Factors influencing insulin initiation in primary care facilities in Cape Town, South Africa.

BACKGROUND: Type 2 diabetes (T2DM) is a leading cause of mortality in South Africa and resistance to the use of insulin is common. This study aimed to explore factors that influence the initiation of insulin in patients with T2DM in primary care facilities in Cape Town, South Africa. METHODS: An exploratory descriptive qualitative study was conducted. Seventeen semi-structured interviews were held with patients eligible for insulin, on insulin and primary care providers. Participants were selected by maximum variation purposive sampling. Data were analysed using the framework method in Atlas-ti. RESULTS: Factors related to the health system, service delivery, clinical care and patients. Systemic issues related to the required inputs of workforce, educational materials, and supplies. Service delivery issues related to workload, poor continuity and parallel coordination of care. Clinical issues related to adequate counselling. Patient factors included a lack of trust, concerns about injections, impact on lifestyle and disposal of needles. CONCLUSION: Although resource constraints are likely to remain, district and facility managers can improve supplies, educational materials, continuity and coordination. Counselling must be improved and may require innovative alternative approaches to support clinicians who face high number of patients. Alternative approaches using group education, telehealth and digital solutions should be considered.Contribution: This study identified key factors influencing insulin initiation in patients with T2DM in primary care. These can be addressed by those responsible for clinical governance, service delivery and in further research.

Concordance of Central Laboratory Hemoglobin A1c Measurements from Capillary Kits Compared to Venous Draws in the Insulin-Only Bionic Pancreas Pivotal Trial.

Capillary hemoglobin A1c (HbA1c) collection has grown in importance due to its convenience during situations such as the coronavirus disease 2019 (COVID-19) pandemic and virtual visits. The viability of capillary blood samples as an accurate alternative to venous samples has previously only been assessed in smaller sample sizes. In this brief report, 773 paired capillary and venous samples taken from 258 study participants in the Insulin-Only Bionic Pancreas Trial were analyzed at the University of Minnesota Advanced Research and Diagnostic Laboratory and assessed for HbA1c value congruency. Results showed that 97.7% of the capillary samples were within 5% of their respective venous measurement, and R2 between the two HbA1c sources was 0.95. These results are consistent with previous studies that also reported high concordance between capillary and venous HbA1c values using the same laboratory method, providing further evidence that capillary HbA1c measurements are an accurate alternative to venous measurements. Clinical Trial Registration number: NCT04200313.

Continuous Glucose Monitoring in the Intensive Care Unit.

Traditionally, the care of critically ill patients with diabetes or stress hyperglycemia in the intensive care unit (ICU) demands the use of continuous intravenous insulin (CII) therapy to achieve narrow glycemic targets. To reduce the risk of iatrogenic hypoglycemia and to achieve glycemic targets during CII, healthcare providers (HCP) rely on hourly point-of-care (POC) arterial or capillary glucose tests obtained with glucose monitors. The burden of this approach, however, was evident during the beginning of the pandemic when the immediate reduction in close contact interactions between HCP and patients with COVID-19 was necessary to avoid potentially life-threatening exposures. Taking advantage of the advancements in current diabetes technologies, including continuous glucose monitoring (CGM) devices integrated with digital health tools for remote monitoring, HCP implemented novel protocols in the ICU to care for patients with COVID-19 and hyperglycemia. We provide an overview of research conducted in the ICU setting with the use of initial CGM technology to current devices and summarize our recent experience in the ICU.

Continuous Glucose Monitoring for Patients with COVID-19 Pneumonia: Initial Experience at a Tertiary Care Center.

OBJECTIVE: Patients hospitalized with COVID-19 and hyperglycemia require frequent glucose monitoring, usually performed with glucometers. Continuous glucose monitors (CGMs) are common in the outpatient setting but not yet approved for hospital use. We evaluated CGM accuracy, safety for insulin dosing, and CGM clinical reliability in 20 adult patients hospitalized with COVID-19 and hyperglycemia. METHODS: Study patients were fitted with a remotely monitored CGM. CGM values were evaluated against glucometer readings. The CGM sensor calibration was performed if necessary. CGM values were used to dose insulin, without glucometer confirmation. RESULTS: CGM accuracy against glucometer, expressed as mean absolute relative difference (MARD), was calculated using 812 paired glucometer-CGM values. The aggregate MARD was 10.4%. For time in range and grades 1 and 2 hyperglycemia, MARD was 11.4%, 9.4%, and 9.1%, respectively, with a small variation between medical floors and intensive care units. There was no MARD correlation with mean arterial blood pressure levels, oxygen saturation, daily hemoglobin levels, and glomerular filtration rates. CGM clinical reliability was high, with 99.7% of the CGM values falling within the "safe" zones of Clarke error grid. After CGM placement, the frequency of glucometer measurements decreased from 5 to 3 and then 2 per day, reducing nurse presence in patient rooms and limiting viral exposure. CONCLUSION: With twice daily, on-demand calibration, the inpatient CGM use was safe for insulin dosing, decreasing the frequency of glucometer fingersticks. For glucose levels >70 mg/dL, CGMs showed adequate accuracy, without interference from vital and laboratory values.

A UK nationwide study of adults admitted to hospital with diabetic ketoacidosis or hyperosmolar hyperglycaemic state and COVID-19.

AIMS: To investigate characteristics of people hospitalized with coronavirus-disease-2019 (COVID-19) and diabetic ketoacidosis (DKA) or hyperosmolar hyperglycaemic state (HHS), and to identify risk factors for mortality and intensive care admission. MATERIALS AND METHODS: Retrospective cohort study with anonymized data from the Association of British Clinical Diabetologists nationwide audit of hospital admissions with COVID-19 and diabetes, from start of pandemic to November 2021. The primary outcome was inpatient mortality. DKA and HHS were adjudicated against national criteria. Age-adjusted odds ratios were calculated using logistic regression. RESULTS: In total, 85 confirmed DKA cases, and 20 HHS, occurred among 4073 people (211 type 1 diabetes, 3748 type 2 diabetes, 114 unknown type) hospitalized with COVID-19. Mean (SD) age was 60 (18.2) years in DKA and 74 (11.8) years in HHS (p < .001). A higher proportion of patients with HHS than with DKA were of non-White ethnicity (71.4% vs 39.0% p = .038). Mortality in DKA was 36.8% (n = 57) and 3.8% (n = 26) in type 2 and type 1 diabetes respectively. Among people with type 2 diabetes and DKA, mortality was lower in insulin users compared with non-users [21.4% vs. 52.2%; age-adjusted odds ratio 0.13 (95% CI 0.03-0.60)]. Crude mortality was lower in DKA than HHS (25.9% vs. 65.0%, p = .001) and in statin users versus non-users (36.4% vs. 100%; p = .035) but these were not statistically significant after age adjustment. CONCLUSIONS: Hospitalization with COVID-19 and adjudicated DKA is four times more common than HHS but both associate with substantial mortality. There is a strong association of previous insulin therapy with survival in type 2 diabetes-associated DKA.

Exploratory study on glycemic control improvement for patients with diabetes mellitus by appropriate re-education on insulin self-injection technique during COVID-19 pandemic.

AIMS: To conduct a study on glycemic control improvement by appropriate re-education on the self-injection technique (SIT) in patients with diabetes mellitus undergoing insulin therapy. METHODS: Patients who received appropriate SIT and were treated with insulin for more than a year were re-educated. For the observation period of six months, the subjects' SIT was checked, and hemoglobin A1c (HbA1c) levels were measured at each visit. HbA1c levels, insulin doses, and behavioral changes in SIT were investigated at baseline and at the end of the observation period. RESULTS: In the per-protocol set population, the HbA1c level decreased by 0.2 % (2.0 mmol/mol) on average, showing a significant difference (p = 0.009). No significant difference was observed in the proportion of subjects with decreased HbA1c levels, changes in total daily insulin doses, or blood glucose levels. Four of the six SIT items covered by re-education were improved. CONCLUSIONS: Providing re-education on insulin SIT was considered effective in reducing HbA1c levels and improving adherence to proper SIT.

Outpatient Randomized Crossover Comparison of Zone Model Predictive Control Automated Insulin Delivery with Weekly Data Driven Adaptation Versus Sensor-Augmented Pump: Results from the International Diabetes Closed-Loop Trial 4.

Background: Automated insulin delivery (AID) systems have proven effective in increasing time-in-range during both clinical trials and real-world use. Further improvements in outcomes for single-hormone (insulin only) AID may be limited by suboptimal insulin delivery settings. Methods: Adults (≥18 years of age) with type 1 diabetes were randomized to either sensor-augmented pump (SAP) (inclusive of predictive low-glucose suspend) or adaptive zone model predictive control AID for 13 weeks, then crossed over to the other arm. Each week, the AID insulin delivery settings were sequentially and automatically updated by an adaptation system running on the study phone. Primary outcome was sensor glucose time-in-range 70-180 mg/dL, with noninferiority in percent time below 54 mg/dL as a hierarchical outcome. Results: Thirty-five participants completed the trial (mean age 39 ± 16 years, HbA1c at enrollment 6.9% ± 1.0%). Mean time-in-range 70-180 mg/dL was 66% with SAP versus 69% with AID (mean adjusted difference +2% [95% confidence interval: -1% to +6%], P = 0.22). Median time <70 mg/dL improved from 3.0% with SAP to 1.6% with AID (-1.5% [-2.4% to -0.5%], P = 0.002). The adaptation system decreased initial basal rates by a median of 4% (-8%, 16%) and increased initial carbohydrate ratios by a median of 45% (32%, 59%) after 13 weeks. Conclusions: Automated adaptation of insulin delivery settings with AID use did not significantly improve time-in-range in this very well-controlled population. Additional study and further refinement of the adaptation system are needed, especially in populations with differing degrees of baseline glycemic control, who may show larger benefits from adaptation.

New Digital Health Technologies for Insulin Initiation and Optimization for People With Type 2 Diabetes.

OBJECTIVE: The health and economic burden of type 2 diabetes is of global significance. Many people with type 2 diabetes eventually need insulin to help reduce their risk of serious associated complications. However, barriers to the initiation and/or optimization of insulin expose people with diabetes to sustained hyperglycemia. In this review, we investigated how new and future technologies may provide opportunities to help overcome these barriers to the initiation and/or optimization of insulin. METHODS: A focused literature search of PubMed and key scientific congresses was conducted. Software tools and devices developed to support the initiation and/or optimization of insulin were identified by manually filtering >300 publications and conference abstracts. RESULTS: Most software tools have been developed for smartphone platforms. At present, published data suggest that the use of these technologies is associated with equivalent or improved glycemic outcomes compared with standard care, with additional benefits such as reduced time burden and improved knowledge of diabetes among health care providers. However, there remains paucity of good-quality evidence. Most new devices to support insulin therapy help track the dose and timing of insulin. CONCLUSION: New digital health tools may help to reduce barriers to optimal insulin therapy. An integrated solution that connects glucose monitoring, dose recording, and titration advice as well as records comorbidities and lifestyle factors has the potential to reduce the complexity and burden of treatment and may improve adherence to titration and treatment, resulting in better outcomes for people with diabetes.

Single-centre case-control study investigating the association between acanthosis nigricans, insulin resistance and type 2 diabetes in a young, overweight, UK population.

OBJECTIVE: To determine the extent to which the presence of acanthosis nigricans confers additional risk for insulin resistance, in addition to obesity alone (body mass index, BMI) within a young, overweight, UK population. RESEARCH DESIGN AND METHODS: Retrospective data were collected to compare the degree of insulin resistance within a sample of 94 young people with acanthosis nigricans, and a matched cohort of 94 participants with obesity alone. Insulin resistance was assessed by fasting glucose, fasting insulin and Homeostatic Model Assessment of insulin resistance (HOMA-IR) score (a mathematical model derived to measure insulin resistance). RESULTS: The acanthotic and control group were well matched for age, BMI, BMI SDS and sex, although the groups were not matched for ethnicity. The acanthotic group showed a significantly greater median fasting insulin (215 pmol/L), mean fasting glucose (4.7 mmol/L) and median HOMA-IR score (6.4), compared with the control group (126 pmol/L, 4.5 mmol/L and 3.7, respectively). The presence of acanthosis nigricans as an indicator of insulin resistance was found to have a positive predictive value of 81% (within this study population). CONCLUSION: Individuals with both acanthosis nigricans and obesity had significantly greater degrees of insulin resistance than individuals with obesity alone. The findings support the potential for acanthosis nigricans as a visible marker of type 2 diabetes in young people.

Impact of COVID-19 lockdown on glucemic control in children and adolescents with type 1 diabetes mellitus.

BACKGROUND AND AIMS: To face the rapid spread of SARS-CoV2 coronavirus pandemic, home lockdown in Spain was decreed on 15th March 2020. The main objective of this study is to evaluate the impact of this constraint on glycemic control in children and adolescents with type 1 diabetes mellitus (T1D). PATIENTS AND METHODS: Observational, retrospective study in children and adolescents with T1D users of interstitial glucose monitoring systems. The following information corresponding to the last 2 weeks of lockdown was collected for subsequent comparison with data of 2 weeks prior to quarantine: daily insulin needs, mean interstitial glucose, estimated HbA1c, coefficient of variation (CV), time in range (70-180mg/dl), hypoglycemia (<70 and <54mg/dl) and hyperglycemia (>180 and> 250mg/dl), sensor use and number of blood glucose measurements. Data about meal routines, physical exercise, need for adjustments in therapy, acute complications and lockdown of caregivers were assessed via a survey. RESULTS: 80 patients were studied (mean age 12.61±3.32 years, mean time of evolution of the disease 5.85±3.92 years), 66.2% treated with an insulin pump, users of following glucose monitoring systems: Guardian 3 (65%), FreeStyle Libre (18.8%) and Dexcom G6 (16.2%). Time in range in the cohort increased significantly during confinement (72.1±10.5 vs 74.8±10.5%; P=0.011) with lower time in hypoglycemia both <70mg/dl (4.6±3.2 vs 3.2±2.7%; P<0.001) and <54mg/dl (1.2±1.6 vs 0.7±1.2%; P<0.001) and hyperglycemia >250mg/dl (4.6±3.9 vs 3.7±3.7%; P=0.038). CV also decreased (35.8±6.3 vs 33.1±6.1%; P<0.001). Patients treated with multiple doses of insulin and poorer baseline glycemic control experienced greatest improvement. Daily insulin requirements remained stable. Regular practice of physical exercise and caregivers' confinement did not have a significant impact. CONCLUSIONS: Glycemic control in children and adolescents with T1D improved during quarantine, particularly in those with worse baseline control.

Effectiveness of Continuous Glucose Monitoring in Older Adults with Type 2 Diabetes Treated with Basal Insulin.

Objective: To evaluate the effectiveness and safety of real-time continuous glucose monitoring (CGM) in adults 65 years old and older with type 2 diabetes (T2D) using basal without bolus insulin. Research Design and Methods: Using data from the MOBILE randomized trial comparing CGM versus blood glucose meter (BGM) monitoring for T2D treated with basal insulin, the treatment effect in participants ≥65 years (range: 65-79 years, N = 42) was compared with the treatment effect in participants <65 years (range: 33-64 years, N = 133). Results: For participants ≥65 years old, mean change in hemoglobin A1c (HbA1c) was -1.08% in the CGM group and -0.38% in the BGM group (adjusted mean difference = -0.65% [95% confidence interval (CI) -1.49 to 0.19]). In contrast, the adjusted mean difference in HbA1c between treatment groups was -0.35% [95% CI -0.77 to 0.07] in the <65 years age group. For time in range 70-180 mg/dL (TIR), mean adjusted treatment group difference was 19% (95% CI 4 to 35, P = 0.01) in ≥65 years old participants and 12% (95% CI 4 to 19, P = 0.003) in those <65 years old. Comparable treatment group differences favoring the CGM group were observed in both the ≥65 and <65 years age groups for mean glucose and less time >180, 250, and 300 mg/dL. Hypoglycemia was low in both groups with little difference between treatment groups in both age groups. Conclusions: In this study of adults with T2D treated with basal insulin without bolus insulin, participants ≥65 years old using CGM had a greater increase in TIR and a reduction in hyperglycemia than those using BGM and the benefit appeared to be at least as great as that observed in younger adults.

Adolescents with type 1 diabetes can achieve glycemic targets on intensive insulin therapy without excessive weight gain.

INTRODUCTION: The aim of this study was to compare glycemic control and body mass index standard deviation score (BMI-SDS) before and after implementation of intensive insulin therapy using multiple daily injection (MDI) or continuous subcutaneous insulin infusion (CSII) in adolescents with type 1 diabetes (T1D) attending a large multidisciplinary paediatric diabetes clinic in Australia. METHODS: Prospective data were collected for cross-sectional comparison of youth aged 10.0-17.9 years (n = 669) from routine follow-up visits to the diabetes clinic in 2004, 2010, and 2016. Outcome measures included HbA1c; BMI-SDS; and insulin regimen. RESULTS: BMI-SDS remained stable between 2004 to 2016 in the 10-13 and 14-17 year age group (0.7 vs. 0.5, p = .12 and 0.7 vs. 0.7, p = .93, respectively). BMI-SDS was not different across HbA1c groups; <53 mmol/mol (7.0%), 53 to <75 mmol/mol (<7.0 to <9.0%) and >75 mmol/mol (>9.0%) in 2004 (p = .873), 2010 (p = .10) or 2016 (p = .630). Mean HbA1c decreased from 2004 to 2016 in the 10-13 year (69 mmol/mol (8.4%) vs. 57 mmol/mol (7.4%), p = <.001) and 14-17 year group (72 mmol/mol (8.7%) vs. 63 mmol/mol (7.9%), p = <.001). Prior to the implementation of MDI and CSII in 2004 only 10% of 10-13 year olds and 8% of 14-17 year olds achieved the international target for glycemic control (HbA1c 53 mmol/mol [<7.0%]). In 2016, this increased to 31% of 10-13 year olds and 21% of 14-17 year olds. CONCLUSIONS: BMI-SDS did not increase with the change to intensive insulin therapy despite a doubling in the number of adolescents achieving the recommended glycemic target of <7.0% (53 mmol/mol). HbA1c was not associated with weight gain.

Assessment of Insulin Infusion Requirements in COVID-19-Infected Patients With Diabetic Ketoacidosis.

BACKGROUND/OBJECTIVE: Coronavirus disease 2019 (COVID-19) is thought to contribute to diabetic ketoacidosis (DKA) and worse outcomes in patients with diabetes. This study compared the cumulative insulin dose required to achieve DKA resolution in the intensive care unit among patients with type 2 diabetes and COVID-19 infection versus without COVID-19 infection. METHODS: This retrospective cohort study evaluated 100 patients-50 patients with COVID-19 in cohort 1 and 50 patients without COVID-19 in cohort 2-treated with insulin infusions for DKA at a tertiary care teaching hospital. The primary outcome was to compare the cumulative insulin dose required to achieve DKA resolution in each cohort. The secondary outcomes included time to DKA resolution, mean insulin infusion rate, and mean weight-based cumulative insulin infusion dose required to achieve DKA resolution. All endpoints were adjusted for confounders. RESULTS: The mean cumulative insulin dose was 190.3 units in cohort 1 versus 116.4 units in cohort 2 (P = .0038). Patients receiving steroids had a mean time to DKA resolution of 35.9 hours in cohort 1 versus 15.6 hours in cohort 2 (P = .0014). In cohort 1 versus cohort 2, the mean insulin infusion rate was 7.1 units/hour versus 5.3 units/hour (P = .0025), whereas the mean weight-based cumulative insulin infusion dose was 2.1 units/kg versus 1.5 units/kg (P = .0437), respectively. CONCLUSION: COVID-19-infected patients required a significantly larger cumulative insulin dose, longer time to DKA resolution, higher insulin infusion rate, and higher weight-based insulin infusion dose to achieve DKA resolution versus non-COVID-19-infected patients with type 2 diabetes.

Incidence of an Insulin-Requiring Hyperglycemic Syndrome in SARS-CoV-2-Infected Young Individuals: Is It Type 1 Diabetes?

Pancreatic ACE2 receptor expression, together with increased prevalence of insulin-requiring hyperglycemia in patients with coronavirus disease 2019 (COVID-19), suggested that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pancreatic infection might trigger a ß-cell-selective inflammation precipitating autoimmune type 1 diabetes (T1D). We examined T1D incidence in patients with COVID-19 inside a large, global population using a "big data" approach. The incidence in 0-30-year-old patients with confirmed COVID-19 over an ∼15-month period from the beginning of the COVID-19 pandemic was compared with an age-matched population without COVID-19 inside the TriNetX COVID-19 Research Network (>80 million deidentified patient electronic medical records globally). The cohorts were used to generate outcomes of T1D postindex. In those up to 18 years of age, the incidence of insulin-requiring diabetes that could represent T1D in patients with already diagnosed, confirmed COVID-19 was statistically indistinguishable from the control population without COVID-19. In contrast, in those aged 19-30 years, the incidence was statistically greater. These data suggest that the incidence of T1D among patients with COVID-19 <30 years of age, at least up to this time since the beginning of the pandemic, is not greater when compared with an age-, sex-, and BMI-matched population without COVID-19. Nevertheless, we caution that patients with COVID-19 could be asymptomatic of a diabetic/prediabetic state and therefore would not be expected to come to medical attention, remaining undiagnosed. Hence, it is still possible that asymptomatic virus-infected individuals could acquire ß-cell autoimmunity, eventually progressing to dysglycemia and clinical T1D at higher rates.