Background Telemedicine has the potential to improve patient care and management for various chronic diseases such as type 2 diabetes. To ensure the success of any telemedicine program, there is a need to understand the patients’ satisfaction and their preferences. This review aims to collate and provide evidence related to practices that may influence the performance of telemedicine for patients with type 2 diabetes. Methods We searched three electronic databases for studies examining patients’ satisfaction and preferences for using telemedicine in type 2 diabetes. An evaluation matrix was developed to collect the data from the included articles. A total of 20 articles were identified and data on the key outcomes identified were narratively synthesized. Results Patients were generally satisfied with the use of telemedicine for management of type 2 diabetes. Users reported that telemedicine was beneficial as it provided constant monitoring, improved access to healthcare providers, and reduced waiting time. When adopting a telemedicine platform, most patients expressed preference for mobile health (mHealth) as the telemedicine modality, especially if it has been endorsed by their physician. To improve usability and sustainability, patients suggested that modules related to diabetes education be enhanced, together with sufficient technical and physician support when adopting telemedicine. Patients also expressed the importance of having a sufficiently flexible platform that could be adapted to their needs. Conclusion Personalized telemedicine strategies coupled with appropriate physician endorsement greatly influences a patient’s decision to undertake telemedicine. Future work should focus on improving telemedicine infrastructure and increasing physician’s involvement, especially during the implementation phase.

Aims: To compare the cardiovascular, renal and safety outcomes of second-line glucose-lowering agents used in the management of people with type 2 diabetes.Methods: MEDLINE, EMBASE and CENTRAL were searched from inception to 13 July 2021 for randomised controlled trials comparing second-line glucose lowering therapies with placebo, standard care or one another. Primary outcomes included cardiovascular and renal outcomes. Secondary outcomes were non-cardiovascular adverse events. Risk ratios (RRs) and corresponding confidence intervals (CI) or credible intervals (CrI) were reported within pairwise and network meta-analysis. The quality of evidence was evaluated using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) criteria. Number needed to treat (NNT) and number needed (NNH) to harm were calculated at 5 years using incidence rates and RRs. PROSPERO (CRD42020168322). Results:We included 38 trials from seven classes of glucose-lowering therapies. Both sodium-glucose co-transporter-2 inhibitors (SGLT2i) and glucagon-like peptide 1 receptor agonists (GLP1RA) showed moderate to high certainty in reducing risk of 3-point major adverse cardiovascular events, 3P-MACE

Good blood glucose control is important to reduce the risk of adverse effects on mothers and their offspring in women with gestational diabetes (GDM). This review examined the impact of using digital health interventions on reported glycaemic control among pregnant women with GDM and its impact on maternal and foetal outcomes. Seven databases were searched from database inception to October 31st, 2021 for randomised controlled trials that examined digital health interventions to provide services remotely for women with GDM. Two authors independently screened and assessed the studies for eligibility for inclusion. Risk of bias was independently assessed using the Cochrane Collaboration’s tool. Studies were pooled using random effects model and presented as risk ratio or mean difference with 95% confidence intervals. Quality of evidence was assessed using GRADE framework. Twenty-eight randomised controlled trials that examined digital health interventions in 3,228 pregnant women with GDM were included. Moderate certainty of evidence showed that digital health interventions improved glycaemic control among pregnant women, with lower fasting plasma glucose (mean difference -0.33 mmol/L; 95% CI: -0.59 to -0.07), 2-hour post-prandial glucose (-0.49 mmol/L; -0.83 to -0.15) and HbA1c (-0.36%; -0.65 to -0.07). Among those randomised to digital health interventions, there was a lower need for caesarean delivery (Relative risk: 0.81; 0.69 to 0.95; high certainty) and foetal macrosomia (0.67; 0.48 to 0.95; high certainty). Other maternal and foetal outcomes were not significantly different between both groups. Moderate to high certainty evidence support the use of digital health interventions, as these appear to improve glycaemic control and reduce the need for caesarean delivery. However, more robust evidence is needed before it can be offered as a choice to supplement or replace clinic follow up. Systematic review registration: PROSPERO: CRD42016043009.

Background Diabetes is one of the leading cause of chronic kidney disease (CKD) and end stage renal disease. This study aims to develop and validate different risk predictive models for incident CKD and CKD progression in people with type 2 diabetes (T2D). Methods We reviewed a cohort of people with T2D seeking care from two tertiary hospitals in the metropolitan cities of the state of Selangor and Negeri Sembilan from January 2012 to May 2021. To identify the three-year predictor of developing CKD (primary outcome) and CKD progression (secondary outcome), the dataset was randomly split into a training and test set. A Cox proportional hazards (CoxPH) model was developed to identify for predictors of developing CKD. The resultant CoxPH model was compared with other machine learning models on their performance using C-statistic. Results The cohorts included 1 992 participants, of which 295 had developed CKD and 442 reported worsening of kidney function. Equation for the three-year risk of developing CKD included gender, haemoglobin A1c, triglyceride and serum creatinine levels, estimated glomerular filtration rate, history of cardiovascular disease and diabetes duration. For risk of CKD progression, the model included systolic blood pressure, retinopathy and proteinuria. The CoxPH model was better at prediction compared to other machine learning models examined for incident CKD (C-statistic: training 0.826; test 0.874) and CKD progression (C-statistic: training 0.611; test 0.655). Risk calculator can be found at https://rs59.shinyapps.io/071221/. Conclusions The Cox regression model was the best performing modelto predict people with T2D who will develop a 3-year risk of incident CKD and CKD progression in a Malaysian cohort.

Objectives Data on the long-term effects comparing sodium-glucose co-transporter 2 inhibitors (SGLT2i) and dipeptidyl peptidase-4 inhibitors (DPP4i) are scarce, especially from middle-income countries. To examine the effects of SGLT2i and DPP4i on the cardiorenal function and treatment adherence for people with type 2 diabetes (T2D) using prevalent new-user design in real-world setting. Methods We conducted a retrospective cohort study in two tertiary hospitals in Malaysia and matched T2D patients initiated on SGLT2i or DPP4i from 2010 to 2021 using time-conditional propensity score. Outcomes of interest included cardiovascular and renal outcomes, as well as clinical lab outcomes, adherence and non-persistence. The hazard ratios for cardiorenal outcomes was inferred using Cox proportional hazards model. Key findings The cohort included 1528 patients, with 406 SGLT2i users matched with 406 DPP4i users. Over a median follow-up of 1.52 years, no differences in cardiorenal outcomes were observed. Patients initiated with SGLT2i had lower HbA1c at 12-month (-0.79%,p<0.001) compared to DPP4i (-0.49%,p<0.05; difference:-0.30%,p<0.05). No differences in the renal, lipid, weight and blood pressure parameters were observed between both groups. Higher medication persistence was noted among SGLT2i users compared to DPP4i users (92% vs 87%,P=0.03). Conclusions Both medications were comparable in exerting distinct effects on cardiorenal risk factors, with better HbA1c control and medication persistence among SGLT2i users. The long-term cardiorenal outcomes remains undetermined.