Intermittent Glucose Monitoring Research Articles

Continuous and Intermittent Glucose Monitoring in 2023.

Continuous and Intermittent Glucose Monitoring in 2023.

Continuous Glucose Monitoring Systems and the Efficacy of Acarbose Treatment in Cystic Fibrosis-related Dysglycemia.

Early detection of glycemic dysregulation and optimization of glycemic control at cystic fibrosis related diabetes (CFRD) is associated with improved pulmonary function and decreased mortality. The standard 2-hour oral glucose tolerance test (OGTT) is the current routine screening test for CFRD. However, hyperglycemia can be detected by continuous glucose monitoring systems (CGMS) in patients with normal OGTT evaluation. High-dose acarbose is an important alternative, in the treatment of glycemic dysregulation especially accompanied by hypoglycemia. A 7-year-old boy with cystic fibrosis (CF) presented with hyperglycemia. Hypoglycemia (29 mg/dL) and hyperglycemia (400 mg/dL) were demonstrated by OGTT and intermittent CGM (iCGMS). Thickener was added to nutritional solutions and acarbose was initiated as 3x12.5 mg /dose and increased to 6x25 mg without any side effects. On the 20th day of treatment, glycemic dysregulation was resolved. In the early detection of CFRD, screening with OGTT after the age of 10 is insufficient; therefore, routine use of continous or intermittent glucose monitoring systems should be considered. In addition, in CFRDs with severe hypoglycemia, acarbose is an important alternative in the high and increased dose range.

Impact on glucometric variables and quality of life of the advanced hybrid closed-loop system in pediatric and adolescent type 1 diabetes.

In recent years, technological advances in the field of diabetes have revolutionized the management, prognosis, and quality of life of diabetes patients and their environment. The aim of our study was to evaluate the impact of implementing the MiniMed 780G closed-loop system in a pediatric and adolescent population previously treated with a continuous subcutaneous insulin infusion pump and intermittent glucose monitoring. Data were collected from 28 patients with type 1 diabetes aged 6 to 17 years, with a follow-up of 6 months. We included both glucometric and quality of life variables, as well as quality of life in primary caregivers. Metabolic control variables were assessed at baseline (before system change) and at different cutoff points after initiation of the closed-loop system (48 hours, 7 days, 14 days, 21 days, 1 month, 3 months, 6 months). Time in range 70-180 mg/dL increased from 59.44% at baseline to 74.29% in the first 48 hours after automation of the new system, and this improvement was maintained at the other cutoff points, as was time in hyperglycemia 180-250 mg/dL (24.44% at baseline to 18.96% at 48 hours) and >250 mg/dL (11.71% at baseline to 3.82% at 48 hours). Our study showed an improvement in time in range and in all time spent in hyperglycemia from the first 48 hours after the automation of the system, which was maintained at 6 months.

Continuous and Intermittent Glucose Monitoring in 2022.

Continuous and Intermittent Glucose Monitoring in 2022.

IDF21-0272 Glycemic Variability in patients with SARS-CoV-2 admitted to the ICU

Background: Glycemic variability (GV) is the measure of fluctuations in plasma glucose. An association between mortality and GV is evident in patients in the Intensive Care Unit (ICU). There are several indices for evaluating GV, including the coefficient of variation (CV). The evidence of GV as a possible prognostic factor in ICU patients diagnosed with SARS-CoV-2 is scarce and heterogeneous. Aim: Determine the probable impact of Glycemic Variability in patients with SARS-CoV-2 admitted in the ICU. Method: An observational, descriptive and retrospective study was conducted. Glycemic variability was evaluated in 324 patients, admitted to the ICU with diagnosis of Sars-CoV-2 between March - December 2020 at Hospital General Plaza de la Salud. Analysis included: sociodemographic, comorbidities, length of hospital stay, need for ventilatory support and mortality. For the calculation of the GV, “EasyGV'' version 9.0, a free software of the University of Oxford, was used. The exclusion criteria were intermittent glucose monitoring of less than 7 determinations and the diagnosis of Sars-CoV-2 without PCR. Results: A total of 324 patients (average age 62.7±14.9 years; 65.4% men; 34.6% women) were analyzed. They were divided into groups with low GV, (CV<36%; 68.8%, N=223) and with high GV, (CV>36%; 31.1%, N=101), patients with high GV had a higher frequency of Type 2 Diabetes Mellitus with 78.2% (79), compared to the group with low GV with 39.0% (87), renal insufficiency was present in the group with low GV in 17.4% (39) vs 41.5% (42) in the group with high GV. The average sum of comorbidities was 2.03 in the group with low GV and 2.3 in the group with high GV. Frequency of mortality in group with high GV, was 47.5% (48) vs 29.1% (65) in the group with low GV. There was no significant difference in the total number of days hospitalized in the ICU, however, in the total number of days hospitalized, patients with low GV had an average of 9.4 ±5.8 days, compared to the group with high GV 11.2 ±6.6 days. The need for ventilatory support in the group with high GV was 37.6% (38), compared to the group with low GV 28.2% (63). The APACHE had an average score in the group with Low GV of a 9.13 vs 9.6 of the high GV group. The SOFA had an average score in the group with Low GV of a 6.7 against a 6.6 of the high GV group. Discussion: For Chao et al, 2020, the mortality results in patients admitted to the ICU were similar to those of this study, 36.7% (high GV Group) vs. 26.6% (Low GV Group). It is necessary to include intermittent glucose monitoring in the follow-up of hospitalized patients due to its impact on their outcome, after showing that a CV ≥36% in patients diagnosed with SARS-CoV-2 resulted in a greater need for ventilatory support, longer hospital stay and greater mortality. Further research is required to evaluate GV as a prognostic factor to be considered.

Continuous and Intermittent Glucose Monitoring in 2021.

Continuous and Intermittent Glucose Monitoring in 2021.

Continuous and Intermittent Glucose Monitoring in 2020.

Continuous and Intermittent Glucose Monitoring in 2020.

Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes.

The purpose of this study was to describe objective sleep-wake characteristics and glycemia over 7-14 days in young adults with type 1 diabetes. In addition, person-level associations among objective sleep-wake characteristics (total sleep time, sleep variability, and sleep fragmentation index), daytime sleepiness, and glycemia (glycemic control and glucose variability) were examined. In this cross-sectional study, objective sleep-wake characteristics were measured via actigraphy and glucose variability via continuous glucose monitoring over 6-14 days. At baseline, participants completed the Psychomotor Vigilance Test, the Trail Making Test, and questionnaires on daytime sleepiness, sleep quality, and sleep disturbance including sleep diaries. Forty-six participants (mean age, 22.3 ± 3.2 years) wore a wrist actigraph and underwent continuous glucose monitoring concurrently for 6-14 days. Greater sleep variability was directly associated with greater glucose variability (mean of daily differences; r = .33, P = .036). Higher daytime sleepiness was directly associated with greater glucose variability (mean of daily differences; r = .50, P = .001). The association between sleep variability and glucose variability (mean of daily differences) was no longer significant when accounting for daytime sleepiness and controlling for type 1 diabetes duration (P > .05). A higher sleep fragmentation index was associated with greater glucose variability (B = 1.27, P = .010, pr2 = 0.40) after controlling for type 1 diabetes duration and accounting for higher daytime sleepiness. Sleep-wake variability, sleep fragmentation, daytime sleepiness, and the associations with glycemia are new dimensions to consider in young adults with type 1 diabetes. Sleep habits in this population may explain higher glucose variability, and optimizing sleep may improve overall diabetes management. Griggs S, Hickman RL Jr, Strohl KP, Redeker NS, Crawford SL, Grey M. Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes. J Clin Sleep Med. 2021;17(9):1865-1874.

Continuous and Intermittent Glucose Monitoring in 2019.

Continuous and Intermittent Glucose Monitoring in 2019.

Techniques of monitoring blood glucose during pregnancy for women with pre-existing diabetes.

There are a number of ways of monitoring blood glucose in women with diabetes during pregnancy, with self-monitoring of blood glucose (SMBG) recommended as a key component of the management plan. No existing systematic reviews consider the benefits/effectiveness of different techniques of blood glucose monitoring on maternal and infant outcomes among pregnant women with pre-existing diabetes. The effectiveness of the various monitoring techniques is unclear. This review is an update of a review that was first published in 2014 and subsequently updated in 2017. To compare techniques of blood glucose monitoring and their impact on maternal and infant outcomes among pregnant women with pre-existing diabetes. For this update, we searched Cochrane Pregnancy and Childbirth's Trials Register, ClinicalTrials.gov, the WHO International Clinical Trials Registry Platform (ICTRP) (1 November 2018), and reference lists of retrieved studies. Randomised controlled trials (RCTs) and quasi-RCTs comparing techniques of blood glucose monitoring including SMBG, continuous glucose monitoring (CGM), automated telemedicine monitoring or clinic monitoring among pregnant women with pre-existing diabetes mellitus (type 1 or type 2). Trials investigating timing and frequency of monitoring were also eligible for inclusion. RCTs using a cluster-randomised design were eligible for inclusion but none were identified. Two review authors independently assessed study eligibility, extracted data and assessed the risk of bias of included studies. Data were checked for accuracy. The quality of the evidence was assessed using the GRADE approach. This review update includes a total of 12 trials (863) women (792 women with type 1 diabetes and 152 women with type 2 diabetes). The trials took place in Europe, the USA and Canada. Three of the 12 included studies are at low risk of bias, eight studies are at moderate risk of bias, and one study is at high risk of bias. Four trials reported that they were provided with the continuous glucose monitors free of charge or at a reduced cost by the manufacturer.Continuous glucose monitoring (CGM) versus intermittent glucose monitoring, (four studies, 609 women)CGM may reduce hypertensive disorders of pregnancy (pre-eclampsia and pregnancy-induced hypertension) (risk ratio (RR) 0.58, 95% confidence interval (CI) 0.39 to 0.85; 2 studies, 384 women; low-quality evidence), although it should be noted that only two of the four relevant studies reported data for this composite outcome. Conversely, this did not translate into a clear reduction for pre-eclampsia (RR 0.65, 95% CI 0.39 to 1.08; 4 studies, 609 women, moderate-quality evidence). There was also no clear reduction in caesarean section (average RR 0.94, 95% CI 0.75 to 1.18; 3 studies, 427 women; I2 = 41%; moderate-quality evidence) or large-for-gestational age (average RR 0.84, 95% CI 0.57 to 1.26; 3 studies, 421 women; I2 = 70%; low-quality evidence) with CGM. There was not enough evidence to assess perinatal mortality (RR 0.82, 95% CI 0.05 to 12.61, 71 infants, 1 study; low-quality evidence), or mortality or morbidity composite (RR 0.80, 95% CI 0.61 to 1.06; 1 study, 200 women) as the evidence was based on single studies of low quality. CGM appears to reduce neonatal hypoglycaemia (RR 0.66, 95% CI 0.48 to 0.93; 3 studies, 428 infants). Neurosensory disability was not reported.Other methods of glucose monitoringFor the following five comparisons, self-monitoring versus a different type of self-monitoring (two studies, 43 women); self-monitoring at home versus hospitalisation (one study, 100 women), pre-prandial versus post-prandial glucose monitoring (one study, 61 women), automated telemedicine monitoring versus conventional system (three studies, 84 women), and constant CGM versus intermittent CGM (one study, 25 women), it is uncertain whether any of the interventions has any impact on any of our GRADE outcomes (hypertensive disorders of pregnancy, caesarean section, large-for-gestational age) because the quality of the evidence was found to be very low. This was due to evidence largely being derived from single trials, with design limitations and limitations with imprecision (wide CIs, small sample sizes, and few events). There was not enough evidence to assess perinatal mortality and neonatal mortality and morbidity composite. Other important outcomes, such as neurosensory disability, were not reported in any of these comparisons. Two new studies (406 women) have been incorporated to one of the comparisons for this update. Although the evidence suggests that CGM in comparison to intermittent glucose monitoring may reduce hypertensive disorders of pregnancy, this did not translate into a clear reduction for pre-eclampsia, and so this result should be viewed with caution. No differences were observed for other primary outcomes for this comparison. The evidence base for the effectiveness of other monitoring techniques analysed in the other five comparisons is weak and based on mainly single studies with very low-quality evidence. Additional evidence from large well-designed randomised trials is required to inform choices of other glucose monitoring techniques and to confirm the effectiveness of CGM.

Near-Continuous Glucose Monitoring Makes Glycemic Control Safer in ICU Patients.

Tight glycemic control using intermittent blood glucose measurements is associated with a risk of hypoglycemia. Glucose concentrations can now be measured near continuously (every 5-15 min). We assessed the quality and safety of glycemic control guided by a near-continuous glucose monitoring system in ICU patients. Prospective, cluster-randomized, crossover study. Thirty-five-bed medico-surgical department of intensive care with four separate ICUs. Adult patients admitted to the department and expected to stay for at least 3 days were considered for inclusion if they had persistent hyperglycemia (blood glucose > 150 mg/dL) up to 6 hours after admission and/or were receiving insulin therapy. A peripheral venous catheter was inserted in all patients and connected to a continuous glucose monitoring sensor (GlucoClear; Edwards Lifesciences, Irvine, CA). The four ICUs were randomized in pairs in a crossover design to glycemic control using unblinded or blinded continuous glucose monitoring monitors. The insulin infusion rate was adjusted to keep blood glucose between 90 and 150 mg/dL using the blood glucose values displayed on the continuous glucose monitor (continuous glucose monitoring group-unblinded units) or according to intermittent blood glucose readings (intermittent glucose monitoring group-blinded units). The quality and safety of glycemic control were assessed using the proportion of time in range, the frequency of blood glucose less than 70 mg/dL, and the time spent with blood glucose less than 70 mg/dL (TB70), using blood glucose values measured by the continuous glucose monitoring device. Seventy-seven patients were enrolled: 39 in the continuous glucose monitoring group and 38 in the intermittent glucose monitoring group. A total of 43,107 blood glucose values were recorded. The time in range was similar in the two groups. The incidence of hypoglycemia (8/39 [20.5%] vs 15/38 [39.5%]) and the TB70 (0.4% ± 0.9% vs 1.6% ± 3.4%; p < 0.05) was lower in the continuous glucose monitoring than in the intermittent glucose monitoring group. Use of a continuous glucose monitoring-based strategy decreased the incidence and severity of hypoglycemia, thus improving the safety of glycemic control.

Comparison of continuous and intermittent glucose monitoring systems in a dog with diabetic ketoacidosis: a case report

A Miniature schnauzer (12 years old, neutered male) was referred for lethargy, anorexia, and oral bleeding. On initial evaluation, severe hyperglycaemia (blood glucose concentration of 34.9 mmol/l), ketonuria, systemic inflammation (fever, panting, left-shift neutrophilia, and a high C-reactive protein level of 980.97 nmol/l, abnormal pancreatic lipase immunoreactivity, and periodontitis were found. With consideration of possible insulin resistance, blood glucose (BG) levels were monitored using a portable glucose meter (q 1–3 h) and a continuous glucose monitoring system (CGMS) for 72 h (three consecutive trials); intensive insulin therapy was initiated using regular insulin (2.2 IU/kg intravenously). The insulin doses needed, based on the nadir, peak, and duration of insulin action from a traditional intermittent glucose curve were higher than those based on the CGMS results. Meanwhile, transient hyperglycaemic and hypoglycaemic periods, occurring between the intermittent measurements, were easily identified with the CGMS. Therefore, insulin resistance and the Somogyi phenomenon are less likely to occur with use of the CGMS than with intermittent BG measurements. By comparing data from a CGMS to those from an intermittent portable BG measurement system, this case report emphasises the importance and usefulness of a CGMS.

Accuracy, reliability, feasibility and nurse acceptance of a subcutaneous continuous glucose management system in critically ill patients: a prospective clinical trial.

BackgroundContinuous glucose monitoring (CGM) has not yet been implemented in the intensive care unit (ICU) setting. The purpose of this study was to evaluate reliability, feasibility, nurse acceptance and accuracy of the Medtronic Sentrino® CGM system in critically ill patients.Methods Sensors were inserted into the subcutaneous tissue of the patient’s thigh, quantifying interstitial glucose concentration for up to 72 h per sensor. Reliability and feasibility analysis included frequency of data display, data gaps and reasons for sensor removal. We surveyed nurse acceptance in a questionnaire. For the accuracy analysis, we compared sensor values to glucose values obtained via blood gas analysis. Potential benefits of CGM were investigated in intra-individual analyses of factors, such as glycemic variability or time in target range achieved with CGM compared to that achieved with intermittent glucose monitoring.ResultsThe device generated 68,655 real-time values from 31 sensors in 20 critically ill patients. 532 comparative blood glucose values were collected. Data were displayed during 32.5 h [16.0/62.4] per sensor, which is 45.1 % of the expected time of 72 h and 84.8 % of 37.9 h actual monitoring time. 21 out of 31 sensors were removed prematurely. 79.1 % of the nursing staff rated the device as not beneficial; the response rate was one-third. Mean absolute relative difference was 15.3 % (CI 13.5–17.0 %). Clarke error grid: 76.9 % zone A, 21.6 % zone B, 0.2 % zone C, 0.9 % zone D, 0.4 % zone E. Bland–Altman plot: mean bias +0.53 mg/dl, limits of agreement +64.6 and −63.5 mg/dl. Accuracy deteriorated during elevated glycemic variability and in the hyperglycemic range. There was no reduction in dysglycemic events during CGM compared to 72 h before and after CGM. If CGM was measuring accurately, it identified more hyperglycemic events when compared to intermittent measurements. This study was not designed to evaluate potential benefits of CGM on glucose control.ConclusionsThe subcutaneous CGM system did not perform with satisfactory accuracy, feasibility, or nursing acceptance when evaluated in 20 medical-surgical ICU patients. Low point accuracy and prolonged data gaps significantly limited the potential clinical usefulness of the CGM trend data. Accurate continuous data display, with a MARD < 14 %, showed potential benefits in a subgroup of our patients.Trial registration NCT02296372; Ethic vote Charité EA2/095/14Electronic supplementary materialThe online version of this article (doi:10.1186/s13613-016-0167-z) contains supplementary material, which is available to authorized users.

Evaluation of the performance of a new OptiScanner™ 5000 system for an intermittent glucose monitoring

BackgroundMid-infrared spectral technology has shown a high degree of promise in detecting glucose in plasma. OptiScan Biomedical has developed a glucose monitor based on mid-infrared spectroscopy that withdraws blood samples and measures plasma glucose. The objective of this study was to evaluate the accuracy and performance of the OptiScanner™ 5000 system on different pools of blood. MethodsThis study was performed to validate the blood glucose measurements obtained with the OptiScanner™ 5000 by comparing them to Central Laboratory glucose measurements (VITROS® 5600 Integrated System) as a comparative method across a broad range of glucose values over a three day period to obtain 80–90 paired measurements. ResultsA total of 81 paired measurements, distributed between 33 and 320mg/100mL of glucose, were performed. The aggregate data points were within International Organization for Standardization standards, with 100% of the glucose values within ±15%. ConclusionsThe current study suggests that a mid-IR fixed-wavelength system (OptiScanner) can measure glucose accurately across a wide range of glucose values in plasma of ICU patients.

Clinical review: Consensus recommendations on measurement of blood glucose and reporting glycemic control in critically ill adults.

The management reporting and assessment of glycemic control lacks standardization. The use of different methods to measure the blood glucose concentration and to report the performance of insulin treatment yields major disparities and complicates the interpretation and comparison of clinical trials. We convened a meeting of 16 experts plus invited observers from industry to discuss and where possible reach consensus on the most appropriate methods to measure and monitor blood glucose in critically ill patients and on how glycemic control should be assessed and reported. Where consensus could not be reached, recommendations on further research and data needed to reach consensus in the future were suggested. Recognizing their clear conflict of interest, industry observers played no role in developing the consensus or recommendations from the meeting. Consensus recommendations were agreed for the measurement and reporting of glycemic control in clinical trials and for the measurement of blood glucose in clinical practice. Recommendations covered the following areas: How should we measure and report glucose control when intermittent blood glucose measurements are used? What are the appropriate performance standards for intermittent blood glucose monitors in the ICU? Continuous or automated intermittent glucose monitoring - methods and technology: can we use the same measures for assessment of glucose control with continuous and intermittent monitoring? What is acceptable performance for continuous glucose monitoring systems? If implemented, these recommendations have the potential to minimize the discrepancies in the conduct and reporting of clinical trials and to improve glucose control in clinical practice. Furthermore, to be fit for use, glucose meters and continuous monitoring systems must match their performance to fit the needs of patients and clinicians in the intensive care setting.See related commentary by Soto-Rivera and Agus, http://ccforum.com/content/17/3/155

Is There a Difference in Pregnancy and Glycemic Outcome in Patients with Type 1 Diabetes on Insulin Pump with Constant or Intermittent Glucose Monitoring? A Pilot Study

The aim of the study is to describe glycemic and insulin outcomes by trimester and maternal and fetal outcome in patients with type 1 diabetes using an insulin pump with constant or intermittent continuous glucose monitoring (CGM). Twenty-five women with type 1 diabetes with newly diagnosed pregnancy were treated with insulin pump therapy (Medtronic 722, Medtronic Minimed, Northridge, CA) for at least 1 year. Insulin pump and CGM (Medtronic Paradigm Real-Time) were implemented at least 3 months before conception. Patients were randomized in two groups: constant CGM group, 12 patients on insulin pump with glucose sensor, 24 h/day; and intermittent CGM group, 13 patients on insulin pump with intermittent glucose sensor, 14 days/month. The following parameters were analyzed: glycosylated hemoglobin (HbA1c), mean blood glucose, insulin requirement (in IU/kg/day), weight gain, severe hypoglycemic events, diabetic ketoacidosis, macrosomia, cesarean section, and neonatal hypoglycemia. Both groups achieved good glucose control during their pregnancies (P<0.05): 6.78±1.3% and 6.92±0.9% at the beginning of the study compared with 6.14±0.9% (constant CGM group) and 6.23±0.6% (intermittent CGM group) at the end of the study (last HbA1c before delivery). There was no significant decrease of HbA1c between the two groups. The constant CGM group had a significantly lower A1c in the first trimester compared with the intermittent CGM group. Maternal and fetal outcome did not show a significant difference between the two groups. Insulin pump therapy together with constant or intermittent CGM can improve diabetes control and pregnancy outcome in type 1 diabetes. The quality of the glucose profile at conception was the important factor for pregnancy outcome.