Correlation between centre size, metabolic variation and mean HbA1c in major paediatric diabetes centres.

AIM: To exploit a relatively homogeneous national health care context and a national diabetes database to address the questions: Is there an optimal clinic/centre size in determining outcomes?; and Can improvement in median centre outcomes be driven by reducing variability in outcome? METHODS: Using the Australasian Diabetes Database Network, data from seven tertiary hospital paediatric diabetes clinics for patients with type one diabetes from Australia were recorded from 6-month uploads: September 2017, March 2018, September 2018 and March 2019. Data from 25 244 patient visits included demographic variables, HbA1C, number of patient visits and insulin regimens. RESULTS: There was no association between centre size and median HbA1C. On the other hand, there was a significant association between or median absolute deviation of HbA1C outcomes and the median HbA1C result between centres. On average every two thirds of a median absolute deviation increase in clinic HbA1C was associated with a 1.0% (10.9 mmol/mol) increase in median clinic HbA1C. CONCLUSIONS: Our data have shown that it is likely difficult for centres to have a low median HbA1C if there is high variance of HbA1C's within centres or within centre treatment groups. This appears to be true regardless of centre size. These findings need to be carefully considered by teams who wish to lower their clinic median HbA1C.

Optimal Coefficient of Variance Threshold to Minimize Hypoglycemia Risk in Individuals with Well-Controlled Type 1 Diabetes Mellitus.

Background: This study investigated the optimal coefficient of variance (%CV) for preventing hypoglycemia based on real-time continuous glucose monitoring (rt-CGM) data in people with type 1 diabetes mellitus (T1DM) already achieving their mean glucose (MG) target. Methods: Data from 172 subjects who underwent rt-CGM for at least 90 days and for whom 439 90-day glycemic profiles were available were analyzed. Receiver operator characteristic analysis was conducted to determine the cut-off value of %CV to achieve time below range (%TBR)<54 mg/dL <1 and =0. Results: Overall mean glycosylated hemoglobin was 6.8% and median %TBR<54 mg/dL was 0.2%. MG was significantly higher and %CV significantly lower in profiles achieving %TBR<54 mg/dL <1 compared to %TBR<54 mg/dL ≥1 (all P<0.001). The cut-off value of %CV for achieving %TBR<54 mg/dL <1 was 37.5%, 37.3%, and 31.0%, in the whole population, MG >135 mg/dL, and ≤135 mg/dL, respectively. The cut-off value for %TBR<54 mg/dL=0% was 29.2% in MG ≤135 mg/dL. In profiles with MG ≤135 mg/dL, 94.2% of profiles with a %CV <31 achieved the target of %TBR<54 mg/dL <1, and 97.3% with a %CV <29.2 achieved the target of %TBR<54 mg/ dL=0%. When MG was >135 mg/dL, 99.4% of profiles with a %CV <37.3 achieved %TBR<54 mg/dL <1. Conclusion: In well-controlled T1DM with MG ≤135 mg/dL, we suggest a %CV <31% to achieve the %TBR<54 mg/dL <1 target. Furthermore, we suggest a %CV <29.2% to achieve the target of %TBR<54 mg/dL =0 for people at high risk of hypoglycemia.

Effects of an Electronic Medical Records-Linked Diabetes Self-Management System on Treatment Targets in Real Clinical Practice: Retrospective, Observational Cohort Study.

Background: This study evaluated the effects of a mobile diabetes management program called "iCareD" (College of Medicine, The Catholic University of Korea) which was integrated into the hospital's electronic medical records system to minimize the workload of the healthcare team in the real clinical practice setting. Methods: In this retrospective observational study, we recruited 308 patients. We categorized these patients based on their compliance regarding their use of the iCareD program at home; compliance was determined through self-monitored blood glucose inputs and message subscription rates. We analyzed changes in the ABC (hemoglobin A1c, blood pressure, and low-density lipoprotein cholesterol) levels from the baseline to 12 months thereafter, based on the patients' iCareD usage patterns. Results: The patients comprised 92 (30%) non-users, 170 (55%) poor-compliance users, and 46 (15%) good-compliance users; the ABC target achievement rate showed prominent changes in good-compliance groups from baseline to 12 months (10.9% vs. 23.9%, P<0.05), whereas no significant changes were observed for poor-compliance users and non-users (13.5% vs. 18.8%, P=0.106; 20.7% vs. 14.1%, P=0.201; respectively). Conclusion: Implementing the iCareD can improve the ABC levels of patients with diabetes with minimal efforts of the healthcare team in real clinical settings. However, the improvement of patients' compliance concerning the use of the system without the vigorous intervention of the healthcare team needs to be solved in the future.

Patient-Centered Medicine and Self-Care of Patients with Type 2 Diabetes: A Cross-Sectional Study.

INTRODUCTION: Even though the prevalence rate of diabetes in Portugal is one of the highest in Europe, no studies on the association between patient centered medicine, diabetes self-care, and glycemic control have been published. Assuming that patient centered medicine increases adherence to treatment through the improvement of the doctor-patient relationship, the aim of this study was to assess the influence of patient-centered medicine on the self-care of patients with type 2 diabetes patients' (T2DM) in two Family Health Units in Central Portugal, according to gender and age. MATERIAL AND METHODS: A cross-sectional study was conducted in two Family Health Units in Central Portugal between the 25th November 2021 and the 15th January 2022. Patients with type 2 diabetes were invited to fill in the Patient-Centered Medicine questionnaire, for patients (PCM-p) (where higher values represent worse results) and the Summary of Diabetes Self-Care Activities Measure (SDSCAM), (where higher values represent better results), while healthcare professionals filled in the epidemiologic variables on pre-defined days. RESULTS: A sample of 298 patients with type 2 diabetes was studied. Linear regressions for the association between SDSCAM scale factors and PCM-p showed significant associations for general diet (ß = -0.07, p < 0.001), specific diet (ß = -0.10, p < 0.001), exercise (ß = -0.03, p = 0.008), foot care (ß = -0.11, p < 0.001) and medication adherence in general (ß = -0.06, p = 0.001). Multiple linear regression including the association between glycated hemoglobin (HbA1c) and the SDSCAM scale dimensions showed that specific diet was associated with lower HbA1c levels (ß = -0.01, p = 0.007) and blood sugar testing (ß = 0.01, p < 0.001) and that a higher score in PCMp was associated with higher HbA1c levels (ß = 0.06, p < 0.001). Male patients (ß = -6.93, p = 0.007) and older patients (ß = -0.42, p = 0.001) were associated with lower scores in the specific diet. The male gender was associated with higher scores in exercise (ß = 7.62, p = 0.029), lower scores in foot care (ß = -6.06, p = 0.029) and lower scores in medication adherence to injectable medicines/6.2 (ß = -0.73, p = 0.018). Age was associated with a lower score in medication (ß = -0.03, p = 0.045) and a higher PCMp total score (ß = 0.07, p = 0.030). CONCLUSION: Patient-centered medicine in type 2 diabetics is associated with better self-care behaviors in patients with type 2 diabetes. Gender and age differences were observed in self-care behaviors and age differences were observed in Patient Centered Medicine.

Error traps in the perioperative management of children with type 1 diabetes.

Patients with type 1 diabetes mellitus (T1D) require insulin administration at all times to maintain euglycemia and metabolic stability. Insulin administration in the perioperative period is complicated by fasting requirements and perioperative stressors that can change the patient's insulin needs. In addition, many anesthesia providers are not familiar with insulin dosing strategies and technology, such as insulin pumps and continuous glucose monitors (CGMs), that are commonly used by patients with T1D. Errors in perioperative insulin administration can lead to hypoglycemia, hyperglycemia, and diabetic ketoacidosis. This article reviews common errors of associated with the perioperative management of patients with T1D, including failure to assess and coordinate patient care preoperatively; failure to understand diabetes management and technology; failure to monitor blood glucose and recognize dysglycemia; and failure to appropriately administer basal insulin.

Correlación entre tiempo en rango y hemoglobina glicosilada en personas con diabetes mellitus: revisión sistemática / Correlation between time on target and glycated hemoglobin in people with diabetes mellitus: systematic review / Correlação entre tempo no alvo e hemoglobina glicada de pessoas com diabetes mellitus: revisão sistemática

Objetivo: analizar la correlación entre el tiempo en rango y la hemoglobina glicosilada de personas que viven con diabetes mellitus y realizan la monitorización continua de la glucemia o el automonitoreo de la glucemia capilar Método: revisión sistemática de etiología y riesgo basada en las directrices del JBI e informada según los Preferred Reporting Items for Systematic Reviews and Meta-Analyses, abarcando seis bases de datos y la literatura gris. La muestra incluyó 16 estudios y la calidad metodológica fue evaluada utilizando las herramientas del JBI. Protocolo registrado en Open Science Framework, disponible en https://doi.org/10.17605/OSF.IO/NKMZB. Resultados: tiempo en rango (70-180 mg/dl) mostró una correlación negativa con la hemoglobina glicosilada, mientras que el tiempo por encima del rango (>180 mg/dl) mostró una correlación positiva. Los coeficientes de correlación variaron entre -0,310 y -0,869 para el tiempo en rango, y entre 0,66 y 0,934 para el tiempo por encima del rango. Un estudio se realizó en una población que hacía el automonitoreo. Conclusión: hay una correlación estadísticamente significativa entre el tiempo en rango y el tiempo por encima del rango con la hemoglobina glicosilada. Cuanto mayor sea la proporción en el rango glucémico adecuado, más cerca o por debajo del 7% estará la hemoglobina glicosilada. Se necesitan más estudios que evalúen esta métrica con datos del automonitoreo de la glucemia.

Objective: to analyze the correlation between time on target and glycated hemoglobin in people living with diabetes mellitus and carrying out continuous blood glucose monitoring or self-monitoring of capillary blood glucose. Method: systematic review of etiology and risk based on JBI guidelines and reported according to Preferred Reporting Items for Systematic Reviews and Meta- Analyses, covering six databases and grey literature. The sample included 16 studies and methodological quality was assessed using JBI tools. Protocol registered in the Open Science Framework, available at https://doi.org/10.17605/OSF.IO/NKMZB. Results: time on target (70-180 mg/dl) showed a negative correlation with glycated hemoglobin, while time above target (>180 mg/dl) showed a positive correlation. Correlation coefficients ranged between -0.310 and -0.869 for time on target, and between 0.66 and 0.934 for time above target. A study was carried out on a population that performed self-monitoring. Conclusion: there is a statistically significant correlation between time on target and time above target with glycated hemoglobin. The higher the proportion in the adequate glycemic range, the closer to or less than 7% the glycated hemoglobin will be. More studies are needed to evaluate this metric with data from self-monitoring of blood glucose.

Objetivo: analisar a correlação entre o tempo no alvo e a hemoglobina glicada de pessoas que vivem com diabetes mellitus e realizam a monitorização contínua da glicemia ou a automonitorização da glicemia capilar. Método: revisão sistemática de etiologia e de risco pautada nas diretrizes do JBI e reportada conforme Preferred Reporting Items for Systematic Reviews and Meta-Analyses, abrangendo seis bases de dados e a literatura cinzenta. A amostra incluiu 16 estudos e a qualidade metodológica foi avaliada utilizando as ferramentas do JBI. Registrado protocolo no Open Science Framework, disponível em https://doi.org/10.17605/OSF.IO/NKMZB. Resultados: tempo no alvo (70-180 mg/dl) apresentou correlação negativa com a hemoglobina glicada, enquanto o tempo acima do alvo (>180 mg/dl) mostrou correlação positiva. Os coeficientes de correlação variaram entre -0,310 e -0,869 para o tempo no alvo, e entre 0,66 e 0,934 para o tempo acima do alvo. Um estudo foi efetuado com população que realizava a automonitorização. Conclusão: há correlação estatisticamente significativa entre o tempo no alvo e o tempo acima do alvo com a hemoglobina glicada. Quanto maior a proporção na faixa glicêmica adequada, mais próxima ou inferior a 7% estará a hemoglobina glicada. São necessários mais estudos que avaliem essa métrica com dados da automonitorização da glicemia.

Determinants of diabetes self-care activities in patients with type 2 diabetes based on self-determination theory.

AIMS: In type 2 diabetes control, self-management is an effective way to minimize the risk of developing complications and improve the quality of life. Self-determination theory (SDT) proposed a promising explanatory framework to predict self-regulated behavior which was particularly relevant for self-management. This study aimed to investigate whether SDT constructs can affect the self-management and controlling glycated hemoglobin A1c (HbA1c) levels in type 2 diabetic patients or not. METHODS: This cross-sectional study was conducted from August to December 2022 at two diabetes clinics in Zahedan. The study included 300 patients with type 2 diabetes. Data collection was done using a researcher-administrated questionnaire that included demographic data, diabetes self-care activities, and self-determination constructs including autonomous support, autonomous motivation, and perceived competence. RESULTS: The mean of the overall score of self-care activities was 34.62 ± 11.86 out of a maximum of 70. Patients in the fourth quarter (wealthiest) of the socioeconomic status had the highest mean self-care score (P = 0.003). There was a significant relationship between diet score with perceived competence (P = 0.009). Perceived competence (P<0.001) and controlled self-regulation (P<0.001) were the predictors of exercise score in diabetes patients. Independent self-regulation (P<0.001, r = 0.21) and overall self-regulation (P = 0.001, r = 0.19) were significantly related to blood-glucose testing score. There was a significant relationship between foot care score with perceived competence (P = 0.048, r = 0.11) and autonomous support (P = 0.013, r = 0.14). Multiple regression showed that exercise was the predictor of HbA1c (P = 0.014). CONCLUSION: Exercise is crucial for achieving good individualized glycemic control and reducing the risk of diabetes complications. The findings provided valuable insights into the determinants of self-care activities in patients with type 2 diabetes and underscore the need for interventions that address socioeconomic disparities, enhance perceived competence, and provide autonomy support to improve diabetes self-care.

Knowledge, Attitude and Practice of Patients with Gestational Diabetes Mellitus Regarding Gestational Diabetes Mellitus: A Cross-Sectional Study.

Introduction: Self-monitoring of blood glucose levels and changes in diet and lifestyle play important roles in the management of gestational diabetes mellitus (GDM). Methods: This cross-sectional study enrolled patients with GDM at Hangzhou Women's Hospital, China, between September 1, 2022, and October 26, 2022. A questionnaire was designed that included the following dimensions: demographic/clinical information, knowledge, attitude and practice. Correlations between knowledge, attitude and practice scores were evaluated using Spearman correlation analysis. Factors associated with practice score ≥14/16 were identified using multivariate logistic regression. Results: The analysis included 499 women with GDM and a mean age of 31.22±3.89 years. The average knowledge, attitude and practice score were 11.55±3.04, 34.23±4.06 and 10.7±2.87 points, respectively. Knowledge score was positively correlated with attitude score (r=0.318, P<0.001) and practice score (r=0.351, P<0.001); attitude and practice scores were also positively correlated (r=0.209, P<0.001). Multivariate analysis identified higher knowledge score (odds ratio [OR], 1.138; 95% confidence interval [95% CI], 1.042-1.244; P=0.004) and higher attitude score (OR, 1.137; 95% CI, 1.060-1.219; P<0.001) as independently associated with good practice (ie, practice score ≥14 points). Conclusion: The results provide important insights into the knowledge, attitudes and practices of women with GDM in China regarding GDM and its management. These findings may facilitate the development and implementation of education and training programs to improve the self-management of GDM by women in China.

Monitorización flash en pacientes con diabetes mellitus tipo 1: adherencia, complicaciones y parámetros clínicos / Flash monitoring in patients with type 1 diabetes mellitus: treatment adherence, complications and clinical parameters

Objetivos: describir el perfil sociodemográfico y clínico de las personas con diabetes mellitus tipo 1 (DM1), así como el uso del dispositivo de monitorización flash Freestyle Libre (FL) en quienes se lo habían costeado por cuenta propia, y analizar las diferencias (parámetros analíticos, complicaciones de la enfermedad y adherencia al tratamiento) frente a pacientes con DM1 que utilizaban los controles glucémicos tradicionales mediante punción capilar.Método: estudio descriptivo transversal en 206 pacientes con DM1 de un área de salud en la región de Castilla-La Mancha. Variables de estudio: tener dispositivo FL por cuenta propia, variables sociodemográficas y clínicas (incluyendo parámetros analíticos) y el cuestionario validado Self Care Inventory Revised (SCI-R). Se realizaron análisis univariante y bivariante, así como un análisis multivariante de regresión logística (variable dependiente: tener el dispositivo FL por cuenta propia).Resultados: el análisis multivariante mostró que no tener el dispositivo FL era más probable en quienes tenían estudios primarios/sin estudios (OR 4,86 (IC95%: 1,03-22,88); Referencia (Ref): estudios secundarios/universitarios), dislipemia (OR 3,18 (IC95% 1,39-7,26); Ref: no dislipemia), 6 o más hipoglucemias/semana (OR 3,21 (IC95%: 1,44-7,16); Ref: menos de 6) y 4 o más punciones/día (OR: 17,56 (IC95%: 6,09-50,64); Ref: menos de 4). Tanto le media de glucosa basal como la HBA1c eran más bajas (p< 0,001) en quienes tenían el dispositivo, así como mejores puntuaciones en el SCI-R (p< 0,001).Conclusión: el uso de los dispositivos de control glucémico permite un mejor manejo de las complicaciones de la DM1: menor número de hiper e hipoglucemias, punciones y mejor adherencia al tratamiento.(AU)

Objectives: to describe the sociodemographic and clinical profile of persons with Type 1 Diabetes Mellitus (T1D), as well as the use of the FreeStyle Libre (FL) flash monitoring device in those who had paid for it out of their own pocket, and to analyse the differences (lab test parameters, disease complications and treatment adherence) vs. T1D patients using traditional glycemic monitoring through finger prick.Method: a descriptive cross-sectional study in 206 patients with T1D from a health area in the Castilla-La Mancha region. Study variables: to have a FL device purchased out of pocket, sociodemographic and clinical variables (including lab test parameters) and the validated Self Care Inventory Revised (SCI-R) questionnaire. Univariate and bivariate analyses were conducted, as well as multivariate logistical regression analysis (dependent variable: to have purchased the FL out of pocket).Results: the multivariate analysis showed that not having the FL device was more likely among those with primary education / no education (OR 4.86 (CI95%: 1.03-22.88); Reference (Ref): secondary / university education, dyslipidemias (OR 3.18 (CI95% 1.39-7.26); Ref: no dyslipidemia, 6 or more hypoglycaemias/ week (OR 3.21 (CI95%: 1.44-7.16); Ref: less than 4, or more finger pricks/day (OR: 17.56 (CI95%: 6.09-50.64); Ref: less than 4. Both the mean baseline glucose and the HBA1c were lower (p< 0.001) among those who had the device, who also had better scores in the SCI-R questionnaire (p< 0.001).Conclusion: the use of the glycemic control devices allows better management of TDI complications: a lower number of hyper and hypoglycaemias and finger pricks, and better treatment adherence.(AU)

Implementation of flash glucose monitoring in four pediatric diabetes clinics: controlled before and after study to produce real-world evidence of patient benefit.

AIMS: To assess the real-world evidence for flash glucose monitoring (Abbott FreeStyle Libre) for children with type 1 diabetes in terms of glucose control, secondary healthcare resources and costs. RESEARCH DESIGN AND METHODS: We conducted a controlled before and after study (approximately 12 months before and after) using routinely collected health record data on children who start using flash monitors and a control population of children with self-monitoring of blood glucose (SMBG). Our population-based sample of eligible individuals using flash monitoring (n=114) and controls (n=80) aged between 4 and 18 years was drawn from four paediatric diabetes clinics (secondary care) in the South West England. Outcome measures included: glycated hemoglobin (HbA1c), frequency of BG tests; frequency of sensor scans; time in recommended glucose range; short-term complications (hypoglycemia, diabetic ketoacidosis and related illness resulting in investigation) and secondary care costs. RESULTS: After adjustment for age, time since diagnosis, deprivation and the test modality (point of care or laboratory), the mean HbA1c reading for controls was 61.2 (mmol/mol) for the period before and 63.9 after. For individuals using flash monitoring, the adjusted mean HbA1c reading was 64.6 for the period before implementation and 63.8 after. Rates of short-term complications were low across all groups in the study. Whereas the 'after' flash monitoring group had substantially higher incremental costs (+£703 vs the flash monitoring 'before' comparison and +£841 vs contemporaneous SMBG controls), these cost differences were driven by primary care prescribing (sensor costs). CONCLUSIONS: There was some indication that flash monitoring might help young people improve the control of their diabetes but for our sample, the difference between finger-prick testing and flash monitoring was not clinically significant (HbA1c improvement <5 mmol/mol). Given the pace of technological change within diabetes, research efforts should now facilitate the real-time analysis of long-term routine data on flash and continuous glucose monitors.

Clinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus.

BACKGRUOUND: There was limited evidence to evaluate the association between lifestyle habits and continuous glucose monitoring (CGM) metrics. Thus, we aimed to depict the behavioral and metabolic determinants of CGM metrics in insulin-treated patients with type 2 diabetes mellitus (T2DM). METHODS: This is a prospective observational study. We analyzed data from 122 insulin-treated patients with T2DM. Participants wore Dexcom G6 and Fitbit, and diet information was identified for 10 days. Multivariate-adjusted logistic regression analysis was performed for the simultaneous achievement of CGM-based targets, defined by the percentage of time in terms of hyper, hypoglycemia and glycemic variability (GV). Intake of macronutrients and fiber, step counts, sleep, postprandial C-peptide-to-glucose ratio (PCGR), information about glucose lowering medications and metabolic factors were added to the analyses. Additionally, we evaluated the impact of the distribution of energy and macronutrient during a day, and snack consumption on CGM metrics. RESULTS: Logistic regression analysis revealed that female, participants with high PCGR, low glycosylated hemoglobin (HbA1c) and daytime step count had a higher probability of achieving all targets based on CGM (odds ratios [95% confidence intervals] which were 0.24 [0.09 to 0.65], 1.34 [1.03 to 1.25], 0.95 [0.9 to 0.99], and 1.15 [1.03 to 1.29], respectively). And participants who ate snacks showed a shorter period of hyperglycemia and less GV compared to those without. CONCLUSION: We confirmed that residual insulin secretion, daytime step count, HbA1c, and women were the most relevant determinants of adequate glycemic control in insulin-treated patients with T2DM. In addition, individuals with snack consumption were exposed to lower times of hyperglycemia and GV.

Exploring the Impact of Dawn Phenomenon on Glucose-Guided Eating Thresholds in Individuals With Type 2 Diabetes Using Continuous Glucose Monitoring: Observational Study.

BACKGROUND: Glucose-guided eating (GGE) improves metabolic markers of chronic disease risk, including insulin resistance, in adults without diabetes. GGE is a timed eating paradigm that relies on experiencing feelings of hunger and having a preprandial glucose level below a personalized threshold computed from 2 consecutive morning fasting glucose levels. The dawn phenomenon (DP), which results in elevated morning preprandial glucose levels, could cause typically derived GGE thresholds to be unacceptable or ineffective among people with type 2 diabetes (T2DM). OBJECTIVE: The aim of this study is to quantify the incidence and day-to-day variability in the magnitude of DP and examine its effect on morning preprandial glucose levels as a preliminary test of the feasibility of GGE in adults with T2DM. METHODS: Study participants wore a single-blinded Dexcom G6 Pro continuous glucose monitoring (CGM) system for up to 10 days. First and last eating times and any overnight eating were reported using daily surveys over the study duration. DP was expressed as a dichotomous variable at the day level (DP day vs non-DP day) and as a continuous variable reflecting the percent of days DP was experienced on a valid day. A valid day was defined as having no reported overnight eating (between midnight and 6 AM). ∂ Glucose was computed as the difference in nocturnal glucose nadir (between midnight and 6 AM) to morning preprandial glucose levels. ∂ Glucose ≥20 mg/dL constituted a DP day. Using multilevel modeling, we examined the between- and within-person effects of DP on morning preprandial glucose and the effect of evening eating times on DP. RESULTS: In total, 21 adults (59% female; 13/21, 62%) with non-insulin-treated T2DM wore a CGM for an average of 10.5 (SD 1.1) days. Twenty out of 21 participants (95%) experienced DP for at least 1 day, with an average of 51% of days (SD 27.2; range 0%-100%). The mean ∂ glucose was 23.7 (SD 13.2) mg/dL. People who experience DP more frequently had a morning preprandial glucose level that was 54.1 (95% CI 17.0-83.9; P<.001) mg/dL higher than those who experienced DP less frequently. For within-person effect, morning preprandial glucose levels were 12.1 (95% CI 6.3-17.8; P=.008) mg/dL higher on a DP day than on a non-DP day. The association between ∂ glucose and preprandial glucose levels was 0.50 (95% CI 0.37-0.60; P<.001). There was no effect of the last eating time on DP. CONCLUSIONS: DP was experienced by most study participants regardless of last eating times. The magnitude of the within-person effect of DP on morning preprandial glucose levels was meaningful in the context of GGE. Alternative approaches for determining acceptable and effective GGE thresholds for people with T2DM should be explored and evaluated.

Diabetes and blood glucose monitoring knowledge and practices among pharmacy professionals in Cambodia and Viet Nam: digital survey and education.

BACKGROUND: In Southeast Asia, pharmacies are critical sources of healthcare advice for under-served communities, including those with/at risk of diabetes. AIM: Explore knowledge/practices relating to diabetes and blood glucose monitoring (BGM) among pharmacy professionals in Cambodia and Viet Nam, using digital professional education to address gaps. METHODS: An online survey was distributed to pharmacy professionals in Cambodia and Viet Nam registered on SwipeRx mobile application. Eligible participants dispensed medicines and/or were involved in purchasing products, and worked at retail pharmacies stocking ≥ 1 BGM product. An accredited continuing professional development module was then made available to pharmacy professionals and students on SwipeRx in both countries. After completing the 1-2 h module, users were required to correctly answer ≥ 60% (Cambodia) or ≥ 70% (Viet Nam) of knowledge assessment questions to achieve accreditation units from local partners. RESULTS: Whereas 33% of survey respondents in Cambodia (N = 386) and 63% in Viet Nam (N = 375) reported performing blood glucose testing at the pharmacy, only 19% and 14% were aware that clients taking multiple daily doses of insulin should check blood glucose levels several times a day. Of 1,137 and 399 pharmacy professionals/students who completed the module and passed the assessment in Cambodia and Viet Nam, 1,124 (99%) and 376 (94%) received accreditation. Knowledge levels improved substantially in 10 of 14 learning areas in Cambodia and 6 of 10 in Viet Nam. CONCLUSIONS: Digital education can strengthen pharmacy professional capacity to provide comprehensive and accurate information on diabetes management and the awareness of quality BGM products in Southeast Asia.

Patient and nursing experience of flash glucose monitoring following kidney transplantation.

Flash glucose monitoring (FGM) is increasingly used for blood glucose assessment due to ease of use and is now subsidized in Australia for blood glucose measurement for patients with Type 1 Diabetes Mellitus. Dysglycaemia is common following kidney transplantation and is associated with worse outcomes and there are data to support the use of FGM post-transplant to better detect and manage changes in blood glucose levels. There is, however, no data on patient or staff perceptions of FGM, or resource implications in this setting. We prospectively evaluated patients and nursing staff experiences of FGM compared to traditional capillary glucose measurement in the immediate post-transplant setting, along with resource utilization, cost of testing, staff time taken to test and accuracy. Twenty-one kidney transplant recipients had a FGM sensor applied in the post-operative period and results compared to capillary blood glucose monitoring (CBGM) measured at least four times a day. Six-hundred-fifty-six glucose measurements were obtained, median per patient of 30 readings (IQR 10). Pearson's correlation between FGM and CBGM readings is 0.95 (p < .001). FGM readings were lower than CBGM by an average of 1.2 mmol/L (SD 0.7). Using a 5-point preference questionnaire (with ratings varying from strongly disagree-strongly agree), both patients and nurses were highly satisfied with the usability and convenience of FGM, with all preferring FGM over CBGM. Average time to perform FGM was 3.6 s versus 64 s for CBGM. In average, cost of FGM was $58 less than traditional testing per patient. FGM is an accurate, convenient and cost-effective tool that may support optimal management of glycaemic control in the post-transplant period.

Noninvasive Continuous Glucose Monitoring With a Novel Wearable Dial Resonating Sensor: A Clinical Proof-of-Concept Study.

BACKGROUND: A noninvasive, wearable continuous glucose monitor would be a major advancement in diabetes therapy. This trial investigated a novel noninvasive glucose monitor which analyzes spectral variations in radio frequency/microwave signals reflected from the wrist. METHODS: A single-arm, open-label, experimental study compared glucose values from a prototype investigational device with laboratory glucose measurements from venous blood samples (Super GL Glucose Analyzer, Dr. Müller Gerätebau GmbH) at varying levels of glycemia. The study included 29 male participants with type 1 diabetes (age range = 19-56 years). The study comprised three stages with the following aims: (1) demonstrate initial proof-of-principle, (2) test an improved device design, and (3) test performance on two consecutive days without device recalibration. The co-primary endpoints in all trial stages were median and mean absolute relative difference (ARD) calculated across all data points. RESULTS: In stage 1, the median and mean ARDs were 30% and 46%, respectively. Stage 2 produced marked performance improvements with a median and mean ARD of 22% and 28%, respectively. Stage 3 showed that, without recalibration, the device performed as well as the initial prototype (stage 1) with a median and mean ARD of 35% and 44%, respectively. CONCLUSION: This proof-of-concept study shows that a novel noninvasive continuous glucose monitor was capable of detecting glucose levels. Furthermore, the ARD results are comparable to first models of commercially available minimally invasive products without the need to insert a needle. The prototype has been further developed and is being tested in subsequent studies. TRIAL REGISTRATION NUMBER: NCT05023798.

High prevalence with no gender difference of likely eating disorders in type 1 mellitus diabetes on insulin pump.

AIM: The aim of this study was to determine the prevalence of likely eating disorders and insulin misuse in a prospective cohort of adults with type 1 diabetes mellitus (T1DM) treated with insulin pump therapy. METHODS: This prospective study was held at the participants' home. The participants completed the SCOFF questionnaire as well as a question related to insulin misuse. Information about lifestyle, medical history, insulin pump and Continuous Glucose Monitoring (CGM) data were collected. RESULTS: The analysis covered 198 participants with a median age of 51 [95% CI 38; 62] years. The prevalence of likely eating disorders was 21.7% (95% CI 16.3; 28.2) in the study population and 20.6% (95% CI 14.3; 28.6) and 24.2% (95% CI 14.6; 37.0) in males and females respectively. The prevalence of insulin misuse was 39.0% (95% CI 30.8; 47.7). There was no significant difference in prevalence between males and females for likely eating disorders and insulin misuse. The analysis of CGM data revealed no factors related to glycaemic control associated with likely eating disorders. CONCLUSION: The results of this study indicate that the prevalence of likely eating disorders is high even in a middle-aged population with a T1DM and satisfactory glucose control.

Assessing non-adjunctive CGM safety at home and in new markets (ANSHIN).

INTRODUCTION: Continuous glucose monitoring (CGM) can guide treatment for people with type 1 (T1D) and type 2 diabetes (T2D). The ANSHIN study assessed the impact of non-adjunctive CGM use in adults with diabetes using intensive insulin therapy (IIT). MATERIALS AND METHODS: This single-arm, prospective, interventional study enrolled adults with T1D or T2D who had not used CGM in the prior 6 months. Participants wore blinded CGMs (Dexcom G6) during a 20-day run-in phase, with treatment based on fingerstick glucose values, followed by a 16-week intervention phase and then a randomized 12-week extension phase with treatment based on CGM values. The primary outcome was change in HbA1c. Secondary outcomes were CGM metrics. Safety endpoints were the number of severe hypoglycaemic (SH) and diabetic ketoacidosis (DKA) events. RESULTS: Of the 77 adults enrolled, 63 completed the study. Those enrolled had mean (SD) baseline HbA1c of 9.8% (1.9%), 36% had T1D, and 44% were ≥65 years old. Mean HbA1c decreased by 1.3, 1.0 and 1.0 percentage points for participants with T1D, T2D or age ≥65, respectively (p < .001 for each). CGM-based metrics including time in range also improved significantly. SH events decreased from the run-in period (67.3 per 100 person-years) to the intervention period (17.0 per 100 person-years). Three DKA events unrelated to CGM use occurred during the total intervention period. CONCLUSIONS: Non-adjunctive use of the Dexcom G6 CGM system improved glycaemic control and was safe for adults using IIT.

Glycemia according to the Use of Continuous Glucose Monitoring among Adults with Type 1 Diabetes Mellitus in Korea: A Real-World Study.

BACKGROUND: We explored the association between continuous glucose monitoring (CGM) use and glycemia among adults with type 1 diabetes mellitus (T1DM) and determined the status of CGM metrics among adults with T1DM using CGM in the real-world. METHODS: For this propensity-matched cross-sectional study, individuals with T1DM who visited the outpatient clinic of the Endocrinology Department of Samsung Medical Center between March 2018 and February 2020 were screened. Among them, 111 CGM users (for ≥9 months) were matched based on propensity score considering age, sex, and diabetes duration in a 1:2 ratio with 203 CGM never-users. The association between CGM use and glycemic measures was explored. In a subpopulation of CGM users who had been using official applications (not "do-it-yourself" software) such that Ambulatory Glucose Profile data for ≥1 month were available (n=87), standardized CGM metrics were summarized. RESULTS: Linear regression analyses identified CGM use as a determining factor for log-transformed glycosylated hemoglobin. The fully-adjusted odds ratio (OR) and 95% confidence interval (CI) for uncontrolled glycosylated hemoglobin (>8%) were 0.365 (95% CI, 0.190 to 0.703) in CGM users compared to never-users. The fully-adjusted OR for controlled glycosylated hemoglobin (<7%) was 1.861 (95% CI, 1.119 to 3.096) in CGM users compared to never-users. Among individuals who had been using official applications for CGM, time in range (TIR) values within recent 30- and 90-day periods were 62.45%±16.63% and 63.08%±15.32%, respectively. CONCLUSION: CGM use was associated with glycemic control status among Korean adults with T1DM in the real-world, although CGM metrics including TIR might require further improvement among CGM users.

Diabetes patient preferences for glucose-monitoring technologies: results from a discrete choice experiment in Poland and the Netherlands.

INTRODUCTION: New glucose-monitoring technologies have different cost-benefit profiles compared with traditional finger-prick tests, resulting in a preference-sensitive situation for patients. This study aimed to assess the relative value adults with diabetes assign to device attributes in two countries. RESEARCH DESIGN AND METHODS: Adults with type 1 or 2 diabetes from the Netherlands (n=226) and Poland (n=261) completed an online discrete choice experiment. Respondents choose between hypothetical glucose monitors described using seven attributes: precision, effort to check, number of finger pricks required, risk of skin irritation, information provided, alarm function and out-of-pocket costs. Panel mixed logit models were used to determine attribute relative importance and to calculate expected uptake rates and willingness to pay (WTP). RESULTS: The most important attribute for both countries was monthly out-of-pocket costs. Polish respondents were more likely than Dutch respondents to choose a glucose-monitoring device over a standard finger prick and had higher WTP for a device. Dutch respondents had higher WTP for device improvements in an effort to check and reduce the number of finger pricks a device requires. CONCLUSION: Costs are the primary concern of patients in both countries when choosing a glucose monitor and would likely hamper real-world uptake. The costs-benefit profiles of such devices should be critically reviewed.

Advances in Continuous Glucose Monitoring and Integrated Devices for Management of Diabetes with Insulin-Based Therapy: Improvement in Glycemic Control.

Continuous glucose monitoring (CGM) technology has evolved over the past decade with the integration of various devices including insulin pumps, connected insulin pens (CIPs), automated insulin delivery (AID) systems, and virtual platforms. CGM has shown consistent benefits in glycemic outcomes in type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) treated with insulin. Moreover, the combined effect of CGM and education have been shown to improve glycemic outcomes more than CGM alone. Now a CIP is the expected future technology that does not need to be worn all day like insulin pumps and helps to calculate insulin doses with a built-in bolus calculator. Although only a few clinical trials have assessed the effectiveness of CIPs, they consistently show benefits in glycemic outcomes by reducing missed doses of insulin and improving problematic adherence. AID systems and virtual platforms made it possible to achieve target glycosylated hemoglobin in diabetes while minimizing hypoglycemia, which has always been challenging in T1DM. Now fully automatic AID systems and tools for diabetes decisions based on artificial intelligence are in development. These advances in technology could reduce the burden associated with insulin treatment for diabetes.