Evaluation of continuous flash glucose monitoring in a pediatric ICU setting

Accuracy of continuous glucose monitoring systems in intensive care unit patients: a scoping review

PURPOSE

Glycemic control poses a challenge in intensive care unit (ICU) patients and dysglycemia is associated with poor outcomes. Continuous glucose monitoring (CGM) has been successfully implemented in the type 1 diabetes out-patient setting and renewed interest has been directed into the transition of CGM into the ICU. This scoping review aimed to provide an overview of CGM accuracy in ICU patients to inform future research and CGM implementation.

METHODS

We systematically searched PubMed and EMBASE between 5th of December 2023 and 21st of May 2024 and reported findings in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline for scoping reviews (PRISMA-ScR). We assessed studies reporting the accuracy of CGM in the ICU and report study characteristics and accuracy outcomes.

RESULTS

We identified 2133 studies, of which 96 were included. Most studies were observational (91.7%), conducted in adult patients (74%), in mixed ICUs (47.9%), from 2014 and onward, and assessed subcutaneous CGM systems (80%) using arterial blood samples as reference test (40.6%). Half of the studies (56.3%) mention the use of a prespecified reference test protocol. The mean absolute relative difference (MARD) ranged from 6.6 to 30.5% for all subcutaneous CGM studies. For newer factory calibrated CGM, MARD ranged from 9.7 to 20.6%. MARD for intravenous CGM was 5-14.2% and 6.4-13% for intraarterial CGM.

CONCLUSIONS

In this scoping review of CGM accuracy in the ICU, we found great diversity in accuracy reporting. Accuracy varied depending on CGM and comparator, and may be better for intravascular CGM and potentially lower during hypoglycemia.

Performance of Continuous Glucose Monitoring in Patients With Acute Respiratory Failure: A Prospective, Single-Center Observational Study

OBJECTIVE

Continuous glucose monitoring (CGM) may have benefits in achieving glycemic control in critically ill patients. The aim of this study was to assess the accuracy of the Freestyle Libre H (professional version similar to the Libre Pro) in patients with acute respiratory failure (ARF) in the intensive care unit (ICU).

METHODS

Fifty-two adult patients with ARF were selected. The performance of CGM was evaluated using the arterial blood glucose (aBG) and point-of-care (POC) glucose levels as the reference values. Numerical accuracy was evaluated by the mean absolute relative difference, Bland-Altman analysis, %15/15 (the percentage of CGM values within 15 mg/dL or 15% of reference values <100 or >100 mg/dL, respectively), %20/20, and %30/30. Clinical accuracy was assessed using the Clarke error grid analysis.

RESULTS

A total of 519 and 1504 pairs of aBG/CGM and POC/CGM glucose values were analyzed. The mean absolute relative difference values were 13.8% and 14.7%, respectively. The mean deviations of the Bland-Altman analysis were 0.82 mmol/L and 0.81 mmol/L. The proportions of CGM values within %15/15, %20/20, and %30/30 of the aBG values were 62.6%, 75.5%, and 92.4%, respectively; those within %15/15, %20/20, and %30/30 of the POC values were 57.1%, 72.9%, and 88.7%, respectively. The Clarke error grid analysis showed that 97.8% and 99.3% of the values were located in zone A + B. Additionally, the accuracy of CGM was not affected by general patient factors.

CONCLUSION

This study demonstrated that the accuracy of CGM in patients with ARF is lower than that in most outpatients and it is not affected by general patient factors. Whether CGM is beneficial to glucose management in the intensive care unit needs further evaluation.

Flash glucose monitoring system in gestational diabetes: a study of accuracy and usability

PURPOSE

Studies of flash glucose monitoring systems (FGMSs) in pregnancy are insufficient, especially in gestational diabetes (GD). Our aim was to evaluate Freestyle Libre's usability and accuracy (compared to self-monitoring of blood glucose [SMBG]) for GD patients in real-life conditions.

METHODS

This is a prospective study with pregnant women diagnosed with GD (n = 24 for the usability analysis; n = 19 for the accuracy analysis). The study duration was up to 28 days (lifetime of two sensors). Participants executed a minimum of four daily FGMS readings obtained immediately after capillary SMBG. Analytical accuracy was assessed with mean absolute relative difference (MARD) and mean absolute difference (MAD); clinical accuracy was assessed with Surveillance Error Grid (SEG). Usability was evaluated with a user acceptability questionnaire.

RESULTS

The mean pregestational BMI was 25.21 ± 5.15 kg/m2 (mean ± SD), the mean gestational age was 30.31 ± 2.02 weeks, and the mean glucose values were 76.63 ± 7.49 mg/dL. A total of 1339 SMBG-FGMS pairs of values were obtained. Analytical accuracy was good with an overall MARD of 14.07% and an in-target MARD of 13.79%. The number of SMBG-FMGS pairs for above-target values was low (122 of 1339) with an associated MARD of 17.95%. Clinical accuracy of the FGMS was demonstrated, with 94.4% of values in the no-risk or slight, lower risk zones of the SEG. FGMS accuracy was unaffected by pregestational BMI or gestational age. The user acceptability questionnaire showed high levels of satisfaction, with 95.8-100% preferring FGMS to SMBG. No unexpected or severe adverse effects occurred.

CONCLUSION

FGMS showed good performance in GD regarding accuracy and usability. Larger studies are needed to corroborate our results, verify the analytical accuracy of above-target values as this glucose range might lead to initiation or adjustment of pharmacological therapy, and ultimately establish definitive recommendations regarding prescription of FGMS for GD patients.

What, why and how to monitor blood glucose in critically ill patients

Critically ill patients are prone to high glycemic variations irrespective of their diabetes status. This mandates frequent blood glucose (BG) monitoring and regulation of insulin therapy. Even though the most commonly employed capillary BG monitoring is convenient and rapid, it is inaccurate and prone to high bias, overestimating BG levels in critically ill patients. The targets for BG levels have also varied in the past few years ranging from tight glucose control to a more liberal approach. Each of these has its own fallacies, while tight control increases risk of hypoglycemia, liberal BG targets make the patients prone to hyperglycemia. Moreover, the recent evidence suggests that BG indices, such as glycemic variability and time in target range, may also affect patient outcomes. In this review, we highlight the nuances associated with BG monitoring, including the various indices required to be monitored, BG targets and recent advances in BG monitoring in critically ill patients.

Accuracy of the intermittently scanned continuous glucose monitoring system in critically ill patients: a prospective, multicenter, observational study

OBJECTIVE

Continuous glucose monitoring (CGM) has the potential to improve glucose control in the intensive care unit (ICU) setting. We sought to evaluate the accuracy of the intermittently scanned CGM (isCGM) system in critically ill patients.

RESEARCH DESIGN AND METHODS

Adult patients were consecutively enrolled from three ICUs from August 2020 to January 2021. The performance of FreeStyle Libre Pro was evaluated against the venous blood glucose samples as a reference. Numerical accuracy was examined by the mean absolute relative difference (MARD), the Bland-Altman analysis, and the International Organization for Standardization criteria. Clinical accuracy was assessed by performing the Clarke and consensus error grid analysis.

RESULTS

A total of 122 patients were included and 3416 matched glucose pairs were analyzed. The overall MARD was 18.0%, and the highest MARD (33.1%) was observed in the hypoglycemic range (&lt;70 mg/dL). The Bland-Altman analysis revealed a mean bias of -11.7 mg/dL, with the 95% limits of agreement of -73.0 to 49.5 mg/dL. The percentages of isCGM glucose values within ±15%/15, ±20%/20, and ±30%/30 mg/dL were 49.8%, 64.7%, and 84.5%, respectively. The Clarke and consensus error grid analysis showed acceptable clinical accuracy with 98.5% and 98.8% of glucose values falling into zones A and B.

CONCLUSIONS

Our study demonstrated suboptimal overall accuracy of isCGM for critically ill patients. Whether the adjunctive use of isCGM could improve glucose management and health outcomes in the critically ill needs further investigation.

CLINICAL TRIAL REGISTRATION

ChiCTR2100042036, Chinese Clinical Trial Registry.

Flash glucose monitoring system in special situations

The management of diabetes mellitus (DM) requires maintaining glycemic control, and patients must keep their blood glucose levels close to the normal range to reduce the risk of microvascular complications and cardiovascular events. While glycated hemoglobin (A1C) is currently the primary measure for glucose management and a key marker for long-term complications, it does not provide information on acute glycemic excursions and overall glycemic variability. These limitations may even be higher in some special situations, thereby compromising A1C accuracy, especially when wider glycemic variability is expected and/or when the glycemic goal is more stringent. To attain adequate glycemic control, continuous glucose monitoring (CGM) is more useful than self-monitoring of blood glucose (SMBG), as it is more convenient and provides a greater amount of data. Flash Glucose Monitoring (isCGM /FGM) is a widely accepted option of CGM for measuring interstitial glucose levels in individuals with DM. However, its application under special conditions, such as pregnancy, patients on hemodialysis, patients with cirrhosis, during hospitalization in the intensive care unit and during physical exercise has not yet been fully validated. This review addresses some of these specific situations in which hypoglycemia should be avoided, or in pregnancy, where strict glycemic control is essential, and the application of isCGM/FGM could alleviate the shortcomings associated with poor glucose control or high glycemic variability, thereby contributing to high-quality care.

Accuracy and Stability of a Subcutaneous Flash Glucose Monitoring System in Critically Ill Patients

BACKGROUND

Flash glucose monitoring (FGM) systems can reduce glycemic variability and facilitate blood glucose management within the target range. However, in critically ill patients, only small (n < 30) studies have examined the accuracy of FGM and none have assessed the stability of FGM accuracy. We evaluated the accuracy and stability of FGM in critically ill patients.

METHOD

This was a single-center, retrospective observational study. We included a total of 116 critically ill patients who underwent FGM for glycemic control. The accuracy of FGM was assessed as follows using blood gas glucose values as a reference: (1) numerical accuracy using the mean absolute relative difference, (2) clinical accuracy using consensus error grid analysis, and (3) stability of accuracy assessing 14-day trends in consensus error grid distribution.

RESULTS

FGM sensors remained in situ for a median of 6 [4, 11] days. We compared 2014 pairs of measurements between the sensor and blood gas analysis. Glucose values from the sensor were consistently lower, with a mean absolute relative difference of 13.8% (±16.0%), than those from blood gas analysis. Consensus error grid analysis demonstrated 99.4% of the readings to be in a clinically acceptable accuracy zone. The accuracy of FGM was stable across the 14 days after device insertion.

CONCLUSIONS

FGM had acceptable reliability and accuracy to arterial blood gas analysis in critically ill patients. In addition, the accuracy of FGM persisted for at least 14 days. Our study promotes the potential usefulness of FGM for glycemic monitoring in critically ill patients.

Artificial intelligence in critically ill diabetic patients: current status and future prospects

Recent years have witnessed increasing numbers of artificial intelligence (AI) based applications and devices being tested and approved for medical care. Diabetes is arguably the most common chronic disorder worldwide and AI is now being used for making an early diagnosis, to predict and diagnose early complications, increase adherence to therapy, and even motivate patients to manage diabetes and maintain glycemic control. However, these AI applications have largely been tested in non-critically ill patients and aid in managing chronic problems. Intensive care units (ICUs) have a dynamic environment generating huge data, which AI can extract and organize simultaneously, thus analysing many variables for diagnostic and/or therapeutic purposes in order to predict outcomes of interest. Even non-diabetic ICU patients are at risk of developing hypo or hyperglycemia, complicating their ICU course and affecting outcomes. In addition, to maintain glycemic control frequent blood sampling and insulin dose adjustments are required, increasing nursing workload and chances of error. AI has the potential to improve glycemic control while reducing the nursing workload and errors. Continuous glucose monitoring (CGM) devices, which are Food and Drug Administration (FDA) approved for use in non-critically ill patients, are now being recommended for use in specific ICU populations with increased accuracy. AI based devices including artificial pancreas and CGM regulated insulin infusion system have shown promise as comprehensive glycemic control solutions in critically ill patients. Even though many of these AI applications have shown potential, these devices need to be tested in larger number of ICU patients, have wider availability, show favorable cost-benefit ratio and be amenable for easy integration into the existing healthcare systems, before they become acceptable to ICU physicians for routine use.

The Effect of Various, Everyday Practices on Glucose Levels in Critically Ill Children

BACKGROUND

To evaluate the effect of various, everyday intensive care unit (ICU) practices on glucose levels in critically ill pediatric patients with the use of a continuous glucose monitoring system.

METHODS

Seventeen sensors were placed in 16 pediatric patients (8 male). All therapeutic and diagnostic interventions were recorded and 15 minutes later, a flash glucose measurement was obtained by swiping the sensor with a reader. Glucose difference was calculated as the glucose value 15 minutes after the intervention minus the mean daily glucose value for each individual patient. Additionally, the consciousness status of the patient (awake or sedated) was recorded.

RESULTS

Two hundred and five painful skin interventions were recorded. The mean difference of glucose values was higher by 1.84 ± 14.76 mg/dL (95% CI: -0.19 to 3.87 mg/dL, P = .076). However, when patients were categorized regarding their consciousness level, mean glucose difference was significantly higher in awake state than in sedated patients (4.76 ± 28.07 vs -2.21 ± 15.77 mg/dL, P < .001). Six hundred forty-nine interventions involving the respiratory system were recorded. Glucose difference during washings proved to be significantly higher than the ones during simple suctions (4.74 ± 14.18 mg/dL vs 0.32 ± 18.22 mg/dL, P = .016). Finally, glucose difference in awake patients was higher by 3.66 ± 13.91 mg/dL compared to glucose difference of -2.25 ± 21.07 mg/dL obtained during respiratory intervention in sedated patients.

CONCLUSIONS

Diagnostic and therapeutic procedures in the ICU, especially when performed in an awake state, exacerbate the stress and lead to a significant rise in glucose levels.

Continuous Glucose Monitoring in the Hospital

Continuous glucose monitors (CGMs) have suddenly become part of routine care in many hospitals. The coronavirus disease 2019 (COVID-19) pandemic has necessitated the use of new technologies and new processes to care for hospitalized patients, including diabetes patients. The use of CGMs to automatically and remotely supplement or replace assisted monitoring of blood glucose by bedside nurses can decrease: the amount of necessary nursing exposure to COVID-19 patients with diabetes; the amount of time required for obtaining blood glucose measurements, and the amount of personal protective equipment necessary for interacting with patients during the blood glucose testing. The United States Food and Drug Administration (FDA) is now exercising enforcement discretion and not objecting to certain factory-calibrated CGMs being used in a hospital setting, both to facilitate patient care and to obtain performance data that can be used for future regulatory submissions. CGMs can be used in the hospital to decrease the frequency of fingerstick point of care capillary blood glucose testing, decrease hyperglycemic episodes, and decrease hypoglycemic episodes. Most of the research on CGMs in the hospital has focused on their accuracy and only recently outcomes data has been reported. A hospital CGM program requires cooperation of physicians, bedside nurses, diabetes educators, and hospital administrators to appropriately select and manage patients. Processes for collecting, reviewing, storing, and responding to CGM data must be established for such a program to be successful. CGM technology is advancing and we expect that CGMs will be increasingly used in the hospital for patients with diabetes.

Hospital care: improving outcomes in type 1 diabetes

PURPOSE OF REVIEW

Caring for patients with type 1 diabetes (T1D) in the hospital presents unique challenges. This review provides an update on significant issues relevant to the inpatient management of T1D. Topics include trends in diabetic ketoacidosis (DKA), hypoglycemia, and adapting ambulatory technologies for inpatient use.

RECENT FINDINGS

Rates of DKA in the United States are rising. Although socioeconomic status, health insurance coverage, and hemoglobin A1c are persistently associated with DKA in individuals with T1D, newer risk factors have also emerged. These include the off-label use of sodium-glucose cotransporter inhibitor medications, immune checkpoint inhibitor-induced diabetes, and infection with severe acute respiratory syndrome coronavirus 2. Hypoglycemia is common among hospitalized patients with T1D. Use of validated hypoglycemia risk prediction models and multidisciplinary care initiatives can reduce the risk of inpatient hypoglycemia. Finally, continuous glucose monitoring is being adapted for use in the hospital setting and has shown promise during the coronavirus disease 2019 (COVID-19) pandemic.

SUMMARY

Evidence-based treatment algorithms, risk prediction calculators, multidisciplinary interventions, and wearable technology hold promise for improved outcomes in hospitalized patients with T1D.

Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline

This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes.

Safety and Accuracy of Factory-Calibrated Continuous Glucose Monitoring in Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation

Background: Pediatric patients undergoing hematopoietic stem cell transplantation (HSCT) may be at risk for malglycemia and adverse outcomes, including infection, prolonged hospital stays, organ dysfunction, graft-versus-host-disease, delayed hematopoietic recovery, and increased mortality. Continuous glucose monitoring (CGM) may aid in describing and treating malglycemia in this population. However, no studies have demonstrated safety, tolerability, or accuracy of CGM in this uniquely immunocompromised population. Materials and Methods: A prospective observational study was conducted, using the Abbott Freestyle Libre Pro, in patients aged 2-30 undergoing HSCT at Children's Hospital Colorado to evaluate continuous glycemia in this population. CGM occurred up to 7 days before and 60 days after HSCT, during hospitalization only. In a secondary analysis of this data, blood glucoses collected during routine HSCT care were compared with CGM values to evaluate accuracy. Adverse events and patient refusal to wear CGM device were monitored to assess safety and tolerability. Results: Participants (n = 29; median age 13.1 years, [interquartile range] [4.7, 16.6] years) wore 84 sensors for an average of 25 [21.5, 30.0] days per participant. Paired serum-sensor values (n = 893) demonstrated a mean absolute relative difference of 20% ± 14% with Clarke Error Grid analysis showing 99% of pairs in the clinically acceptable Zones (A+B). There were four episodes of self-limited bleeding (4.8% of sensors); no other adverse events occurred. Six patients (20.7%) refused subsequent CGM placements. Conclusions: CGM use appears safe and feasible although with suboptimal accuracy in the hospitalized pediatric HSCT population. Few adverse events occurred, all of which were low grade.

Accuracy and stability of an arterial sensor for glucose monitoring in a porcine model using glucose clamp technique

Intravascular glucose sensors have the potential to improve and facilitate glycemic control in critically ill patients and might overcome measurement delay and accuracy issues. This study investigated the accuracy and stability of a biosensor for arterial glucose monitoring tested in a hypo- and hyperglycemic clamp experiment in pigs. 12 sensors were tested over 5 consecutive days in 6 different pigs. Samples of sensor and reference measurement pairs were obtained every 15 minutes. 1337 pairs of glucose values (range 37–458 mg/dl) were available for analysis. The systems met ISO 15197:2013 criteria in 99.2% in total, 100% for glucose <100 mg/dl (n = 414) and 98.8% for glucose ≥100 mg/dl (n = 923). The mean absolute relative difference (MARD) during the entire glycemic range of all sensors was 4.3%. The MARDs within the hypoglycemic (<70 mg/dl), euglycemic (≥70–180 mg/dl) and hyperglycemic glucose ranges (≥180 mg/dl) were 6.1%, 3.6% and 4.7%, respectively. Sensors indicated comparable performance on all days investigated (day 1, 3 and 5). None of the systems showed premature failures. In a porcine model, the performance of the biosensor revealed a promising performance. The transfer of these results into a human setting is the logical next step.