparison of average glucoses during this period between two sensor glucose (mg/dL) data (15-min/5-min) are as follows: Open glucose: 108/111 Close glucose: 115/115 Maximum (max) glucose: 170 /175 Minimum (min) glucose: 85/83 Average glucose: 120/117 Additional analysis of time above range (TAR)≥140 mg/dL for hyperglycemia, time within the range (TIR) from 70-140 mg/dL for normal, time below range (TBR)≤70 mg/dL for hypoglycemia based on two sensor candlesticks revealing the following information in a specific format of TAR%/ TIR%/TBR%. 15-min:18.3%, 80.5%, 1.2% 5-min: 17.0%, 81.9%, 1.1% By evaluating the results of the TIR analysis, the 5-min glucose levels appear to be marginally healthier (1.4%) than the 15-min ones. During the coronavirus pandemic (COVID 19) quarantine period, the author lived a rather unique lifestyle which is extremely calm with regular routines, such as eating home-cooked meals and exercising on a regular basis. As a result, his HbA1c has decreased from 6.6% to 6.3% with an average A1c of 6.4% without taking any diabetes medications. However, these three different measurement methods still provide three different sets of glucoses levels which are within a 10% margin of differences, while the HbA1c values are particularly close to each other between the finger-piercing and CGM 15-min.


2019 ◽  
Vol 104 (10) ◽  
pp. 4356-4364 ◽  
Author(s):  
Viral N Shah ◽  
Stephanie N DuBose ◽  
Zoey Li ◽  
Roy W Beck ◽  
Anne L Peters ◽  
...  

Abstract Context Use of continuous glucose monitoring (CGM) is increasing for insulin-requiring patients with diabetes. Although data on glycemic profiles of healthy, nondiabetic individuals exist for older sensors, assessment of glycemic metrics with new-generation CGM devices is lacking. Objective To establish reference sensor glucose ranges in healthy, nondiabetic individuals across different age groups using a current generation CGM sensor. Design Multicenter, prospective study. Setting Twelve centers within the T1D Exchange Clinic Network. Patients or Participants Nonpregnant, healthy, nondiabetic children and adults (age ≥6 years) with nonobese body mass index. Intervention Each participant wore a blinded Dexcom G6 CGM, with once-daily calibration, for up to 10 days. Main Outcome Measures CGM metrics of mean glucose, hyperglycemia, hypoglycemia, and glycemic variability. Results A total of 153 participants (age 7 to 80 years) were included in the analyses. Mean average glucose was 98 to 99 mg/dL (5.4 to 5.5 mmol/L) for all age groups except those over 60 years, in whom mean average glucose was 104 mg/dL (5.8 mmol/L). The median time between 70 to 140 mg/dL (3.9 to 7.8 mmol/L) was 96% (interquartile range, 93 to 98). Mean within-individual coefficient of variation was 17 ± 3%. Median time spent with glucose levels >140 mg/dL was 2.1% (30 min/d), and median time spent with glucose levels <70 mg/dL (3.9 mmol/L) was 1.1% (15 min/d). Conclusion By assessing across age groups in a healthy, nondiabetic population, normative sensor glucose data have been derived and will be useful as a benchmark for future research studies.


2021 ◽  
pp. 1-9
Author(s):  
Tobias Bomholt ◽  
Marianne Rix ◽  
Thomas Almdal ◽  
Filip K. Knop ◽  
Susanne Rosthøj ◽  
...  

<b><i>Introduction:</i></b> The accuracy of hemoglobin A1c (HbA1c) as a glycemic marker in patients with type 2 diabetes (T2D) receiving hemodialysis (HD) remains unknown. To assess accuracy, we compared HbA1c and fructosamine levels with interstitial glucose measured by continuous glucose monitoring (CGM) in patients with T2D receiving HD. <b><i>Methods:</i></b> Thirty patients in the HD group and 36 patients in the control group (T2D and an estimated glomerular filtration rate &#x3e;60 mL/min/1.73 m<sup>2</sup>) completed the study period of 17 weeks. CGM (Ipro2<sup>®</sup>, Medtronic) was performed 5 times for periods of up to 7 days (with 4-week intervals) during a 16-week period. HbA1c (mmol/mol), the estimated mean plasma glucose from HbA1c (eMPGA1c [mmol/L]) and fructosamine (μmol/L) was measured at week 17 and compared with mean sensor glucose levels from CGM. <b><i>Findings:</i></b> In the HD group, mean sensor glucose was 1.4 mmol/L (95% confidence interval [CI]: 1.0–1.8) higher than the eMPGA1c, whereas the difference for controls was 0.1 mmol/L (95% CI: −0.1–[0.4]; <i>p</i> &#x3c; 0.001). Adjusted for mean sensor glucose, HbA1c was lower in the HD group (−7.3 mmol/mol, 95% CI: −10.0–[−4.7]) than in the control group (<i>p</i> &#x3c; 0.001), with no difference detected for fructosamine (<i>p</i> = 0.64). <b><i>Discussion:</i></b> HbA1c evaluated by CGM underestimates plasma glucose levels in patients receiving HD. The underestimation represents a clinical challenge in optimizing glycemic control in the HD population. Fructosamine is unaffected by the factors affecting HbA1c and appears to be more accurate for glycemic monitoring. CGM or fructosamine could thus complement HbA1c in obtaining more accurate glycemic control in this patient group.


2015 ◽  
Vol 41 (1-3) ◽  
pp. 18-24 ◽  
Author(s):  
Ahad Qayyum ◽  
Tahseen A. Chowdhury ◽  
Elizabeth Ley Oei ◽  
Stanley L. Fan

Introduction: Glycated hemoglobin is used to assess diabetic control although its accuracy in dialysis has been questioned. How does it compare to the Continuous Glucose Monitoring System (CGMS) in peritoneal dialysis (PD) patients? Methods: We conducted a retrospective analysis of 60 insulin-treated diabetic patients on PD. We determined the mean interstitial glucose concentration and the proportion of patients with hypoglycemia (<4 mmol/l) or hyperglycemia (>11 mmol/l). Results: The correlation between HbA1c and glucose was 0.48, p < 0.0001. Three of 15 patients with HbA1c >75 mmol/mol experienced significant hypoglycemia (14-144 min per day). The patients with frequent episodes of hypoglycemia could not be differentiated from those with frequent hyperglycemia by demographics or PD prescription. Conclusion: HbA1c and average glucose levels measured by the CGMS are only weakly correlated. On its own, HbA1c as an indicator of glycemic control in patients with diabetes on PD appears inadequate. We suggest that the CGMS technology should be more widely adopted.


2021 ◽  
Vol 8 (16) ◽  
pp. 1-142
Author(s):  
Kathryn Beardsall ◽  
Lynn Thomson ◽  
Catherine Guy ◽  
Simon Bond ◽  
Annabel Allison ◽  
...  

Background Hyperglycaemia and hypoglycaemia are common in preterm infants and are associated with increased mortality and morbidity. Continuous glucose monitoring is widely used to target glucose control in adults and children, but not in neonates. Objective To evaluate the role of continuous glucose monitoring in the preterm infant. Design The REAl-time Continuous glucose moniToring in neonatal intensive care project combined (1) a feasibility study, (2) a multicentre randomised controlled trial and (3) a pilot of ‘closed-loop’ continuous glucose monitoring. The feasibility study comprised a single-centre study (n = 20). Eligibility criteria included a birthweight ≤ 1200 g and aged ≤ 48 hours. Continuous glucose monitoring was initiated to support glucose control. The efficacy and safety outcomes guided the design of the randomised controlled trial. The randomised controlled trial comprised a European multicentre trial (n = 182). Eligibility criteria included birthweight ≤ 1200 g and aged ≤ 24 hours. Exclusion criteria included any lethal congenital abnormality. Continuous glucose monitoring was initiated to support glucose control within 24 hours of birth. In the intervention group, the continuous glucose monitoring sensor provided real-time data on glucose levels, which guided clinical management. In control infants, the continuous glucose monitoring data were masked, and glucose level was managed in accordance with standard clinical practice and based on the blood glucose levels. The primary outcome measure was the percentage of time during which the sensor glucose level was within the target range of 2.6–10 mmol/l. Secondary outcome measures included mean sensor glucose level, the percentage of time during which the sensor glucose level was within the target range of 4–8 mmol/l, the percentage of time during which the sensor glucose level was in the hyperglycaemic range (i.e. > 15 mmol/l) and sensor glucose level variability. Safety outcomes included hypoglycaemia exposure. Acceptability assessment and health economic analyses were carried out and further exploratory health outcomes were explored. The mean percentage of time in glucose target range of 2.6–10 mmol/l was 9% higher in infants in the continuous glucose monitoring group (95% confidence interval 3% to 14%; p = 0.002), and the mean time in the target range of 4–8 mmol/l was 12% higher in this group (95% confidence interval 4% to 19%; p = 0.004). There was no difference in the number of episodes of hypoglycaemia. Exploratory outcomes showed a reduced risk of necrotising enterocolitis in the intervention arm (odds ratio 0.33, 95% confidence interval 0.13 to 0.78; p = 0.01). Health economic analyses demonstrated that continuous glucose monitoring was cost-effective on the basis of the cost per additional case of adequate glucose control between 2.6 and 10 mmol/l. The ‘closed-loop’ study was a single-center pilot study, with eligibility criteria including a birthweight of ≤ 1200 g and aged ≤ 48 hours. Infants underwent continuous glucose monitoring for the first week of life (n = 21), with those in the intervention group receiving closed-loop insulin delivery between 48 and 72 hours of age. The primary outcome of percentage of time in the target range (i.e. sensor glucose 4–8 mmol/l) increased from a median of 26% (interquartile range 6–64%) to 91% (interquartile range 78–99%) during closed-loop insulin delivery (p < 0.001). Limitations These studies have not defined the optimal targets for glucose control or the best strategies to achieve them in these infants. Future work Studies are needed to evaluate the longer-term impact of targeting glucose control on clinical outcomes. Conclusions Continuous glucose monitoring in extremely preterm infants can improve glucose control, with closed-loop insulin delivery having further potential to target glucose levels. Staff and parents felt that the use of continuous glucose monitoring improved care and the results of the health economic evaluation favours the use of continuous glucose monitoring. Trial registration Current Controlled Trials ISRCTN12793535. Funding This project was funded by the Efficacy and Mechanism Evaluation (EME) programme, a MRC and National Institute for Health Research (NIHR) partnership. This will be published in full in Efficacy and Mechanism Evaluation; Vol. 8, No. 16. See the NIHR Journals Library website for further project information. Medtronic plc provided some MiniMed™ 640G systems and Nova Biomedical (Waltham, MA, USA) provided point-of-care devices.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jen-Hung Huang ◽  
Yung-Kuo Lin ◽  
Ting-Wei Lee ◽  
Han-Wen Liu ◽  
Yu-Mei Chien ◽  
...  

Abstract 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.


Author(s):  
Myat Win ◽  
Rowan Beckett ◽  
Lynn Thomson ◽  
Ajay Thankamony ◽  
Kathy Beardsall

Abstract Background Persistent hypoglycaemia is common in the newborn and is associated with poor neurodevelopmental outcome. Adequate monitoring is critical in prevention, but is dependent on frequent, often hourly blood sampling. Continuous glucose monitoring (CGM) is increasingly being used in children with type 1 diabetes mellitus, but use in neonatology remains limited. We aimed to introduce real-time CGM to provide insights into patterns of dysglycaemia and to support the management of persistent neonatal hypoglycaemia. Methods This is a single centre retrospective study of real-time CGM use over a 4-year period in babies with persistent hypoglycaemia. Results CGMs were inserted in 14 babies: 8 term and 6 preterm infants, 9 with evidence of congenital hyperinsulinism (CHI). A total of 224 days of data were collected demonstrating marked fluctuations in glucose levels in babies with CHI, with a higher sensor glucose SD (1.52±0.79 mmol/l vs 0.77±0.22mmol/l) in infants with CHI compared to preterm infants. A total of 1254 paired glucose values (CGM and blood) were compared and gave a mean absolute relative difference (MARD) of 11%. Conclusion CGM highlighted the challenges of preventing hypoglycaemia in these babies when using intermittent blood glucose levels alone, and the potential application of CGM as an adjunct to clinical care.


Author(s):  
Sathyakala Vijayanand ◽  
Paul G. Stevenson ◽  
Maree Grant ◽  
Catherine S. Choong ◽  
Elizabeth A. Davis ◽  
...  

Abstract Objectives Glucose monitoring is vital in children with persistent hypoglycaemia to reduce the risk of adverse neuro-behavioural outcomes; especially in children with hyperinsulinism. The role of continuous glucose monitoring (CGM) systems in monitoring glucose levels in this cohort is limited. The objective of this study was to ascertain the effectiveness of CGM and to evaluate parents’ experience of using CGM for monitoring glucose levels in children with hypoglycaemia. Methods Retrospective analysis of sensor glucose (SG) values from Dexcom G4 CGM with paired finger-prick blood glucose (BG) values was performed to determine the accuracy of CGM. The parent experience of CGM was assessed using a questionnaire administered to families of children with congenital hyperinsulinism currently attending the clinic. Results SG data from 40 children (median age 6 months) with persistent hypoglycaemia (60% Hyperinsulinism) were analysed. The mean difference between 5,650 paired BG and SG values was 0.28 mmol/L. The sensitivity and specificity of CGM to identify severe hypoglycaemia (BG < 3.0 mmol/L) were 54.3% (95% CI: 39.0%, 69.1%) and 97.4% (95% CI: 96.9%, 97.8%) respectively. Parents (n=11) reported less anxiety (n=9), better sleep at night (n=7) and preferred to use CGM for monitoring (n=9). Conclusions Although the high number of false-positive readings precludes the routine use of CGM in the evaluation of hypoglycaemia, it avoids unnecessary BG testing during normoglycaemia. It is an acceptable tool for parents for monitoring their children who are at risk of hypoglycaemia. Newer CGM systems with improved accuracy at lower glucose levels have the potential to further improve monitoring.


2009 ◽  
Vol 3 (3) ◽  
pp. 429-438 ◽  
Author(s):  
Ken Sikaris

The understanding that hemoglobin A1c (HbA1c) represents the average blood glucose level of patients over the previous 120 days underlies the current management of diabetes. Even in making such a statement, we speak of “average blood glucose” as though “blood glucose” were itself a simple idea. When we consider all the blood glucose forms—arterial versus venous versus capillary, whole blood versus serum versus fluoride-preserved plasma, fasting versus nonfasting—we can start to see that this is not a simple issue. Nevertheless, it seems as though HbA1c correlates to any single glucose measurement. Having more than one measurement and taking those measurements in the preceding month improves the correlation further. In particular, by having glucose measurements that reflect both the relatively lower overnight glucose levels and measurements that reflect the postprandial peaks improves not only our ability to manage diabetes patients, but also our understanding of how HbA1c levels are determined. Modern continuous glucose monitoring (CGM) devices may take thousands of glucose results over a week. Several studies have shown that CGM glucose averages account for the vast proportion of the variation of HbA1c. The ability to relate HbA1c to average glucose may become a popular method for reporting HbA1c, eliminating current concerns regarding differences in HbA1c standardization. Hemoglobin A1c expressed as an average glucose may be more understandable to patients and improve not only their understanding, but also their ability to improve their diabetes management.


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