P6441New continuous glucose monitoring reveals hypoglycemia risk in both diabetic and nondiabetic patients with acute myocardial infarction

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M Kuroda ◽  
M Kawata ◽  
A Matsuura ◽  
K Adachi ◽  
Y Hirayama ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Mean Amplitude ◽  
Glucose Fluctuation ◽  
Glucose Levels ◽  
Interstitial Glucose ◽  
The Mean ◽  
Artery Disease

Abstract Background There has been growing evidence that the glucose fluctuation is an important contributing factor to the development of coronary artery disease. However, whether large glucose fluctuation, especially hypoglycemia, may be associated with acute myocardial infarction (AMI) remains largely unknown. Aim As new continuous glucose monitoring (CGM) has recently become available to evaluate glucose fluctuation from immediately after an emergency visit, this study sought to investigate glucose fluctuation and the occurrence of hypoglycemia in patients with AMI. Methods In this prospective study, 93 consecutive patients with AMI from April 2017 to November 2018 were enrolled. Subcutaneous interstitial glucose levels were monitored from emergency room to discharge using the CGM System. Based on the CGM data, 24-h mean glucose levels, the time in hyperglycemia and hypoglycemia and the occurrence of hypoglycemia, defined as less than 70 mg/dL, were measured, and the mean amplitude of glycemic excursions (MAGE) were calculated. Results The majority of patients [n=57, 61% (non-DM)] did not have diabetes and 36 patients had diabetes (DM). The occurrence of hypoglycemia within 24 hours after admission was observed in 49 patients [DM: n=11 (30.6%), non-DM: n=38 (66.7%)]. MAGE within 24 hours after admission were 100±47 in DM patients and 67±20 in non-DM patients. The mean time in hypoglycemia within 24 hours after admission was 148 minutes [DM: 100±260 minutes, non-DM: 178±287 minutes]. The occurrence of hypoglycemia during a hospital stay (mean 11.5 days) was detected in 76 patients [DM: n=28 (77.8%), non-DM: n=48 (84.2%)]. Representative case of hypoglycemia Conclusion Not only in DM patients but also in non-DM patients with AMI, large glucose fluctuation and high incidence of hypoglycemia were observed using new CGM system. Further investigations should address the rationale for the early detection and control of glucose fluctuation for AMI patients.

Use of Continuous Glucose Monitoring in Patients with Diabetes Mellitus on Peritoneal Dialysis: Correlation with Glycated Hemoglobin and Detection of High Incidence of Unaware Hypoglycemia

2015 ◽  
Vol 41 (1-3) ◽  
pp. 18-24 ◽  
Author(s):  
Ahad Qayyum ◽  
Tahseen A. Chowdhury ◽  
Elizabeth Ley Oei ◽  
Stanley L. Fan
Keyword(s):  
Peritoneal Dialysis ◽  
Continuous Glucose Monitoring ◽  
Glycated Hemoglobin ◽  
Glucose Monitoring ◽  
Diabetic Control ◽  
Diabetic Patients ◽  
Glucose Levels ◽  
High Incidence ◽  
Patients With Diabetes ◽  
Interstitial Glucose

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.

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

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jen-Hung Huang ◽  
Yung-Kuo Lin ◽  
Ting-Wei Lee ◽  
Han-Wen Liu ◽  
Yu-Mei Chien ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glycemic Control ◽  
Continuous Glucose Monitoring ◽  
Hemoglobin A1c ◽  
Glucose Monitoring ◽  
Mean Amplitude ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Before And After ◽  
Patients With Diabetes

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.

scholarly journals Evaluation of Reference Metrics for Continuous Glucose Monitoring in Persons Without Diabetes and Prediabetes

2020 ◽  
pp. 193229682096559
Author(s):  
Sheyda Sofizadeh ◽  
Anders Pehrsson ◽  
Arndís F. Ólafsdóttir ◽  
Marcus Lind
Keyword(s):  
Clinical Practice ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Mean Amplitude ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Glucose Lowering ◽  
Glucose Levels ◽  
Deviation Coefficient

Background: Recent guidelines have been developed for continuous glucose monitoring (CGM) metrics in persons with diabetes. To understand what glucose profiles should be judged as normal in clinical practice and glucose-lowering trials, we examined the glucose profile of healthy individuals using CGM. Methods: Persons without diabetes or prediabetes were included after passing a normal oral glucose tolerance test, two-hour value <8.9 mmol/L (160 mg/dL), fasting glucose <6.1 mmol/L (110 mg/dL), and HbA1c <6.0% (<42 mmol/mol). CGM metrics were evaluated using the Dexcom G4 Platinum. Results: In total, 60 persons were included, mean age was 43.0 years, 70.0% were women, mean HbA1c was 5.3% (34 mmol/mol), and mean body mass index was 25.7 kg/m2. Median and mean percent times in hypoglycemia <3.9 mmol/L (70 mg/dL) were 1.6% (IQR 0.6-3.2), and 3.2% (95% CI 2.0; 4.3), respectively. For glucose levels <3.0 mmol/L (54 mg/dL), the corresponding estimates were 0.0% (IQR 0.0-0.4) and 0.5% (95% CI 0.2; 0.8). Median and mean time-in-range (3.9-10.0 mmol/L [70-180 mg/dL]) was 97.3% (IQR 95.4-98.7) and 95.4% (95% CI 94.0; 96.8), respectively. Median and mean standard deviations were 1.04 mmol/L (IQR 0.92-1.29) and 1.15 mmol/L (95% CI 1.05; 1.24), respectively. Measures of glycemic variability (standard deviation, coefficient of variation, mean amplitude of glycemic excursions) were significantly greater during daytime compared with nighttime, whereas others did not differ. Conclusions: People without prediabetes or diabetes show a non-negligible % time in hypoglycemia, median 1.6% and mean 3.2%, which needs to be accounted for in clinical practice and glucose-lowering trials. Glycemic variability measures differ day and night in this population.

scholarly journals Outcome of Patients with ST-T Changes in Non STSegment Elevation Myocardial Infarction

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Mohammad Arifur Rahman
Keyword(s):  
Myocardial Infarction ◽  
Continuous Glucose Monitoring ◽  
Hemoglobin A1c ◽  
Glycated Hemoglobin ◽  
Glucose Monitoring ◽  
Measurement Methods ◽  
Glucose Levels ◽  
Sensor Device ◽  
Sensor Glucose ◽  
Average Glucose

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.

The utility of continuous glucose monitoring systems in the management of children with persistent hypoglycaemia

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Sathyakala Vijayanand ◽  
Paul G. Stevenson ◽  
Maree Grant ◽  
Catherine S. Choong ◽  
Elizabeth A. Davis ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Congenital Hyperinsulinism ◽  
Glucose Levels ◽  
Parent Experience ◽  
Lower Glucose ◽  
Sensor Glucose ◽  
The Mean ◽  
Improved Accuracy

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.

scholarly journals The Degree of Hyperglycemia Excursion in Patients of Kidney Transplantation (KT) or Liver Transplantation (LT) Assessed by Continuous Glucose Monitoring (CGM): Pilot Study

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Heung Yong Jin ◽  
Kyung Ae Lee ◽  
Yu Ji Kim ◽  
Tae Sun Park ◽  
Sik Lee ◽  
...  
Keyword(s):  
Liver Transplantation ◽  
Kidney Transplantation ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Early Period ◽  
Mean Amplitude ◽  
Glucose Levels ◽  
Normal Glucose ◽  
Glucose Profiles

Objective. This study used a continuous glucose monitoring system (CGMS) to investigate the glucose profiles and assess the degree of hyperglycemic excursion after kidney or liver transplantation during the early period after operation. Methods. Patients to whom a CGMS was attached during a postoperative period of approximately one month after transplantation were included. The CGM data of 31 patients including 24 with kidney transplantation (KT) and seven with liver transplantation (LT) were analyzed. Results. Hyperglycemia over 126 mg/dL (fasting) or 200 g/dL (postprandial) occurred in 42.1% (8/19) and 16.7% (1/6) of KT and LT patients, respectively, during this early period after transplantation, except for patients with preexisting diabetes (5 KT, 1 LT). The average mean amplitude of glycemic excursion (MAGE) and mean absolute glucose (MAG) levels were 91.18±26.51 vs. 65.66±22.55 (P<0.05) and 24.62±7.78 vs. 18.18±7.07 (P<0.05) in KT vs. LT patients, respectively, in patients without preexisting DM or PTDM patients who showed normal glucose levels. Average increase from the lowest level to the peak glucose value was higher in KT patients than LT patients (P<0.05). Conclusions. The transplanted organ also needs to be considered as an important factor affecting glucose control and the occurrence of more severe glucose excursions in patients who receive transplantation although immunosuppression agents are well-known important factors; however, our study was limited to the early posttransplantation period. Further studies involving CGM follow-up at regular intervals based on the time since transplantation are needed.

scholarly journals Correlation Between Short- and Mid-Term Hemoglobin A1c and Glycemic Control Determined by Continuous Glucose Monitoring

2021 ◽  
Author(s):  
Jen-Hung Huang ◽  
Yung-Kuo Lin ◽  
Ting-Wei Lee ◽  
Han-Wen Liu ◽  
Yu-Mei Chien ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glycemic Control ◽  
Continuous Glucose Monitoring ◽  
Hemoglobin A1c ◽  
Glucose Monitoring ◽  
Mean Amplitude ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Before And After ◽  
Patients With Diabetes

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.

scholarly journals Blood glucose and subcutaneous continuous glucose monitoring in critically ill horses: A pilot study

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247561
Author(s):  
Valentina Vitale ◽  
Lise C. Berg ◽  
Bettina Birch Larsen ◽  
Andrea Hannesdottir ◽  
Preben Dybdahl Thomsen ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Critically Ill ◽  
Continuous Glucose Monitoring ◽  
Interstitial Fluid ◽  
Point Of Care ◽  
Glucose Monitoring ◽  
Relevant Information ◽  
Glucose Levels ◽  
Interstitial Glucose ◽  
Blood Gas Analyzer

This pilot prospective study reports the feasibility, management and cost of the use of a continuous glucose monitoring (CGM) system in critically ill adult horses and foals. We compared the glucose measurements obtained by the CGM device with blood glucose (BG) concentrations. Neonatal foals (0–2 weeks of age) and adult horses (> 1 year old) admitted in the period of March-May 2016 with clinical and laboratory parameters compatible with systemic inflammatory response syndrome (SIRS) were included. Glucose concentration was monitored every 4 hours on blood samples with a point-of-care (POC) glucometer and with a blood gas analyzer. A CGM system was also placed on six adults and four foals but recordings were successfully obtained only in four adults and one foal. Glucose concentrations corresponded fairly well between BG and CGM, however, there appeared to be a lag time for interstitial glucose levels. Fluctuations of glucose in the interstitial fluid did not always follow the same trend as BG. CGM identified peaks and drops that would have been missed with conventional glucose monitoring. The use of CGM system is feasible in ill horses and may provide clinically relevant information on glucose levels, but there are several challenges that need to be resolved for the system to gain more widespread usability.

scholarly journals Continuous Glucose Monitoring of Glycemic Variability During Fasting Post-Sleeve Gastrectomy

2020 ◽  
Vol 30 (10) ◽  
pp. 3721-3729
Author(s):  
Ebaa Al-Ozairi ◽  
Abeer El Samad ◽  
Jumana Al Kandari ◽  
Etab Taghadom ◽  
Safwaan Adam ◽  
...  
Keyword(s):  
Sleeve Gastrectomy ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Intermittent Fasting ◽  
Open Label ◽  
Fasting Period ◽  
Significant Difference ◽  
Interstitial Glucose ◽  
Glucose Profiles ◽  
The Mean

Abstract Introduction Day-long fasting creates considerable metabolic stress that poses challenges in people with diabetes and those who have undergone bariatric surgery. Clinical knowledge of glucose fluctuations and the risks for such patients during fasting is limited. Objectives This study examined the effect of intermittent fasting on glucose excursions, hypoglycemia, and hyperglycemia in people with or without diabetes who had sleeve gastrectomy compared with healthy individuals. Methods This open-label, prospective study compared interstitial glucose profiles measured with continuous glucose monitoring system for 72 h during fasting and non-fasting periods between four groups comprising 15 participants each: people with obesity and medicine-treated type 2 diabetes (T2D) only, obesity and T2D treated with sleeve gastrectomy, obesity without T2D treated with sleeve gastrectomy, and healthy, normal-weight non-diabetic controls. Results The mean 72-h glucose concentration was significantly lower during the fasting period for all groups (p ≤ 0.041), with the highest glucose concentrations in the medicine-treated T2D-only group and the lowest concentrations in the sleeve gastrectomy in non-T2D group. The mean glucose profiles of all the groups showed a marked increase in interstitial glucose on breaking the fast, which was exaggerated in the two diabetes groups. The mean amplitude of glycemic excursions did not differ significantly within each group between fasting and non-fasting. No significant difference was noted in the fraction of time in the hypoglycemic range between the fasting and non-fasting periods in any group. Conclusion Intermittent fasting had no adverse effect on glycemic control in people with or without diabetes who had undergone sleeve gastrectomy.

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