METHODOLOGY: A decision analytic model was developed to estimate annual burden of snakebite in seven countries, including Malaysia, Thailand, Indonesia, Philippines, Vietnam, Lao PDR, and Myanmar. Country-specific input parameters were sought from published literature, country's Ministry of Health, local data, and expert opinion. Economic burden was estimated from the societal perspective. Costs were expressed in 2019 US Dollars (USD). Disease burden was estimated as disability-adjusted life years (DALYs). Probabilistic sensitivity analysis was performed to estimate a 95% credible interval (CrI).
PRINCIPAL FINDINGS: We estimated that annually there were 242,648 snakebite victims (95%CrI 209,810-291,023) of which 15,909 (95%CrI 7,592-33,949) were dead and 954 (95%CrI 383-1,797) were amputated. We estimated that 161,835 snakebite victims (69% of victims who were indicated for antivenom treatment) were not treated with antivenom. Annual disease burden of snakebite was estimated at 391,979 DALYs (95%CrI 187,261-836,559 DALYs) with total costs of 2.5 billion USD (95%CrI 1.2-5.4 billion USD) that were equivalent to 0.09% (95%CrI 0.04-0.20%) of the region's gross domestic product. >95% of the estimated burdens were attributed to premature deaths.
CONCLUSION/SIGNIFICANCE: The estimated high burden of snakebite in ASEAN was demonstrated despite the availability of domestically produced antivenoms. Most burdens were attributed to premature deaths from snakebite envenoming which suggested that the remarkably high burden of snakebite could be averted. We emphasized the importance of funding research to perform a comprehensive data collection on epidemiological and economic burden of snakebite to eventually reveal the true burden of snakebite in ASEAN and inform development of strategies to tackle the problem of snakebite.
METHODS: This was a 12-week, double-blind, double-dummy, randomized, phase 2 clinical trial. A total of 232 male and female patients aged ≥18 and ≤65 years who were newly diagnosed with T2DM and have not received any antidiabetic drugs before and were equally randomized to receive metformin (2000 mg per day), low-dose NW Low-Glu® (content of four capsules per day), or high-dose NW Low-Glu® (content of five capsules per day). Our primary objective was to measure the mean change in HbA1c between each of the experimental arms and the metformin arm.
RESULTS: There was a significant reduction in mean HbA1c at 12 weeks compared to baseline in the low-dose (0.6 (1.4)%; p=0.002) and high-dose arms (0.8 (1.7)%; p=0.004). There was also a significant reduction in 2 hr PPG at 12 weeks in the low-dose (35.4 (74.9) mg/dL, p=0.001) and high-dose arms (24.7 (100.8) mg/dL, p=0.04). Weight reduction was significantly higher with both high-dose (1.1 (-1.7) Kg; p=0.005) and low-dose arms (0.9 (-1.5) Kg; p=0.023) compared to metformin (0.8 (-1.8) Kg). No serious AEs or deaths were reported.
CONCLUSIONS: After 3 months of treatment, NW Low-Glu® was noninferior to metformin in reducing HbA1c and 2 hr PPG, while leading to significantly higher weight reduction in newly diagnosed T2DM patients. It was also safe and well tolerated.
METHODS: Three hundred individuals aged 18-55 years of both sexes were selected for this cross-sectional study. VF was evaluated as a part of body composition analysis using BIA. The body composition variables for the prediction of prediabetes were examined using backward logistic regression. Optimal cut-off levels of VF to predict prediabetes were identified using receiver operator characteristic curve (ROC) analysis.
RESULTS: VF, total fat, and age were found to be associated with prediabetes (p ≤ 0.05). In females, the cut-off value of VF for predicting prediabetes was identified as 8 with 77.8% sensitivity and 69.3% specificity; in males, it was 11 with 84% sensitivity and 62.9% specificity.
CONCLUSION: This study contributes to the sex-specific cut-off values of VF level on BIA that can be used for predicting prediabetes in the Indian population.