PARTICIPANTS: Between 2020 and 2021, 383 children and young people with T1D who were active in the A4D supported programmes were reviewed including information on health coverage, multidisciplinary team management, diabetic ketoacidosis (DKA) on admission and insulin regimen.
RESULTS: Mean HbA1c between 2020 and 2021 for patients in these LMICs arereported for the first time. The average glycaemic index in the five SEAcountries reviewed between 2020 and 2021 were high at 83 mmol/mol (9.7%).
CONCLUSIONS: Government partnership working with non-government organisationsto support T1D from diagnosis to adulthood are the first steps to closing thegaps in many LMICs. Further epidemiological studies are needed to identify the glycaemic outcomes and DKA rates on admission for many of these countries.
METHODS: A randomized, double-blind, placebo-controlled trial was performed in a university hospital. Women with GDMA1 were recruited at 16-30 weeks of pregnancy and randomized to oral metformin 500 mg twice daily or identical placebo tablets to delivery. Level of HbA1c was taken at recruitment and at 36 weeks of pregnancy. The primary outcome was the change in level of HbA1c at recruitment and 36 weeks of pregnancy.
RESULTS: Data from 106 participants were analyzed. The level of HbA1c during pregnancy increased significantly with a mean increase of 0.20% ± 0.31% (P
METHODS: ARISE is a ~26-wk-long, prospective, non-interventional, single-arm study of patients with type 2 diabetes (T2D) initiating IDegAsp treatment. Approximately 1112 patients with T2D aged ≥18 years previously on anti-hyperglycaemic drugs except IDegAsp will be enroled across six countries from 15 Aug 2019 to 12 Nov 2020. IDegAsp treatment will be initiated at the physicians' discretion and as per the local label. Key exclusion criteria include previous participation, or previous IDegAsp treatment. The primary and secondary endpoints are change in HbA1c from baseline (wk 0) to study end (wk 26-36) and the proportion of patients achieving the target HbA1c level of <7% at the study end, respectively. A mixed model for repeated measurements will analyse the primary endpoint.
CONCLUSION: Between-country differences in the prescription patterns of glucose-lowering agents in people with T2D warrant examination of their clinical use in different geographical settings. The ARISE study is designed to assess the clinical use of IDegAsp from real world in six different countries. Findings from the ARISE study will supplement those of previous randomised controlled studies by establishing real-world evidence of IDegAsp use in the participating countries.
TRIAL REGISTRATION: ClinicalTrials.gov, NCT04042441. Registered 02 August 2014, https://clinicaltrials.gov/ct2/show/NCT04042441.
METHODS: In this cross-sectional study, interviews and a standardised questionnaire comparing lifestyle changes before and during the lockdown were performed in follow-up clinic visits after the lockdown. Anthropometry measurements and glycated haemoglobin (HbA1c) values were compared 3 months prior and after the lockdown.
RESULTS: Participants were 93 patients with T1DM (11.08 ± 3.47 years) and 30 patients with T2DM (13.81 ± 2.03 years). Male gender, T2DM and pubertal adolescents were found to have a significant deterioration in glycaemic control. A significant increment of HbA1c was observed in patients with T2DM (8.5 ± 0.40 vs 9.9 ± 0.46%), but not in patients with T1DM (8.6 ± 0.28 vs 8.7 ± 0.33%). Contrarily, there was an improved glycaemic control in pre-pubertal T1DM children likely due to parental supervision during home confinement. Weight and BMI SDS increased in T1DM patients but surprisingly reduced in T2DM patients possibly due to worsening diabetes control. Reduced meal frequency mainly due to skipping breakfast, reduced physical activity level scores, increased screen time and sleep duration were observed in both groups.
CONCLUSIONS: Adverse impact on glycaemic control and lifestyle were seen mostly in patients with T2DM and pubertal adolescent boys.
RESEARCH DESIGN AND METHODS: Multinational, prospective cohort study to assess the prevalence of newborns free from major congenital malformations or perinatal or neonatal death (primary end point) following treatment with insulin detemir (detemir) versus other basal insulins.
RESULTS: Of 1,457 women included, 727 received detemir and 730 received other basal insulins. The prevalence of newborns free from major congenital malformations or perinatal or neonatal death was similar between detemir (97.0%) and other basal insulins (95.5%) (crude risk difference 0.015 [95% CI -0.01, 0.04]; adjusted risk difference -0.003 [95% CI -0.03, 0.03]). The crude prevalence of one or more congenital malformations (major plus minor) was 9.4% vs. 12.6%, with a similar risk difference before (-0.032 [95% CI -0.064, 0.000]) and after (-0.036 [95% CI -0.081, 0.009]) adjustment for confounders. Crude data showed lower maternal HbA1c during the first trimester (6.5% vs. 6.7% [48 vs. 50 mmol/mol]; estimated mean difference -0.181 [95% CI -0.300, -0.062]) and the second trimester (6.1% vs. 6.3% [43 vs. 45 mmol/mol]; -0.139 [95% CI -0.232, -0.046]) and a lower prevalence of major hypoglycemia (6.0% vs. 9.0%; risk difference -0.030 [95% CI -0.058, -0.002]), preeclampsia (6.4% vs. 10.0%; -0.036 [95% CI -0.064, -0.007]), and stillbirth (0.4% vs. 1.8%; -0.013 [95% CI -0.024, -0.002]) with detemir compared with other basal insulins. However, differences were not significant postadjustment.
CONCLUSIONS: Insulin detemir was associated with a similar risk to other basal insulins of major congenital malformations, perinatal or neonatal death, hypoglycemia, preeclampsia, and stillbirth.
METHODS: The index prescriptions were those that when the annual blood tests were reviewed. Prescriptions of medication were verified, compared to the preceding prescriptions and classified as 1) no change, 2) stepping up and 3) stepping down. The treatment targets were HbA1c
MATERIALS AND METHODS: This was an investigator-initiated, single-center, randomized, controlled, clinical trial in patients with T2DM and DKD, comparing 12-weeks of low carbohydrate diet (<20g daily intake) versus standard low protein (0.8g/kg/day) and low salt diet. Patients in the VLCBD group underwent 2-weekly monitoring including their 3-day food diaries. In addition, Dual-energy x-ray absorptiometry (DEXA) was performed to estimate body fat percentages.
RESULTS: The study population (n = 30) had a median age of 57 years old and a BMI of 30.68kg/m2. Both groups showed similar total calorie intake, i.e. 739.33 (IQR288.48) vs 789.92 (IQR522.4) kcal, by the end of the study. The VLCBD group showed significantly lower daily carbohydrate intake 27 (IQR25) g vs 89.33 (IQR77.4) g, p<0.001, significantly higher protein intake per day 44.08 (IQR21.98) g vs 29.63 (IQR16.35) g, p<0.05 and no difference in in daily fat intake. Both groups showed no worsening of serum creatinine at study end, with consistent declines in HbA1c (1.3(1.1) vs 0.7(1.25) %) and fasting blood glucose (1.5(3.37) vs 1.3(5.7) mmol/L). The VLCBD group showed significant reductions in total daily insulin dose (39(22) vs 0 IU, p<0.001), increased LDL-C and HDL-C, decline in IL-6 levels; with contrasting results in the control group. This was associated with significant weight reduction (-4.0(3.9) vs 0.2(4.2) kg, p = <0.001) and improvements in body fat percentages. WC was significantly reduced in the VLCBD group, even after adjustments to age, HbA1c, weight and creatinine changes. Both dietary interventions were well received with no reported adverse events.
CONCLUSION: This study demonstrated that dietary intervention of very low carbohydrate diet in patients with underlying diabetic kidney disease was safe and associated with significant improvements in glycemic control, anthropometric measurements including weight, abdominal adiposity and IL-6. Renal outcomes remained unchanged. These findings would strengthen the importance of this dietary intervention as part of the management of patients with diabetic kidney disease.
OBJECTIVE: This study aimed to evaluate the impact of CMI on medication adherence and glycaemic control among patients with type 2 diabetes in Qatar.
METHODS: We developed and customised CMI for all the anti-diabetic medications used in Qatar. A randomised controlled trial in which the intervention group patients (n = 66) received the customised CMI with usual care, while the control group patients (n = 74) received usual care only, was conducted. Self-reported medication adherence and haemoglobin A1c (HbA1c ) were the primary outcome measures. Glycaemic control and medication adherence parameters were measured at baseline, 3 months, and 6 months in both groups. Medication adherence was measured using the 8-item Morisky Medication Adherence Scale (MMAS-8).
RESULTS: Although the addition of CMI resulted in better glycaemic control, this did not reach statistical significance, possibly because of the short-term follow-up. The median MMAS-8 score improved from baseline (6.6 [IQR = 1.5]) to 6-month follow-up (7.0 [IQR = 1.00]) in the intervention group. In addition, there was a statistically significant difference between the intervention and the control groups in terms of MMAS-8 score at the third visit (7.0 [IQR = 1.0]) vs 6.5 (IQR = 1.25; P-value = .010).
CONCLUSION: CMI for anti-diabetic medications when added to usual care has the potential to improve medication adherence and glycaemic control among patients with type 2 diabetes. Therefore, providing better health communication and CMI to patients with diabetes is recommended.
METHODS: Genetic analysis was performed in 42 patients with MODY aged 1 month to 18 years among a cohort of 759 patients with diabetes, identified with the following four clinical criteria: age of diagnosis ≤18 years; negative pancreatic autoantibodies; family history of diabetes; or persistently detectable C-peptide; or diabetes associated with extrapancreatic features. GCK gene mutations were first screened by Sanger sequencing. GCK mutation-negative patients were further analyzed by WES.
RESULTS: Mutations were identified in 24 patients: 20 mutations in GCK, 1 in HNF4A, 1 in INS, 1 in ABCC8, and a 17q12 microdeletion. Four previously unpublished novel GCK mutations: c.1108G>C in exon 9, and c.1339C>T, c.1288_1290delCTG, and c.1340_1343delGGGGinsCTGGTCT in exon 10 were detected. WES identified a novel missense mutation c.311A>G in exon 3 in the INS gene, and copy number variation analysis detected a 1.4 Mb microdeletion in the long arm of the chromosome 17q12 region. Compared with mutation-negative subjects, the mutation-positive subjects had lower hemoglobin A1c and initial blood glucose levels.
CONCLUSIONS: Most MODY cases in this study were due to GCK mutations, which is in contrast to previous reports in Chinese patients. Diabetes associated with extrapancreatic features should be a clinical criterion for MODY genetic analysis. Mutational analysis by WES provided a precise diagnosis of MODY subtypes. Moreover, WES can be useful for detecting large deletions in coding regions in addition to point mutations.
OBJECTIVE: This study aims to evaluate the effects of remote telemonitoring with team-based management on people with uncontrolled type 2 diabetes.
DESIGN: This was a pragmatic 52-week cluster-randomized controlled study among 11 primary care government practices in Malaysia.
PARTICIPANTS: People with type 2 diabetes aged 18 and above, who had hemoglobin A1c ≥ 7.5% but less than 11.0% within the past 3 months and resided in the state of Selangor.
INTERVENTION: The intervention group received home gluco-telemonitors and transmitted glucose data to a care team who could adjust therapy accordingly. The team also facilitated self-management by supporting participants to improve medication adherence, and encourage healthier lifestyle and use of resources to reduce risk factors. Usual care group received routine healthcare service.
MAIN MEASURE: The primary outcome was the change in HbA1c at 24 weeks and 52 weeks. Secondary outcomes included change in fasting plasma glucose, blood pressure, lipid levels, health-related quality of life, and diabetes self-efficacy.
RESULTS: A total of 240 participants were recruited in this study. The telemonitoring group reported larger improvements in glycemic control compared with control at the end of study (week 24, - 0.05%; 95% CI - 0.10 to 0.00%) and at follow-up (week 52, - 0.03%; - 0.07 to 0.02%, p = 0.226). Similarly, no differences in other secondary outcomes were observed, including the number of adverse events and health-related quality of life.
CONCLUSION: This study indicates that there is limited benefit of replacing telemedicine with the current practice of self-monitoring of blood glucose. Further innovative methods to improve patient engagement in diabetes care are needed.
TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02466880.
MATERIAL AND METHODS: This was a five-year retrospective open cohort study using secondary data from the National Diabetes Registry. The study setting was all public health clinics (n = 47) in the state of Negeri Sembilan, Malaysia. Time to treatment intensification was defined as the number of years from the index year until the addition of another oral antidiabetic drug or initiation of insulin. Life table survival analysis based on best-worst case scenarios was used to determine the time to treatment intensification. Discrete-time proportional hazards model was fitted for the factors associated with treatment intensification.
RESULTS: The mean follow-up duration was 2.6 (SD 1.1) years. Of 7,646 patients, the median time to treatment intensification was 1.29 years (15.5 months), 1.58 years (19.0 months) and 2.32 years (27.8 months) under the best-, average- and worst-case scenarios respectively. The proportion of patients with treatment intensification was 45.4% (95% CI: 44.2-46.5), of which 34.6% occurred only after one year. Younger adults, overweight, obesity, use of antiplatelet medications and poorer HbA1c were positively associated with treatment intensification. Patients treated with more oral antidiabetics were less likely to have treatment intensification.
CONCLUSION: Clinical inertia is present in the management of T2D patients in Malaysian public health clinics. We recommend further studies in lower- and middle-income countries to explore its causes so that targeted strategies can be developed to address this issue.
Methods: A cross-sectional study was conducted at the Universiti Kebangsaan Malaysia Medical Centre (UKMMC) using outpatient population diabetic patients. Demographic data on social and clinical characteristics were collected from participants. Several questionnaires were administered, including the Beck Depression Inventory-II (BDI-II) to measure depressive symptoms, the Generalized Anxiety Disorder-7 (GAD-7) to assess anxiety symptoms, the Big Five Inventory (BFI) to evaluate personality traits, and the WHO Quality of Life-BREF (WHOQOL-BREF) to assess QOL. Multivariate binary logistic regression was performed to determine the predictors of poor glycaemic control.
Results: 300 patients with diabetes mellitus were recruited, with the majority (90%) having type 2 diabetes. In this population, the prevalence of poor glycaemic control (HbA1C ≥ 7.0%) was 69%, with a median HbA1C of 7.6% (IQR = 2.7). Longer duration of diabetes mellitus and a greater number of days of missed medications predicted poor glycaemic control, while older age and overall self-perception of QOL protected against poor glycaemic control. No psychological factors were associated with poor glycaemic control.
Conclusion: This study emphasizes the importance of considering the various factors that contribute to poor glycaemic control, such as duration of diabetes, medication adherence, age, and QOL. These findings should be used by clinicians, particularly when planning a multidisciplinary approach to the management of diabetes.
METHODS: This is a cross-sectional study within the baseline data from the impact evaluation of the Enhanced Primary Health Care (EnPHC) intervention on 40 public clinics in Malaysia. Patients aged 30 and above, diagnosed with T2D, had a clinic visit for T2D between 01 Nov 2016 and 30 April 2017 and had at least one HbA1c, SBP and LDL-C measurement within 1 year from the date of visit were included for analysis. Multilevel linear regression adjusting for patient and clinic characteristics was used to quantify variation at the clinic and patient levels for each outcome.
RESULTS: Variation in intermediate clinical outcomes in T2D lies predominantly (93% and above) at the patient level. The strongest predictors for poor disease control in T2D were the proxy measures for disease severity including duration of diabetes, presence of microvascular complications, being on insulin therapy and number of antihypertensives. Among the three outcomes, HbA1c and LDL-C results provide greatest opportunity for improvement.
CONCLUSION: Clinic variation in HbA1c, SBP and LDL-C accounts for a small percentage from total variation. Findings from this study suggest that standardised interventions need to be applied across all clinics, with a focus on customizing therapy based on individual patient characteristics.
OBJECTIVE: To investigate prevalence and predictors of PREM defined by IDAA1c.
METHODS: Six hundred fourteen of 678 children (aged <15 years) with new-onset T1D (2000-2013) from a regional pediatric diabetes service (Auckland, New Zealand).
RESULTS: Overall rate of PREM at 3 months was 42.4%, and lower in Māori/Pacific children (28.6%; P = .006) and those of other ethnicities (28.8%; P = .030) compared with New Zealand Europeans (50.4%). Comparing the most and least deprived socioeconomic quintiles, the odds of PREM were lower among the most deprived (adjusted odds ratio [aOR] 0.44; P = .019). Lower rates of PREM were seen in children aged 0 to 4.9 years (23.8%) and 10 to 14 years (40.9%) than in children aged 5 to 9.9 years (57.4%; P
METHODS: Patients who were 10 to less than 17 years of age were randomly assigned, in a 1:1 ratio, to receive subcutaneous liraglutide (up to 1.8 mg per day) or placebo for a 26-week double-blind period, followed by a 26-week open-label extension period. Inclusion criteria were a body-mass index greater than the 85th percentile and a glycated hemoglobin level between 7.0 and 11.0% if the patients were being treated with diet and exercise alone or between 6.5 and 11.0% if they were being treated with metformin (with or without insulin). All the patients received metformin during the trial. The primary end point was the change from baseline in the glycated hemoglobin level after 26 weeks. Secondary end points included the change in fasting plasma glucose level. Safety was assessed throughout the course of the trial.
RESULTS: Of 135 patients who underwent randomization, 134 received at least one dose of liraglutide (66 patients) or placebo (68 patients). Demographic characteristics were similar in the two groups (mean age, 14.6 years). At the 26-week analysis of the primary efficacy end point, the mean glycated hemoglobin level had decreased by 0.64 percentage points with liraglutide and increased by 0.42 percentage points with placebo, for an estimated treatment difference of -1.06 percentage points (P<0.001); the difference increased to -1.30 percentage points by 52 weeks. The fasting plasma glucose level had decreased at both time points in the liraglutide group but had increased in the placebo group. The number of patients who reported adverse events was similar in the two groups (56 [84.8%] with liraglutide and 55 [80.9%] with placebo), but the overall rates of adverse events and gastrointestinal adverse events were higher with liraglutide.
CONCLUSIONS: In children and adolescents with type 2 diabetes, liraglutide, at a dose of up to 1.8 mg per day (added to metformin, with or without basal insulin), was efficacious in improving glycemic control over 52 weeks. This efficacy came at the cost of an increased frequency of gastrointestinal adverse events. (Funded by Novo Nordisk; Ellipse ClinicalTrials.gov number, NCT01541215.).
METHODS: A cross-sectional investigation was conducted at General Penang Hospital, Malaysia. Demographic criteria and laboratory tests of patients were investigated. Controlled glycemia (CG) was recognized as glycated hemoglobin (HbA1c) ≤7% depending on American Diabetes Association guidelines 2018. Charlson Comorbidity Index (CCI) was used to estimate the confounding influence of co-morbidities and predict ES-10Y. Data was managed by IBM-SPSS 23.0.
RESULTS: A total of 400 cases categorized to (44.25%) patients with CG, and (55.75%) cases had uncontrolled glycemia (UCG). HbA1c mean in CG and UCG group was (6.8 ± 0.9 vs 9.5 ± 1.6, P-value: 0.001). Fasting blood glucose was (7 ± 2.3 vs. 9.9 ± 4.3, P-value: 0.001) in CG and UCG group. CCI was (3.38 ± 2.38 vs. 4.42 ± 2.70, P-value: 0.001) and, ES-10Y was (62% vs 46.2%, p-value: 0.001) in CG vs. UCG respectively. Spearman test indicates a negative correlation between CG and CCI (r: 0.19, p-value: 0.001). Logistic regression confirmed HbA1c as a significant predictor of CCI (r2: 0.036, P-value: 0.001). CG has a positive correlation with survival (r: 0.16, P-value: 0.001) and logistic regression of survival (r2: 0.26, P-value: 0.001).
CONCLUSIONS: More than one-half of the investigated persons had UCG. Controlled HbA1c was associated with lower co-morbidities and higher ES-10Y.