METHODS: A total of 1844 (780 males and 1064 females) known diabetics aged ≥ 35 years were identified from the South East Asia Community Observatory (SEACO) health and demographic surveillance site database.
RESULTS: 41.3% of the sample had poor glycaemic control. Poor glycaemic control was associated with age and ethnicity, with older participants (65+) better controlled than younger adults (45-54), and Malaysian Indians most poorly controlled, followed by Malay and then Chinese participants. Metabolic risk factors were also highly associated with poor glycaemic control.
CONCLUSIONS: There is a critical need for evidence for a better understanding of the mechanisms of the associations between risk factors and glycaemic control.
METHODS: A systematic search was carried out among online databases to determine eligible RCTs published up to November 2022. A random-effects model was performed for the meta-analysis.
RESULTS: A total of 36 RCTs with 1851 participants were included in the pooled analysis. It was displayed that supplementation with MP effectively reduced levels of fasting blood glucose (FBG) (weighted mean difference (WMD): -1.83 mg/dL, 95% CI: -3.28, -0.38; P = 0.013), fasting insulin (WMD: -1.06 uU/mL, 95% CI: -1.76, -0.36; P = 0.003), and homeostasis model assessment of insulin resistance (HOMA-IR) (WMD: -0.27, 95% CI: -0.40, -0.14; P 8 weeks) with high or moderate doses (≥ 60 or 30-60 g/d) of MP or whey protein (WP). Serum FBG levels were considerably reduced upon short-term administration of a low daily dose of WP (
METHODS: This was a multi-centre, open-label randomised crossover study. Twenty-four overweight/obese T1DM patients aged ⩾18 years old with HbA1c ⩾ 7.0% (53 mmol/mol) were recruited and randomised into two study arms. For first 6-week, one arm remained on standard of care (SOC), the other arm received metformin, adjunctive to SOC. After 2-week washout, patients crossed over and continued for another 6 weeks. Glycaemic variability, other glycaemic parameters and metabolic profile were monitored.
RESULTS: There were significant reduction in metformin group for GV: mean (0.18 ± 1.73 vs -0.95 ± 1.24, p = 0.014), %CV (-15.84 (18.92) vs -19.08 (24.53), p = 0.044), glycemic risk assessment of diabetes equation (-0.69 (3.83) vs -1.61 (3.61), p = 0.047), continuous overlapping net glycaemic action (0.25 ± 1.62 vs -0.85 ± 1.22, p = 0.013), J-index (-0.75 (21.91) vs -7.11 (13.86), p = 0.034), time in range (1.13 ± 14.12% vs 10.83 ± 15.47%, p = 0.032); changes of systolic blood pressure (2.78 ± 11.19 mmHg vs -4.30 ± 9.81 mmHg, p = 0.027) and total daily dose (TDD) insulin (0.0 (3.33) units vs -2.17 (11.45) units, p = 0.012). Hypoglycaemic episodes were not significant in between groups.
CONCLUSION: Metformin showed favourable effect on GV in overweight/obese T1DM patients and reduction in systolic blood pressure, TDD insulin, fasting venous glucose and fructosamine.