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.
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.
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: A retrospective observational study of 60 type 1 and 100 type 2 diabetes subjects. All underwent professional continuous glucose monitoring (CGM) for 3-6 days and recorded self-monitored blood glucose (SMBG). Indices were calculated from both CGM and SMBG. Statistical analyses included regression and area under receiver operator curve (AUC) analyses.
RESULTS: Hypoglycemia frequency (53.3% vs. 24%, P