METHODS: A 6-month parallel multicenter two-arm, single-blind randomized controlled trial involving 14 pharmacists at seven primary care clinics was conducted in Johor, Malaysia. Pharmacists without prior specialized diabetes training were trained to use the tool. Patients were randomized within each center to either Simpler care (SC), receiving care from pharmacists who used the tool (n =55), or usual care (UC), receiving usual care and dispensing services (n = 69).
RESULTS: Compared with UC, SC significantly reduced HbA1c (mean reduction 1.59% [95% confidence interval {CI} -2.2, -0.9] vs 0.25% [95% CI -0.62, 0.11], respectively; P ≤ 0.001), and significantly improved systolic BP (-6.28 mmHg [95% CI -10.5, 2.0] vs 0.26 mmHg [95% CI -3.74, 0.43], respectively; P = 0.005). A significantly higher proportion of patients in the SC than UC arm reached the Malaysian guideline treatment goals for HbA1c (14.3% vs 1.5%; P = 0.020), systolic BP (80% vs 42%; P = 0.001), and low-density lipoprotein cholesterol (60.5% vs 40.4%; P = 0.046).
CONCLUSIONS: Using the Simpler tool facilitated the delivery of comprehensive evidence-based diabetes management and significantly improved clinical outcomes. The Simpler tool supported pharmacists in providing enhanced structured diabetes care.
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 clinically validated insulin/glucose model was used to calculate SI with the standard fasting assumption (SFA) G0 = GTARGET. Then GTARGET was treated as a variable in a second analysis (VGT). The outcomes were contrasted across twelve participants with established type 2 diabetes mellitus that were recruited to take part in a 24-week dietary intervention. Participants underwent three insulin-modified intravenous glucose tolerance tests (IM-IVGTT) at 0, 12, and 24 weeks.
RESULTS: SIVGT had a median value of 3.36×10-4 L·mU-1·min-1 (IQR: 2.30 - 4.95×10-4) and were significantly lower ( P < .05) than the median SISFA (6.38×10-4 L·mU-1·min-1, IQR: 4.87 - 9.39×10-4). The VGT approach generally yielded lower SI values in line with expected participant physiology and more effectively tracked changes in participant state over the 24-week trial. Calculated GTARGET values were significantly lower than G0 values (median GTARGET = 5.48 vs G0 = 7.16 mmol·L-1 P < .001) and were notably higher in individuals with longer term diabetes.
CONCLUSIONS: Typical modeling approaches can overestimate SI when GTARGET does not equal G0. Hence, calculating GTARGET may enable more precise SI measurements in individuals with type 2 diabetes, and could imply a dysfunction in diabetic metabolism.
Methods: A cross-sectional study involving 503 drug naive subjects (163 males, aged 30-65 years old (mean age ± SD = 47.4 ± 8.3 years)) divided into MS, COB and NC groups. COB was defined as central obesity (waist circumference (WC) males ≥90 cm, females ≥80 cm) in the absence of MS according to the International Diabetes Federation 2006. Fasting blood levels of tPA and PAI-1were analyzed.
Results: MS and COB had significantly higher concentration of all biomarkers compared to NC. The MS group had significantly higher concentration of tPA and PAI-1 compared to COB. WC and HDL-c had significant correlation with all biomarkers (tPA p < 0.001, PAI-1 p < 0.001). Fasting plasma glucose and diastolic blood pressure were independent predictors after correcting for confounding factors.
Conclusion: Central obesity with or without MS both demonstrated enhanced prothrombogenesis. This suggests that simple obesity possibly increases the risk of coronary artery disease in part, via increased susceptibility to thrombogenesis.
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.
OBJECTIVES: To evaluate the relationship between plasma [FRA] and glucose concentration ([gluc]) as well as indices of energy balance during early lactation in dairy cattle, and to characterize the influence of plasma total protein concentration ([TP]) and albumin concentration ([albumin]) on [FRA].
ANIMALS: Convenience sample comprising 103 periparturient Holstein-Friesian cattle.
METHODS: Plasma [gluc], [TP], [albumin], and other clinicopathologic indices of energy status were determined periodically from Day 4 postpartum. Body condition score (BCS) was assessed, and backfat thickness (BFT) and longissimus dorsi muscle thickness (LDT) were measured ultrasonographically. Plasma [FRA] was measured at approximately 28 days postpartum. Associations between plasma [FRA] and study variables were evaluated using Spearman's rho and stepwise forward linear regression. Statistical significance was declared at P