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 (
MATERIALS AND METHODS: This longitudinal study included 2198 participants with mean age 43.4 ± 7.7 years, who underwent dental examinations in Yokohama, Japan, at two time points, 2003-2004 and 2008-2009, at an interval of 5 years. Periodontal condition was assessed by the mean value of probing pocket depth (PPD) and clinical attachment level (CAL). Glycaemic status was assessed by fasting glucose and glycated haemoglobin (HbA1c).
RESULTS: The cross-lagged panel models showed the effect of HbA1c at baseline on mean PPD at follow-up (β = 0.044, p = .039). There was a marginal effect of fasting glucose on the mean PPD (β = 0.037, p = .059). It was similar to the effect of fasting glucose or HbAlc on mean CAL. However, in the opposite direction, no effect of mean PPD or CAL at baseline on fasting glucose or HbAlc at follow-up was identified.
CONCLUSIONS: This study demonstrated a unidirectional relationship between glycaemic status and periodontal condition. The study population, however, had mostly mild periodontitis. Future studies are needed to investigate the effect of periodontal condition on glycaemic status in patients with severe periodontitis.
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.
METHODS: Data of 328 eligible housewives who participated in the MyBFF@Home study was used. Intervention group of 169 subjects were provided with an intervention package which includes physical activity (brisk walking, dumbbell exercise, physical activity diary, group exercise) and 159 subjects in control group received various health seminars. Physical activity level was assessed using short-International Physical Activity Questionnaire. The physical activity level was then re-categorized into 4 categories (active intervention, inactive intervention, active control and inactive control). Physical activity, blood glucose and lipid profile were measured at baseline, 3rd month and 6th month of the study. General Linear Model was used to determine the effect of physical activity on glucose and lipid profile.
RESULTS: At the 6th month, there were 99 subjects in the intervention and 79 control group who had complete data for physical activity. There was no difference on the effect of physical activity on the glucose level and lipid profile except for the Triglycerides level. Both intervention and control groups showed reduction of physical activity level over time.
CONCLUSION: The effect of physical activity on blood glucose and lipid profile could not be demonstrated possibly due to physical activity in both intervention and control groups showed decreasing trend over time.
METHODOLOGY: ARISE, an open-label, multicenter, non-interventional, prospective study was conducted between August 2019 and December 2020. Adult Malaysian patients with T2DM who were enrolled from 14 sites received IDegAsp as per the local label for 26 weeks. The primary endpoint was change in glycated hemoglobin (HbA1c) levels from baseline to end of study (EOS).
RESULTS: Of the 182 patients included in the full analysis set, 159 (87.4%) completed the study. From baseline to EOS, HbA1c (estimated difference [ED]: -1.3% [95% CI: -1.61 to -0.90]) and fasting plasma glucose levels (ED: -1.8 mmol/L [95% CI: -2.49 to -1.13]) were significantly reduced (p<0.0001). The patient-reported reduced hypoglycemic episodes (overall and nocturnal) during treatment. Overall, 37 adverse events were observed in 23 (12.6%) patients.
CONCLUSION: Switching or initiating IDegAsp treatment resulted in significant improvements in glycemic control and a reduction in hypoglycemic episodes.
Methodology: 148 patients on hemodialysis were analysed, 91 patients had end-stage-diabetic-renal disease (DM-ESRD), and 57 patients had end-stage-non-diabetic renal disease (NDM-ESRD). Glycemic patterns and PHH data were obtained from 11-point and 7-point self-monitoring blood glucose (SMBG) profiles on hemodialysis and non-hemodialysis days. PHH and its associated factors were analysed with logistic regression.
Results: Mean blood glucose on hemodialysis days was 9.33 [SD 2.7] mmol/L in DM-ESRD patients compared to 6.07 [SD 0.85] mmol/L in those with NDM-ESRD (p<0.001). PHH occurred in 70% of patients and was more pronounced in DM-ESRD compared to NDM-ESRD patients (72.5% vs 27.5%; OR 4.5). Asymptomatic hypoglycemia was observed in 18% of patients. DM-ESRD, older age, previous IHD, obesity, high HbA1c, elevated highly-sensitive CRP and low albumin were associated with PHH.
Conclusion: DM-ESRD patients experienced significant PHH in our cohort. Other associated factors include older age, previous IHD, obesity, high HbA1c, elevated hs-CRP and low albumin.
Methodology: We conducted a cross-sectional study using 6-days CGMS to detect the prevalence of hypoglycaemia in 31 insulin-treated pregnant women with diabetes who achieved HbA1c <6.0%. Patients were required to log-keep their self-monitoring blood glucose (SMBG) readings and hypoglycaemia events.
Results: Eight women experienced confirmed hypoglycaemia with additional seven experienced relative hypoglycaemia, giving rise to prevalence rate of 45.2% (one had both confirmed and relative hypoglycaemia). Nine relative hypoglycaemia and 17 confirmed hypoglycaemic events were recorded. Sixteen (94%) out of 17 confirmed hypoglycaemia events recorded by CGMS were asymptomatic and were missed despite performing regular SMBG. Nocturnal hypoglycaemia events were recorded in seven women. Univariable analysis did not identify any association between conventional risk factors and hypoglycaemia events in our cohort.
Conclusion: Insulin-treated pregnant women with diabetes who achieved HbA1c <6.0% were associated with high prevalence of hypoglycaemia. Asymptomatic hypoglycaemia is common in our cohort and frequently missed despite regular SMBG. Present study did not identify any association between conventional risk factors and hypoglycaemia events in our cohort.