Reliability of Inpatient CGM: Comparison to Standard of Care

Background: Optimal inpatient glycemic management targets a blood glucose (BG) of 140-180 mg/dL and is an important safety measure for hospitalized patients with hyperglycemia. Traditional barriers to appropriate insulin administration include incorrect timing of prandial insulin administration, failure to administer basal insulin to persons with insulin deficiency/type 1 diabetes mellitus (DM), and inaccurate insulin dosing or timing resulting in hypoglycemia. Given the ongoing rapid assimilation of technology to manage our patients with DM, we investigated the use of continuous glucose monitoring (CGM) in the inpatient setting as a potential solution to traditional barriers to optimal hyperglycemia management for inpatient care. In this study, we evaluated the efficacy of use of inpatient CGM for insulin dosing in comparison with current standard of care and whether CGM could aid in minimizing hypoglycemic events. Methods: This study evaluated the use of Abbott professional (blinded) Freestyle Libre CGMs in participants treated with basal bolus insulin administered with subcutaneous insulin (basal bolus therapy [BBT]: n = 20) or on intravenous insulin (IVI) infusions (n =16) compared with standard point of care (POC) BG measurements. All participants on IVI were admitted with a diagnosis of diabetic ketoacidosis (DKA). The CGM data was not available in real time. Sensors were removed at the time of discharge and data uploaded to Libre View. Continuous BG data were aggregated for each subject and matched to POC BG or lab chemistry values within five minutes. The POC BG results were assessed for comparability (CGM vs standard BG testing). Data were further analyzed for clinical decision-making for correction insulin. Results: The overall mean absolute relative difference including both IVI and BBT groups was 22.3% (SD, 9.0), with a median of 20.0%. By group, the IVI arm mean was 19.6% (SD, 9.4), with a median of 16.0%; for BBT, the arm mean was 24.6% (SD, 8.1), with a median 23.4%. Using the Wilcoxon two-sample test, the means were not different ( P = .10), whereas the medians were ( P = .015). The CGM consistently reported lower glucose values than POC BG in the majority of paired values (BBT arm mean difference = 44.8 mg/dL, IVI mean difference = 19.7 mg/dL). Glucose results were in agreement for the group 83% of the time with Bland-Altman Plot of Difference versus the mean of all glucometric data. Analysis of correction dose insulin using either CGM or POC BG values resulted in a negligible difference in calculated insulin dose recommended in those receiving subcutaneous insulin. Corrective doses were based on weight and insulin sensitivity (type 1 vs type 2 DM). Participants initially on IVI were included in a data set of BBT once IVI therapy ceased and basal bolus insulin regimen was started. The data of all basal bolus therapy participants with 1142 paired values of CGM versus POC glucose were used. The dosing difference was less for CGM than POC BG in the majority of paired values, and there was an absolute difference in dose of insulin of only 1.34 units. In the IVI group with 300 paired values of CGM versus POC glucose, there was an absolute difference in dose of insulin of only 0.74 units. About a third of the patients studied in the BBT arm experienced a hypoglycemic event with POC BG <70 mg/dL. If used in real time, CGM would have identified a hypoglycemic event for our patients on average 3 hours and 34 minutes before it was detected by standard POC BG. Two participants incurred severe nocturnal hypoglycemia during the study with POC BG <54 mg/dL with hypoglycemia detected on CGM up to 3 hours and 42 minutes before POC testing. Conclusions: These results suggest that the use of inpatient CGM arrives at similar correction insulin dosing. The routine use of CGM for inpatients would consistently underestimate the BG compared with POC BG and could aid in minimizing and predicting hypoglycemia in the hospital setting. Our data support that the model of adoption of real-time inpatient CGM technology is anticipated to have significant impact in the clinical setting in efforts to maintain adequate glycemic control targeting BG 140-180 mg/dL while minimizing the frequency of hypoglycemic events.

Incidence and Costs of Hypoglycemia among Type II Diabetes Mellitus Patients in Turkey

We aimed to determine the lifetime and one-year incidence of hypoglycemia in adults who had been treated following a diagnosis of Type II Diabetes Mellitus (T2DM), the factors that affected this incidence, and its effect on the use of health care resources. The descriptive cross-sectional cost study included adult T2DM patients who had an outpatient examination. Using a face-to-face interview method, patients were required to complete a questionnaire containing questions about sociodemographic characteristics, T2DM diagnosis and treatment features, and hypoglycemia events. Episode treatment costs of the patients in whom hypoglycemia was observed were calculated as direct cost per episode from the payer perspective. The mean age of the patients (n = 220) was 48.1 ± 11.8 (range 26-79) years, and the mean duration of disease was 4.5 ± 3.0 (range 1-16) years. According to treatment modalities, the frequency of hypoglycemia in the last year was 4.7% in the patients receiving oral antidiabetic drugs and 32.7% in the patients using insulin. In addition, 61.9% of the patients who had a hypoglycemic event in the last year presented to hospital, and 57.7% of these patients were hospitalized because of the hypoglycemic event. The incidence of hypoglycemia was 18 episodes of hypoglycemia per 100 patient years for T2DM patients and 25 severe hypoglycemia episodes per 100 patient years for patients using insulin. Significant predictors of hypoglycemia included insulin therapy (p = 0.000), regular use of medications (p = 0.013), hospitalization in the last year (p = 0.008), and exercise (p = 0.042). The average cost of a hypoglycemic event was calculated as Purchasing Power Parity İn Dollars ($PPP) 1.370.2 ± 1.407.0 (149.8-5,048.8). T2DM complications are the cause of a high economic burden. Hypoglycemia, which is one of these complications, is observed more frequently in patients who receive insulin therapy, who use regular medication, who do not exercise regularly, and who have been hospitalized in the last year.

Physiologic Change in Hypoglycemia in Diabetes Patients in Rajavithi Hospital Using Non-Invasive Hypoglycemic Warning Wearable Devices: A Pilot Study

Background: Hypoglycemic events are serious side effects which can occur when intensive glycemic control is being used to prevent vascular complications in diabetic patients. A wearable device which warns of impending hypoglycemia may help to achieve better control of diabetes. Objective: To identify physiologic changes during hypoglycemic events in diabetic patients using a wearable device. Materials and Methods: This was a pilot study of 28 glycemic events from 10 participants who used wearable hypoglycemic devices with Continuous Glucose Monitors (CGMs) in order to confirm hypoglycemic events during the study period. Variations in skin body temperature, pulse rate and skin resistance were also analysed. Data from the wearable hypoglycemic devices were collected and compared with those from CGMs to find significant variables during the hypoglycemic events. Results: Decrement of body temperature (Min BT-Mode BT) was greater in the hypoglycemic event group (-1.73±2.07 compared to -0.07±0.51in the non-hypoglycemic event group). Increment of heart rate (Max HR-Mode HR) was also higher in the hypoglycemic event group at 30.57±22.08 compared to 13.79±20.04. Decrement of skin resistance (Min SR-Mode SR) was -50.89±44.95 in hypoglycemic event group compared to -7.47±22.60 in non-hypoglycemic event group. All these physiologic changes were statistically significant with p-values= 0.015, 0.046 and 0.002 respectively. Conclusion: This is the first time a scoring system for hypoglycemic response from wearable devices has been used in Rajavithi Hospital.

Identifying Potential Intervention Points for Acute Hypoglycemic Events in Patients With Type 2 Diabetes Using Retrospective Clinical Data

This retrospective study examined changes in medication orders as a risk factor for future acute hypoglycemic events. The investigators identified factors associated with acute hypoglycemic events resulting in emergency department visits or inpatient admissions. Non-Hispanic Black race, chronic kidney disease, insulin at baseline, and non-private insurance were associated with higher risk of an acute hypoglycemic event, whereas age, sex, and A1C were not. After adjustment for other risk factors, changes in insulin orders after A1C measurement were associated with a 1.5 times higher risk of an acute hypoglycemia (adjusted hazard ratio 1.48, 95% CI 1.08–2.03). These results further understanding of risk factors and clinical processes relevant to predicting and preventing acute hypoglycemia.

Identifying Potential Intervention Points for Acute Hypoglycemic Events in Patients With Type 2 Diabetes Using Retrospective Clinical Data

This retrospective study examined changes in medication orders as a risk factor for future acute hypoglycemic events. The investigators identified factors associated with acute hypoglycemic events resulting in emergency department visits or inpatient admissions. Non-Hispanic Black race, chronic kidney disease, insulin at baseline, and non-private insurance were associated with higher risk of an acute hypoglycemic event, whereas age, sex, and A1C were not. After adjustment for other risk factors, changes in insulin orders after A1C measurement were associated with a 1.5 times higher risk of an acute hypoglycemia (adjusted hazard ratio 1.48, 95% CI 1.08–2.03). These results further understanding of risk factors and clinical processes relevant to predicting and preventing acute hypoglycemia.

Big Insulin-like Growth Factor 2–Producing Tumor in a Hypoglycemic Dog

A 10-year-old female Papillon dog that had previously developed a mammary tumor was admitted for treatment of a hypoglycemic attack. Blood examination showed severe hypoglycemia and decreased blood insulin concentration. Computed tomography indicated multiple tumors in the cranial and caudal lobes of the right lung. These tumors were resected surgically and diagnosed as pulmonary adenocarcinomas by histopathologic examination. Hypoglycemia was temporarily improved after the resection, but a hypoglycemic event occurred 2 months after the surgery. Immunohistochemistry of the tumor demonstrated the expression of insulin-like growth factor 2 in tumor cells. Western blot analysis revealed the expression of high-molecular-weight (big)–insulin-like growth factor 2 in the tumor region. Insulin-like growth factor 2 mRNA expression was also confirmed in the tumor using reverse transcription–polymerase chain reaction. These findings indicate the diagnosis of non–islet cell tumor-induced hypoglycemia caused by big-insulin-like growth factor 2 produced by the tumor in the dog. This report provides information on differentiating tumors that cause paraneoplastic hypoglycemia.

Effectiveness of diabetes self-management education and support via a smartphone application in insulin-treated patients with type 2 diabetes: results of a randomized controlled trial (TRIGGER study)

ObjectiveTo investigate the effect of diabetes self-management education and support via a smartphone app in individuals with type 2 diabetes on insulin therapy.Research design and methodsOpen two-arm multicenter parallel randomized controlled superiority trial. The intervention group (n=115) received theory and evidence-based self-management education and support via a smartphone app (optionally two or six times per week, once daily at different times). The control group (n=115) received care as usual. Primary outcome: HbA1c at 6 months. Other outcomes included HbA1c ≤53 mmol/mol (≤7%) without any hypoglycemic event, body mass index, glycemic variability, dietary habits and quality of life. We performed multiple imputation and regression models adjusted for baseline value, age, sex, diabetes duration and insulin dose.ResultsSixty-six general practices and five hospital outpatient clinics recruited 230 participants. Baseline HbA1c was comparable between groups (8.1% and 8.3%, respectively). At 6 months, the HbA1c was 63.8 mmol/mol (8.0%) in the intervention vs 66.2 mmol/mol (8.2%) in the control group; adjusted difference −0.93 mmol/mol (−0.08%), 95% CI −4.02 to 2.17 mmol/mol (−0.37% to 0.20%), p=0.557. The odds for achieving an HbA1c level ≤7% without any hypoglycemic event was lower in the intervention group: OR 0.87, 95% CI 0.33 to 2.35. There was no effect on secondary outcomes. No adverse events were reported.ConclusionsThis smartphone app providing diabetes self-management education and support had small and clinically not relevant effects. Apps should be more personalized and target individuals who think the app will be useful for them.Trial registration numberNTR5515.