The Role of Telehealth in Improving Care Connections and Outcomes for Community Health Center Patients with Diabetes.

INTRODUCTION: Does telehealth decrease health disparities by improving connections to care or simply result in new barriers for vulnerable populations who often lack access to technology? This study aims to better understand the role of telehealth and social determinants of health in improving care connections and outcomes for Community Health Center patients with diabetes. METHODS: This retrospective analysis of Electronic Health Record (EHR) data examined the relationship between telehealth utilization and glycemic control and consistency of connection to the health care team ("connectivity"). EHR data were collected from 20 Community Health Centers from July 1, 2019 through December 31, 2021. Descriptive statistics were calculated, and multivariable linear regression was used to assess the associations between telehealth use and engagement in care and glycemic control. RESULTS: The adjusted analysis found positive, statistically significant associations between telehealth use and each of the 2 primary outcomes. Telehealth use was associated with 0.89 additional months of hemoglobin A1c (HbA1c) control (95% confidence interval [CI], 0.73 to 1.04) and 4.49 additional months of connection to care (95% CI, 4.27 to 4.70). DISCUSSION: The demonstrated increased engagement in primary care for telehealth users is significant and encouraging as Community Health Center populations are at greater risk of lapses in care and loss to follow up. CONCLUSIONS: Telehealth can be a highly effective, patient-centered form of care for people with diabetes. Telehealth can play a critical role in keeping vulnerable patients with diabetes connected to their care team and involved in care and may be an important tool for reducing health disparities.

Prevalence of and factors associated with suboptimal glycemic control among patients with type 2 diabetes mellitus attending public hospitals in the Greater Male' Region, Maldives: a hospital-based cross-sectional study.

BACKGROUND: Suboptimal glycemic control of type 2 diabetes mellitus (T2DM) which is defined as having HbA1c greater than 7% is a major public health problem in several countries, including the Maldives. The study aimed to estimate the prevalence and determine factors associated with suboptimal glycemic control among T2DM patients. METHODS: A hospital-based cross-sectional was applied to collect data from T2DM patients who attended public hospitals in the Greater Male' Region, Maldives where were one of the highest reports of T2DM and suboptimal glycemic control cases in the country between January to March 2023 by a validated questionnaire and anthropometric measurements. Five (5) ml blood specimens were collected to measure the glycated hemoglobin (HbA1c) level. Univariable and multivariable logistic regressions were employed to determine factors associated with suboptimal glycemic control of T2DM at a significant level of α = 0.05. RESULTS: A total of 341 participants were recruited for the study: 65.7% were female, 42.5% were aged 40-60 years, and 42.2% were married. The overall prevalence of suboptimal glycemic control was 50.7%. Ten variables were found to be associated with suboptimal glycemic control in multivariable logistic regression. Those aged 40-60 years (AOR = 3.35, 95% CI = 1.78-6.30), being single (AOR = 2.53, 95% CI = 1.21-5.30), preparation of food using more than three tablespoons of cooking oil (AOR = 2.78, 95% CI = 1.46-5.28), preparation of food with more than three tablespoons of sugar (AOR = 2.55, 95% CI = 1.31-4.93), no exercise (AOR = 2.04, 95% CI = 1.15-3.61), DM diagnosed with more than twenty years prior (AOR = 2.59, 95% CI = 1.34-4.99), obese body mass index (BMI) (AOR = 3.82, 95% CI = 1.75-8.32), high total cholesterol (AOR = 2.43, 95% CI = 1.36-4.35), high triglycerides (AOR = 3.43, 95% CI = 1.93-6.11), and high-level stress (AOR = 2.97, 95% CI = 1.48-5.93) were having a greater odds of having suboptimal glycemic control than those who did not have these characteristics. CONCLUSION: A large proportion of T2DM patients in the Greater Male' Region fail to control their blood glucose. Effective public health interventions should be introduced, especially interventions focused on reducing cooking oil and sugar in daily cooking practices, encouraging regular exercise, and maintaining cholesterol levels, particularly for those diagnosed with diabetes mellitus for more than 20 years prior.

Risk predictors of glycaemic control in children and adolescents with type 1 diabetes: A systematic review and meta-analysis.

OBJECTIVES: To conduct systematic evaluation of the risk predictors of glycaemic control in children and adolescents with type 1 diabetes mellitus. METHODS: Cohort studies on risk predictors of glycaemic control in children and adolescents with type 1 diabetes were retrieved from CNKI, PubMed, Web of Science, Embase databases, etc. from the construction of the repository to 3 February 2023. Literature screening was conducted according to inclusion and exclusion criteria, then data extraction of region, sample size, age, follow-up time, risk predictors, outcome indicators, etc., and quality evaluation of The Newcastle-Ottawa Scale were conducted by two researchers while the third researcher makes decisions if there are disagreements. Finally, Revman5.4 and StataMP17 were used for meta-analysis. RESULTS: A total of 29 studies were included, and the results showed that insulin pump [Weighed mean difference (WMD) = -.48, 95% CI (-.73, -.24), p < .01], high-frequency sensor monitoring, early use of insulin pumps, prospective follow-up male, white race, large body mass index-standardised scoring, conscientiousness, agreeableness of mothers, eicosapentaenoic acid, leucine and protein (p < .05) were beneficial for reducing HbA1c levels in children and adolescents with diabetes. Ketoacidosis [WMD = .39, 95% CI (.28, .50), p < .01], selective admission, higher HbA1c level at one time (p < .01), higher glutamate decarboxylase antibody at 1 month after diagnosis, lower socio-economic status, non-living with biological parents, non-two-parent family, family disorder, family history of diabetes and high carbohydrate intake (p < .05) increased HbA1c levels in children and adolescents with diabetes. CONCLUSION: For children and adolescents with type 1 diabetes mellitus, the use of insulin pump, high-frequency sensor monitoring, prospective follow-up, good family support and reasonable diet are conducive to blood glucose control, while selective admission and DKA are not. Disease characteristics and demographic characteristics of children are closely related to subsequent blood glucose control, and the relationship between diagnosis age and blood glucose control needs to be further explored.

Independent Correlates of Glycemic Control among Adults with Diabetes in South Africa.

BACKGROUND: Globally, the prevalence of diabetes is increasing, especially in low- and middle-income countries (LMICs), including those in the sub-Saharan African region. However, the independent socioeconomic correlates of glycemic control as measured by hemoglobin A1C have yet to be identified. Therefore, the aim of this analysis was to understand the independent correlates of glycemic control in South Africa. METHODS: Data from the 2016 South Africa Demographic and Health Survey on adults with diabetes were used for this analysis. The dependent variable, glycemic control, was defined using hemoglobin A1c (HbA1c). Independent variables included: age, gender, ethnicity, marital status, region, urban/rural residence, ability to read, education, insurance, wealth, occupation, and employment in the last year. Analysis of variance was used to test for differences in mean HbA1c for each category of all independent variables, and a fully adjusted linear regression model was used to identify independent correlates of glycemic control (HbA1c). RESULTS: Among the 772 people included in this analysis, there were significant differences in mean HbA1c by age (p < 0.001), ethnicity (p < 0.001), place of residence (p = 0.024), wealth index (p = 0.001), and employment in the last year (p = 0.008). Independent correlates of HbA1c included age, ethnicity, and wealth index. CONCLUSIONS: This study used data from a large diverse population with a high prevalence of diabetes in sub-Saharan Africa and provides new evidence on the correlates of glycemic control and potential targets for interventions designed to lower HbA1c and improve diabetes-related health outcomes of adults in South Africa.

Real-World Continuous Glucose Monitoring Data from a Population with Type 1 Diabetes in South Korea: Nationwide Single-System Analysis.

Background: We used continuous glucose monitoring (CGM) data to investigate glycemic outcomes in a real-world population with type 1 diabetes (T1D) from South Korea, where the widespread use of CGM and the nationwide education program began almost simultaneously. Methods: Data from Dexcom G6 users with T1D in South Korea were collected between January 2019 and January 2023. Users were included if they provided at least 90 days of glucose data and used CGM at least 70% of the days in the investigational period. The relationship between CGM utilization and glycemic metrics, including the percentage of time in range (TIR), time below range (TBR), and time above range (TAR), was assessed. The study was approved by the Institutional Review Board of Samsung Medical Center (SMC 2023-05-030). Results: A total of 2288 users were included. Mean age was 41.5 years (57% female), with average uploads of 428 days. Mean TIR was 62.4% ± 18.5%, mean TBR <70 mg/dL was 2.6% ± 2.8%, mean TAR >180 mg/dL was 35.0% ± 19.3%, mean glucose was 168.1 ± 35.8 mg/dL, mean glucose management indicator was 7.2% ± 0.9%, and mean coefficient of variation was 36.7% ± 6.0%. Users with higher CGM utilization had higher TIR (67.8% vs. 52.7%), and lower TBR <70 mg/dL (2.3% vs. 4.7%) and TAR >180 mg/dL (30.0% vs. 42.6%) than those with low CGM utilization (P < 0.001 for all). Users whose data were shared with others had higher TIR than those who did not (63.3% vs. 60.8%, P = 0.001). Conclusions: In this South Korean population, higher CGM utilization was associated with a favorably higher mean TIR, which was close to the internationally recommended target. Using its remote data-sharing feature showed beneficial impact on TIR.

Trends in clinical characteristics, medication use, and glycemic control in insulin-treated patients with type 1 and type 2 diabetes in Finland in 2012-2019: Nationwide real-world evidence study.

AIMS: To describe the clinical characteristics and medication purchases of insulin-treated adults in Finland at index (January 1, 2012 or first insulin purchase) and December 31, 2019. Additionally, to describe basal insulin (BI) treatment patterns and associated changes in hemoglobin A1c (HbA1c) values. MATERIALS AND METHODS: In this descriptive study using nationwide registries, we included adults with at least two reimbursed insulin purchases within 12 months of the first purchase between January 1, 2012 and December 31, 2019. We formed four study groups: type 1 diabetes (T1D) and type 2 diabetes (T2D)-diagnosed people who were further divided into prevalent or naïve users (start of insulin use before or after January 1, 2012). Insulin treatment patterns were estimated from medication purchase data and glycemic control from HbA1c results. RESULTS: Out of 145 020 people included, 34 359 had T1D and 110 661 T2D. By 2019, in parallel with the adaptation of new noninsulin medications, second-generation basal insulin (BI) analogues were adopted by 45.9% and 21.1% of prevalent T1D and T2D users. At index, HbA1c target (≤53 mmol/mol) was reached by 17% and 35% of T2D naïve and prevalent users, respectively, and by 17% of T1D prevalent users. At study end, the target was reached respectively by 41%, 34%, and 22% of insulin users. Insulin initiation improved and discontinuation worsened glycemic control in T2D, with lesser effects seen after treatment gaps or switches between BIs. CONCLUSIONS: Our study showed that glycemic control in insulin users has remained stable or improved between 2012 and 2019 despite aging population and in parallel with introduction of new treatment options, providing valuable insight into Finnish national diabetes care.

The Relationship Between Glycated Hemoglobin and Time in Range in a Pediatric Population.

In adults with type 1 diabetes (T1D), time in range (TIR) [70-180 mg/dL] has been proposed as an additional metric besides glycated hemoglobin (HbA1c). This retrospective monocentric cohort study determined the correlation between HbA1c and TIR during the 2, 4, and 12 weeks (TIR2w, TIR4w, and TIR12w) before consultation in a pediatric T1D population. A total of 168 children with T1D were included. Continuous glucose monitoring data, HbA1c, and demographic variables were collected. We found strong linear correlations between HbA1c and TIR2w (R = -0.571), HbA1c and TIR4w (R = -0.603), and between HbA1c and TIR12w (R = -0.624). A strong correlation exists between TIR2w and TIR12w, HbA1c and time above range (TAR), and between TIR and TAR at different time points. In conclusion, a strong correlation was found between HbA1c and TIR, making TIR a potentially complementary metric to HbA1c. TIR2w seems a viable alternative to TIR12w. TAR also seems promising in assessing glycemic control.

Role of Caregivers in Remote Management of Patients With Type 2 Diabetes Mellitus: Systematic Review of Literature.

BACKGROUND: With the growing use of remote monitoring technologies in the management of patients with type 2 diabetes mellitus (T2DM), caregivers are becoming important resources that can be tapped into to improve patient care. OBJECTIVE: This review aims to summarize the role of caregivers in the remote monitoring of patients with T2DM. METHODS: We performed a systematic review in MEDLINE, Embase, Scopus, PsycINFO, and Web of Science up to 2022. Studies that evaluated the role of caregivers in remote management of adult patients with T2DM were included. Outcomes such as diabetes control, adherence to medication, quality of life, frequency of home glucose monitoring, and health care use were evaluated. RESULTS: Of the 1198 identified citations, 11 articles were included. The majority of studies were conducted in North America (7/11, 64%) and South America (2/11, 18%). The main types of caregivers studied were family or friends (10/11, 91%), while the most common remote monitoring modalities evaluated were interactive voice response (5/11, 45%) and phone consultations (4/11, 36%). With regard to diabetes control, 3 of 6 studies showed improvement in diabetes-related laboratory parameters. A total of 2 studies showed improvements in patients' medication adherence rates and frequency of home glucose monitoring. Studies that evaluated patients' quality of life showed mixed evidence. In 1 study, increased hospitalization rates were noted in the intervention group. CONCLUSIONS: Caregivers may play a role in improving clinical outcomes among patients with T2DM under remote monitoring. Studies on mobile health technologies are lacking to understand their impact on Asian populations and long-term patient outcomes.

Prevalence and determinants of poor glycaemic control in individuals aged between 18-60 years, at a regional hospital in KwaZulu-Natal Province, South Africa- a cross sectional study.

Background: Achieving optimal blood glucose control is imperative for preventing diabetes related complications and negative socio-economic consequences associated with them. Objectives: The aim of the study was to determine the prevalence and determinants of poor glycaemic control amongst type II diabetic outpatients presenting at a regional semi-rural hospital in eThekwini district, Kwa-Zulu Natal. Methods: An observational, analytic cross-sectional study was conducted amongst 384 systematically sampled type 2 diabetes patients. Data were collected by an interviewer administered questionnaire, clinical record review and anthropometric measurements. Bivariate and multivariate analyses were performed. Results: Ninety one percent of the study population (349/384) had poorly controlled diabetes. Amongst uncontrolled diabetics, 80% (n=281) were older than 35 years' age group; 58% (n= 203) were male; 85% (n=295) completed primary school education and 93% (n=324) were overweight. Patients that were 35 years and older, female, employed, had a high body mass index, were on oral hypoglycaemic and/or insulin in combination, and receiving treatment longer than 3 years, had an increased odd of uncontrolled diabetes. Being female and receiving oral hypoglycaemic and/or insulin were significantly associated with poor blood glucose control. Conclusion: Patient that were female overweight, having a lower level of education, and greater than three-year duration of medication and on oral hypoglycaemic agent and/or insulin were more likely to have poor blood glucose control. These factors should serve as early identifiers of potential poor control and an alert clinician to adopt a more active approach to optimize treatment.

Evaluation of glycemic control and related factors among outpatients with type 2 diabetes at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia: a cross-sectional study.

BACKGROUND: The goals of glycemic management for patients with diabetes are to prevent or delay complications and optimize quality of life. However, in clinical practice, the recommended glycemic control target is difficult to achieve. Therefore, it is important to identify factors that influence the outcomes of glycemia to improve the quality of diabetic management. The study aimed to evaluate the level and factors associated with glycemic control among type 2 diabetic outpatients at Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. METHODS: A hospital-based cross-sectional study was conducted among systematically selected 325 patients with type 2 diabetes who attended diabetic clinics at Tikur Anbessa Specialized Hospital. Pretested, structured, and interviewer-administered questionnaires were used to collect sociodemographic and diabetes-related information from March 1 to May 30, 2021. HbA1c was used to assess glycemic control according to the HbA1c target of < 7% ('good' control) as recommended by the American Diabetes Association for non-pregnant adults. The HbA1c level in the range of 7-8% was defined as 'inadequate' control and 'poor' at levels > 8%. Data entry and analysis were performed using SPSS v26. Multivariate logistic regression analysis was used to identify determinants of glycemic control. RESULTS: The median level of HbA1c of the participants was 8.4% (IQR 6.8-10.1). And approximately three-quarters (73.8%) of the patients had inadequate and poor glycemic control (HbA1c ≥ 7%). Older age (AOR: 2.46, 95% CI: 1.28-6.01), DM duration of > 10 years (AOR: 3.15, 95% CI: 2.22-6.54), insulin therapy (AOR: 3.07, 95% CI: 2.10-6.12), poor diet compliance (AOR: 1.97, 95% CI: 1.28-3.52) and failure to set goals for glycemic control (AOR: 3.42, 95% CI: 2.17-5.97) were factors associated with inadequate and poor glycemic control. CONCLUSIONS: The study revealed that a significant number of diabetic patients had inadequate and poor glycemic control levels. And this was associated with older age, longer duration of DM, insulin therapy, poor diet compliance, and failure to set control goals. This requires a focus on the associated factors identified and tailored management mechanisms to maintain good glycemic control.

Prevalence of diabetic retinopathy among diabetic patients in Northwest Ethiopia-A cross sectional hospital based study.

BACKGROUND: Diabetic retinopathy is the most common microvascular complication of diabetes mellitus on eye and it is the leading cause of visual impairment among productive segment of the population. Globally, the prevalence of diabetic retinopathy is reported to be 27%. In Ethiopia, sufficient data is lacking on the prevalence of diabetic retinopathy as well as information on its predisposing factors. The study was required to assess the prevalence of diabetic retinopathy and its predisposing factors in diabetic patients attending at a General Hospital in Ethiopia. METHODS: An institution based cross sectional study was employed on 331 diabetic patients recruited with a systematic random sampling technique. Data were collected through structured questionnaire, tracing patients' medical folder and ocular health examination. Data were analyzed with Statistical Package for Social Science Version 20. Logistic regression methods of analysis were used to figure out predisposing factors of diabetic retinopathy. Adjusted odds ratio with 95% confidence interval was used to determine the strength of association. RESULT: A total of 331 diabetic patients completed the study with a response rate of 99.10%. The median duration of diabetes was 5 years. The prevalence of diabetic retinopathy was 34.1% (95%Confidence Interval (CI): 28.7%-39.3%). Low family monthly income (Adjusted Odds Ratio (AOR) = 7.43, 95% CI: 2.44-22.57), longer duration of diabetes (AOR = 1.44, 95% CI: 1.30-1.58), poor glycemic control (AOR = 4.76, 95%CI: 2.26-10.00), and being on insulin treatment alone (AOR = 3.85, 95%CI: 1.16-12.74) were independently associated with diabetic retinopathy. CONCLUSION AND RECOMMENDATION: The prevalence of diabetic retinopathy was 34.1%, higher than national and global figures. Low family monthly income, longer duration of diabetes, poor glucose control and being on insulin treatment alone were important risk factors of diabetic retinopathy. Proper diabetes self management and early screening of diabetic retinopathy in all diabetic patients were recommended.

Effect of COVID 19 pneumonia on hyperglycemia: Is it different from non COVID pneumonia?

BACKGROUND AND AIMS: Glycemic control in critical illness has been linked to outcomes. We sought to investigate if COVID pneumonia was causing disrupted glycemic control compared to historically similar diseases. METHODS: At Intermountain Healthcare, a 23-hospital healthcare system in the intermountain west, we performed a multicenter, retrospective cohort observational study. We compared 13,268 hospitalized patients with COVID pneumonia to 6673 patients with non -COVID-pneumonia. RESULTS: Patients with COVID-19 were younger had fewer comorbidities, had lower mortality and greater length of hospital stay. Our regression models demonstrated that daily insulin dose, indexed for weight, was associated with COVID-19, age, diabetic status, HgbA1c, admission SOFA, ICU length of stay and receipt of corticosteroids. There was significant interaction between a diagnosis of diabetes and having COVID-19. Time in range for our IV insulin protocol was not correlated with having COVID after adjustment. It was correlated with ICU length of stay, diabetic control (HgbA1C) and prior history of diabetes. Among patients with subcutaneous (SQ) insulin only percent of glucose checks in range was correlated with diabetic status, having Covid-19, HgbA1c, total steroids given and Elixhauser comorbidity score even when controlled for other factors. CONCLUSIONS: Hospitalized patients with COVID-19 pneumonia who receive insulin for glycemic control require both more SQ and IV insulin than the non-COVID-19 pneumonia counterparts. Patients with COVID-19 who received SQ insulin only had a lower percent of glucose checks in range.

Frequent scanning using flash glucose monitoring contributes to better glycemic control in children and adolescents with type 1 diabetes.

AIMS/INTRODUCTION: We examined the impact of scanning frequency with flash glucose monitoring on glycemic control in children and adolescents with type 1 diabetes. MATERIALS AND METHODS: The study included 85 patients, aged 14.0 ± 0.5 years, with type 1 diabetes. The median time in the target glucose range (TIR) and glycosylated hemoglobin (HbA1c) values were 50.0 ± 1.4% and 7.5 ± 0.1%, respectively. RESULTS: The median scanning frequency using flash glucose monitoring was 12.0 ± 0.4 times/day. Scanning frequency showed a significant positive correlation with TIR and an inverse correlation with HbA1c. Scanning frequency was identified to be the determinant of TIR and HbA1c by using multivariate analysis. The participants whose scanning frequency was <12 times/day were categorized as the low-frequency group (n = 40), and those who carried out the scanning >12 times/day were categorized as the high-frequency group (n = 45). Patients in the high-frequency group were more likely to be treated with insulin pumps compared with those in the low-frequency group; however, this difference was not significant (21.3 vs 5.3%, P = 0.073). The high-frequency group showed significantly greater TIR than the low-frequency group (57 ± 1.6 vs 42 ± 1.7%, P = 0.002). Furthermore, the high-frequency group showed significantly lower HbA1c levels than the low-frequency group (6.8 ± 0.1 vs 8.0 ± 0.1%, P < 0.001). CONCLUSIONS: These findings showed that patients with a higher scanning frequency had better glycemic control, with greater TIRs and lower HbA1c levels, compared with those with a lower scanning frequency. Scanning frequency of >12 times/day might contribute to better glycemic outcomes in real-world practice in children with type 1 diabetes.

The change in glycaemic control immediately after COVID-19 vaccination in people with type 1 diabetes.

AIMS: Evidence suggests that some people with type 1 diabetes mellitus (T1DM) experience temporary instability of blood glucose (BG) levels after COVID-19 vaccination. We aimed to assess this objectively. METHODS: We examined the interstitial glucose profile of 97 consecutive adults (age ≥ 18 years) with T1DM using the FreeStyle Libre® flash glucose monitor in the periods immediately before and after their first COVID-19 vaccination. The primary outcome measure was percentage (%) interstitial glucose readings within the target range 3.9-10 mmol/L for 7 days prior to the vaccination and the 7 days after the vaccination. Data are mean ± standard error. RESULTS: There was a significant decrease in the % interstitial glucose on target (3.9-10.0) for the 7 days following vaccination (mean 52.2% ± 2.0%) versus pre-COVID-19 vaccination (mean 55.0% ± 2.0%) (p = 0.030). 58% of individuals with T1DM showed a reduction in the 'time in target range' in the week after vaccination. 30% showed a decrease of time within the target range of over 10%, and 10% showed a decrease in time within target range of over 20%. The change in interstitial glucose proportion on target in the week following vaccination was most pronounced for people taking metformin/dapagliflozin + basal bolus insulin (change -7.6%) and for people with HbA1c below the median (change -5.7%). CONCLUSION: In T1DM, we have shown that initial COVID-19 vaccination can cause temporary perturbation of interstitial glucose, with this effect more pronounced in people talking oral hypoglycaemic medication plus insulin, and when HbA1c is lower.

Knowledge about the disease and adherence to treatment in patients with diabetes

Introduction: Glycemic decompensation in diabetes is one of the major factors for the development of chronic disease complications. Factors involved in the adequate control of diabetes include adherence to pharmacological treatment and knowledge about the disease.Methods: Cross-sectional study on the factors associated with adherence to drug treatment and knowledge about diabetes in diabetic patients treated at Hospital Universitário de Santa Maria between 2018 and 2019, based on the validated Morisky-Green test and on the Diabetes Knowledge Questionnaire.Results: A total of 201 patients diagnosed with diabetes were included, the majority (85.6%) of which had type 2 diabetes and were white (75.6%), with a mean age of 59.4 years. An association between insufficient knowledge about diabetes and patients with type 2 diabetes was observed. An association was found between patients with type 2 diabetes using insulin and non-adherence to drug treatment compared with patients with type 2 diabetes who did use insulin. The research also showed that non-adherence to drug treatment was associated with higher occurrence of hypoglycemia compared with patients who adhered to drug treatment.Conclusion: The data obtained in our study allows us to conclude that non-adherence to pharmacological treatment makes diabetes therapy more complicated and worsens the prognosis.

Rethinking Carbohydrate Intake and Time in Range in Children and Adolescents with Type 1 Diabetes.

The aim of this study was to evaluate the association between macronutrient intake and time in range (TIR) of 70-180 mg/dL in children and adolescents with type 1 diabetes (T1D). A multi-center study recruited patients with T1D using continuous glucose monitoring (CGM) between January 2019 and January 2020 from centers across Italy. Diet intake was recorded using three-day weighed food diaries. Nutrients were evaluated as percentages of total intake. TIR was considered at target if the percentage of readings was higher than 70%. Clinical and nutritional factors associated with TIR at target were analyzed using multiple correspondence analysis and multiple logistic regression. Data from 197 participants (53% male, median age 11.6 years, median HbA1c 55.2 mmol/mol, median TIR 60%) were analyzed. Macronutrient intake was 45.9% carbohydrates, 16.9% protein, 37.3% fat, and 13.1 g/day fiber (median values). TIR > 70% was observed in 28% of participants; their diet contained more protein (17.6%, p = 0.015) and fiber (14.4 g/day, p = 0.031) than those not at target. The probability of having a TIR > 70% was significantly higher with 40-44% consumption of carbohydrates compared with 45-50% consumption of carbohydrates and with the use of a carbohydrate counting system. Based on these results, a five percent reduction in the percentage of carbohydrate intake can help children and adolescents with T1D achieve the goal of a TIR > 70%. Both a lower and higher percentage of carbohydrate intake appears to reduce the probability of reaching the target TIR > 70%. These results require validation in other populations before being used in clinical practice.

Lower Interstitial Glucose Concentrations but Higher Glucose Variability during Low-Energy Diet Compared to Regular Diet-An Observational Study in Females with Obesity.

This is an observational study of interstitial glucose (IG) concentrations, IG variability and dietary intake under free-living conditions in 46 females with obesity but without diabetes. We used continuous glucose monitoring, open-ended food recording and step monitoring during regular dietary intake followed by a low-energy diet (LED). Thirty-nine participants completed both study periods. The mean BMI at baseline was 43.6 ± 6.2 kg/m2. Three weeks of LED resulted in a mean weight loss of 5.2% with a significant reduction in diurnal IG concentration but with greater glycemic variability observed during LED. The mean 24 h IG concentration decreased from 5.8 ± 0.5 mmol/L during the regular diet period to 5.4 ± 0.5 mmol/L (p < 0.001) during LED, while the mean amplitude of glycemic excursion increased from 1.5 ± 0.7 to 1.7 ± 0.7 mmol/L (p = 0.031). The positive incremental area under the curve at breakfast was significantly larger for LED compared to regular diet. The daily fiber intake and the glycemic index of breakfast meals were significantly associated with the glycemic variability during regular dietary intake. In conclusion, the 24 h mean IG concentration was lower but with more pronounced glycemic variability during LED compared to a regular diet.

Effect of Nutritional Habits on the Glycemic Response to Different Carbohydrate Diet in Children with Type 1 Diabetes Mellitus.

Unhealthy eating habits are associated with obesity, metabolic syndrome, and increased insulin resistance in young patients with type 1 diabetes mellitus (T1DM), and may impact the possible benefit from dietary interventions on glycaemic control. This study determines how nutritional patterns influence the quality of dietary intervention with a 30% or 50% carbohydrate diet in terms of glycaemic control measured with continuous glucose monitoring (CGM). Eating habits were obtained with a frequency-of-consumption questionnaire (FFQ-6) before the diet assessment. Altogether, we collected CGM and FFQ-6 data from 30 children (16 boys and 14 girls aged 10-17 years) with T1DM subjected to two consecutive 3-day nutritional plans. From these, 23 patients met the CGM data quality criteria for further analysis. Furthermore, high accuracy achieved in training (95.65%) and V-fold cross-validation (81.67%) suggest a significant impact of food habits in response to introduced nutritional changes. Patients who consumed more vegetables or grains (>4 times per day), more wheat products (>once per day), fewer fats (<1.5 times per day), and ranked fruit juice as the most common selection in the drinks category achieved glycaemic control more often after the introduction of a 30% carbohydrate diet, as opposed to those with different dietary patterns, whose glycaemic control was negatively impacted after switching to this diet. Additionally, the 50% carbohydrate diet was safe for all patients in the context of glycaemic control.

Association Between 25(OH)Vitamin D, HbA1c and Albuminuria in Diabetes Mellitus: Data From a Population-Based Study (VIDAMAZON).

Background: The effect of glycemic control on diabetic kidney disease (DKD) is well known. Recent evidence has suggested that Vitamin D (VD) may have a nephroprotective effect in diabetes, but the relationship between VD, glycemic control, and albuminuria has yet to be clarified. Objective: Evaluate the relationship between 25-hydroxy-vitamin D [25(OH)D], HbA1c, and albuminuria in Diabetes Mellitus (DM). Patients and Methods: Cross-sectional study with 1576 individuals with DM who had 25(OH)D, HbA1c, and albuminuria levels measured. Patients with abnormal creatinine levels were excluded, in order to avoid interference on VD levels by impaired kidney function. Results: Patients with HbA1c ≥7% had lower 25(OH)D when compared to patients with HbA1c <7% (29.7 ± 10.2 vs 28.1 ± 9.9 ng/ml, p = 0.003) and 25(OH)D levels seems to predict 1.5% of HbA1c behavior. The 25(OH)D concentrations in patients with normoalbuminuria were higher than the levels observed in those with micro or macroalbuminuria (29.8 ± 9.0 vs 26.8 ± 8.6 and 25.1 ± 7.6, respectively, p = 0.001), patients who had 25(OH)D <20 ng/ml and 25(OH)D <30 ng/ml were at a higher risk of presenting albuminuria [OR = 2.8 (95% CI = 1.6 - 4.9), p<0.001, and OR = 2.1 (95% CI = 1.3 - 4.6), p<0.001, respectively]. In our regression model, albuminuria was influenced by HbA1c (r² = 0.076, p<0.00001) and 25(OH)D (r² = 0.018, p = 0.002) independently. Conclusion: Our study found an association between vitamin D levels, HbA1c and DKD. Additionally, our data suggest that the association between urinary albumin excretion and vitamin D levels is independent of glycemic control in patients with diabetes. Even though our patients presented normal creatinine levels, it is necessary further prospective studies to confirm if this association precedes or not the loss of renal function.

Glycemic control and neonatal outcomes in women with gestational diabetes mellitus treated using glyburide, metformin, or insulin: a pairwise and network meta-analysis.

AIMS: We aimed to assess the comparative efficiency and safety of the use of glyburide, metformin, and insulin in gestational diabetes mellitus (GDM). METHODS: We searched for randomized controlled trials that compared glyburide, metformin, and insulin in GDM. Data regarding glycemic control and neonatal safety were collected and analyzed in pairwise and network meta-analyses. RESULTS: A total of 4533 individuals from 23 trials were included. Compared with glyburide, metformin reduced 2-h postprandial blood glucose (2HPG) to a greater extent (standard mean difference (SMD) 0.18; 95% credible interval (CI) 0.01, 0.34). There were significantly lower prevalence of neonatal hypoglycemia (risk difference (RD) - 0.07; 95%CI - 0.11, - 0.02) and preeclampsia (RD - 0.03; 95%CI - 0.06, 0) in the metformin group than in the insulin group. The metformin group had significantly lower birth weight (SMD - 0.17; 95%CI - 0.25, - 0.08) and maternal weight gain (SMD - 0.61; 95%CI - 0.86,- 0.35) compared with the insulin group. Network meta-analysis suggested that metformin had the highest probability of successfully controlling glycemia and preventing neonatal complications. CONCLUSIONS: The present meta-analysis suggests that metformin may be as effective as insulin for glycemic control and is the most promising drug for the prevention of neonatal and maternal complications.