Continuous glucose monitoring empowers adolescents to take responsibility of diabetes management.

BACKGROUND: Managing diabetes is especially challenging for adolescents, and they often struggle to believe they can manage the condition. Illness perception has been widely associated with better diabetes management outcomes, but the influence of continuous glucose monitoring (CGM) on adolescents has been largely neglected. AIM: The study aimed to explore the illness perception of a group of adolescents living with type 1 diabetes (T1D) using CGM. SETTING: The study was conducted at a medical centre that provides diabetes care services to youth living with T1D in Parktown, South Africa. METHODS: A qualitative research approach using semi-structured online interviews was used to gather data that was thematically analysed. RESULTS: Themes emerging from the data confirmed that CGM creates a sense of control over diabetes management as blood glucose measures were more visible. A sense of normalcy was established as CGM influences a new routine and a way of life, integrating diabetes into a young person's identity. Despite the users' awareness of being different due to diabetes management, CGM assisted in creating a sense of belonging, contributing to developing a better quality of life. CONCLUSION: Findings of this study support the use of CGM as a means of empowering adolescents struggling with diabetes management to achieve better treatment outcomes. The important role of illness perception in facilitating this change was also evident.Contribution: By listening to the adolescent's voice, CGM was identified as a possible intervention to empower adolescents to improve diabetes management.

Nursing Perspectives on the Use of Continuous Glucose Monitoring in the Intensive Care Unit.

BACKGROUND: The COVID-19 pandemic necessitated rapid implementation of continuous glucose monitoring (CGM) in the intensive care unit (ICU). Although rarely reported, perceptions from nursing staff who used the systems are critical for successful implementation and future expanded use of CGM in the inpatient setting. METHODS: A 22-item survey focused on CGM use was distributed to ICU nurses at two large academic medical centers in the United States in 2022. Both institutions initiated inpatient CGM in the spring of 2020 using the same CGM+point of care (POC) hybrid protocol. The survey employed a 1- to 5-point Likert scale regarding CGM sensor insertion, accuracy, acceptability, usability, training, and perceptions on workload. RESULTS: Of the 71 surveys completed, 68 (96%) nurses reported they cared for an ICU patient on CGM and 53% reported they had independently performed CGM sensor insertion. The ICU nurses overwhelmingly reported that CGM was accurate, reduced their workload, provided safer patient care, and was preferred over POC glucose testing alone. Interestingly, nearly half of nurses (49%) reported that they considered trend arrows in dosing decisions although trends were not included in the CGM+POC hybrid protocol. Nurses received training through multiple modalities, with the majority (80%) of nurses reporting that CGM training was sufficient and prepared them for its use. CONCLUSION: These results confirm nursing acceptance and preference for CGM use within a hybrid glucose monitoring protocol in the ICU setting. These data lay a blueprint for successful implementation and training strategies for future widespread use.

The patient-centered diabetes management during the COVID-19 pandemic.

Since December 2019, in the fight against the coronavirus disease 2019 (COVID-19) pandemic, we observed that glycemic control in people with diabetes is easily affected by lifestyle changes. To maintain a good health condition, a patient-centered approach with mental support and close monitoring is required. For these, telemedicine and online continuous glucose monitoring (CGM), are effective systems. Therefore, based on our experience during the two-year period, we reviewed the literature for appropriate actions required for the management of diabetes to prevent COVID-19 infection and avoid unfavorable outcomes in COVID-19 cases. Once infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is a high risk of a poor prognosis in patients with diabetes. Glucocorticoid therapy in severe COVID-19 cases leads to further hyperglycemia. Since good glycemic control has been shown to improve outcomes, strict glycemic control using CGM is recommended. Using CGM data, insulin can be adequately titrated without causing hypoglycemia, and remote data monitoring can reduce the risk of infection for health care professionals, by reducing the frequency of patient contact. Among patients with COVID-19, some are found to have newly-diagnosed diabetes at admission. Those newly diagnosed patients present with a higher risk of poor prognosis compared to those with pre-existing diabetes. Therefore, glycemic status should be evaluated in all patients with COVID-19 admitted to hospitals.

Use of a Continuous Glucose Monitoring System in High-Risk Hospitalized Noncritically Ill Patients With Diabetes After Cardiac Surgery and During Their Transition of Care From the Intensive Care Unit During COVID-19: A Pilot Study.

OBJECTIVE: Continuous glucose monitoring (CGM) has demonstrated benefits in managing inpatient diabetes. We initiated this single-arm pilot feasibility study during the COVID-19 pandemic in 11 patients with diabetes to determine the feasibility and accuracy of real-time CGM in patients who underwent cardiac surgery and whose care was being transitioned from the intensive care unit. METHODS: A Clarke error grid analysis was used to compare CGM and point-of-care measurements. The mean absolute relative difference (MARD) of the paired measurements was calculated to assess the accuracy of CGM for glucose measurements during the first 24 hours on CGM, the remaining time on CGM, and for different chronic kidney disease (CKD) strata. RESULTS: Overall MARD between point-of-care and CGM measurements was 14.80%. MARD for patients without CKD IV and V with an estimated glomerular filtration rate (eGFR) of ≥20 mL/min/1.73 m2 was 12.13%. Overall, 97% of the CGM values were within the no-risk zone of the Clarke error grid analysis. For the first 24 hours, a sensitivity analysis of the overall MARD for all patients and those with an eGFR of ≥20 mL/min/1.73 m2 was 15.42% ± 14.44% and 12.80% ± 7.85%, respectively. Beyond the first 24 hours, overall MARD for all patients and those with an eGFR of ≥20 mL/min/1.73 m2 was 14.54% ± 13.21% and 11.86% ± 7.64%, respectively. CONCLUSION: CGM has shown great promise in optimizing inpatient diabetes management in the noncritical care setting and after the transition of care from the intensive care unit with high clinical reliability and accuracy. More studies are needed to further assess CGM in patients with advanced CKD.

Glycaemic control during the lockdown for COVID-19 in adults with type 1 diabetes: A meta-analysis of observational studies.

AIMS: To assess the effects of lockdown due to COVID-19 pandemic on glucose metrics, measured by glucose monitoring systems, in adult individuals with type 1 diabetes. METHODS: We conducted a systematic literature search for English language articles from MEDLINE, Scopus and Web of Science up to February 28, 2021, using "diabetes", "lockdown", and "glucose" as key search terms. Time in range (TIR) was the main outcome; other metrics were time above range (TAR), time below range (TBR), mean blood glucose (MBG) and its variability (%CV), estimated HbA1c (eA1c) or glucose management indicator (GMI). RESULTS: Seventeen studies for a total of 3,441 individuals with type 1 diabetes were included in the analysis. In the lockdown period, TIR 70-180 mg/dl increased by 3.05% (95% CI 1.67-4.43%; p < 0.0001) while TAR (>180 mg/dL and > 250 mg/dL) declined by 3.39% (-5.14 to -1.63%) and 1.96% (-2.51 to -1.42%), respectively (p < 0.0001 for both). Both TBR < 70 and <54 mg/dL remained unchanged. MBG slightly decreased by 5.40 mg/dL (-7.29 to -3.51 mg/dL; p < 0.0001) along with a reduction in %CV. Pooled eA1c and GMI decreased by 0.18% (-0.24 to -0.11%; p < 0.0001) and a similar reduction was observed when GMI alone was considered (0.15%, -0.23 to -0.07%; p < 0.0001). Sensor use was only slightly but not significantly reduced during lockdown. CONCLUSIONS: This meta-analysis shows that well-controlled people with type 1 diabetes on both MDI and CSII with continuous or flash glucose monitoring did not experience a deterioration in glucose control throughout the COVID-19 lockdown, showing a modest, though statistically significant improvement in many glucose control parameters.

Lessons learned from the continuous glucose monitoring metrics in pediatric patients with type 1 diabetes under COVID-19 lockdown.

AIMS: Billions of people have been under lockdown in an attempt to prevent COVID-19 spread. Lifestyle changes during lockdown could lead to deterioration of glycemic control in type 1 diabetes (T1D). We aimed to assess the impact of COVID-19 lockdown on the glycemic control of pediatric patients with T1D. METHODS: This observational real-life study from the AWeSoMe Group assessed continuous glucose monitoring (CGM) metrics of 102 T1D patients (52.9% males, mean age 11.2 ± 3.8 years, mean diabetes duration 4.2 ± 3.8 years) who used  Dexcom G5. The data were accessed without any interface between patients, caregivers, and the diabetes team. Study variables from CGM metrics were: mean glucose level, time-in-range (TIR, 70-180 mg/dL; 3.9-10 mmol/L), hypoglycemia (< 54 mg/dL; < 3 mmol/L), hyperglycemia (> 250 mg/dL; > 13.3 mmol/L), coefficient of variation (CV), and time CGM active before and during lockdown. Delta-variable = lockdown variable minus before-lockdown variable. RESULTS: The mean TIR was 60.9 ± 14.3% before lockdown, with no significant change during lockdown (delta-TIR was 0.9 ± 7.9%). TIR during lockdown was significantly correlated with TIR before lockdown (r = 0.855, P < 0.001). Patients with improved TIR (delta-TIR > 3%) were significantly older than patients with stable or worse TIR (P = 0.028). Children aged < 10 years had a significantly higher CV before lockdown and during lockdown than children aged ≥ 10 years (P = 0.02 and P = 0.005, respectively). Among children aged < 10 years, a multiple linear regression model revealed associations of age and lower socioeconomic cluster with delta-TIR (F = 4.416, P = 0.019) and with delta-mean glucose (F = 4.459, P = 0.018). CONCLUSIONS: CGM metrics in pediatric patients with T1D were relatively stable during a nationwide lockdown. Intervention plans should focus on younger patients with lower socioeconomic position.