A Network Meta-Analysis of the Dose-Response Effects of Dapagliflozin on Efficacy and Safety in Adults With Type 1 Diabetes.

Background: Most patients with type 1 diabetes (T1DM) do not reach the blood glucose goal with treatment of insulin. In our research, we intended to estimate the therapeutic effect and safety of additional different doses of dapagliflozin on insulin treatment in T1DM. Methods: We performed direct and indirect network meta-analysis using Bayesian models and graded different dosages of dapagliflozin by mixed therapy contrasts. We retrieved information from the PubMed, Embase, The Cochrane Library, Web of Science, China Biology Medicine (CBM) disc, China National Knowledge Infrastructure (CNKI), Wanfang Data, and WEIPU Data. Our research included randomized controlled trials (RCTs) including T1DM treated with insulin and additional dapagliflozin 5 mg or dapagliflozin 10 mg from January 2012 to June 2021. Thirteen RCTs with 10,701 participants were divided into three groups as below: insulin alone, dapagliflozin 5 mg + insulin, and dapagliflozin 10 mg + insulin. Results: Dapagliflozin dose-dependently exhibited reductions in glycated hemoglobin (HbA1c), total insulin daily dose (TDD), and body weight. Neither dapagliflozin 5 mg nor 10 mg could induce hypoglycemia or severe hypoglycemia. However, both doses of dapagliflozin increased the incidence of diabetic ketoacidosis (DKA) and genital infection. Conclusions: Dapagliflozin 10 mg could achieve a better outcome in efficacy and could not increase the risk of hypoglycemia. Although it may induce a higher risk of DKA and genital infection, there was no significant difference between dapagliflozin 10 mg and 5 mg. Our outcomes indicate that dapagliflozin 10mg has a high reliability of being graded prior as a supplementary treatment to insulin in T1DM.

A study on the relationship between air pollution and pulmonary tuberculosis based on the general additive model in Wulumuqi, China.

OBJECTIVE: This study aimed to explore the impact of atmospheric pollutants on the incidence of tuberculosis (TB), and provide new ideas for the prevention and control of TB in the future. METHODS: It explored the relationship between air pollutants and meteorological factors, as well as between air pollutants and heating through Spearman correlation analysis and rank sum test. Additionally, it analyzed the relationship between air pollutants and TB incidence using the general additive model. Statistical analysis results at the p<0.05 level were considered significant. RESULTS: Three months after exposure to air pollutants (PM2.5, SO2, NO2, and CO) TB incidence increased. However, TB incidence increased 9 months after exposure to PM10. The single pollutant model showed when concentrations of PM2.5, PM10, SO2, NO2, CO, and O3 increased by 1µg/m3 (or 1mg/m3), the number of TB cases increased by 0.09%, 0.08%, 0.58%, 0.42%, 6.9%, and 0.57%, respectively. The optimal multi-pollutant model was a two-factor model (PM10+NO2). CONCLUSION: Air pollutants including PM2.5, PM10, SO2, NO2, CO, and O3 increased the risk of TB. Few studies have been conducted in this area of research, especially regarding the mechanism. The results of this study should contribute to the understanding of TB incidence and prompt additional research.

Modelling Seasonal Brucellosis Epidemics in Bayingolin Mongol Autonomous Prefecture of Xinjiang, China, 2010-2014.

Brucellosis is one of the severe public health problems; the cumulative number of new human brucellosis cases reached 211515 from 2010 to 2014 in China. Bayingolin Mongol Autonomous Prefecture is situated in the southeast of Xinjiang, where brucellosis infection occurs every year. Based on the reported data of newly acute human brucellosis cases for each season in Bayingolin Mongol Autonomous Prefecture, we proposed a susceptible, exposed, infected, and vaccinated (SEIV) model with periodic transmission rates to investigate the seasonal brucellosis transmission dynamics among sheep/cattle and from sheep/cattle to humans. Compared with the criteria of MAPE and RMSPE, the model simulations agree to the data on newly acute human brucellosis. We predict that the number of newly acute human brucellosis is increasing and will peak 15325 [95% CI: 11920-18242] around the summer of 2023. We also estimate the basic reproduction number R0 = 2.5524 [95% CI: 2.5129-2.6225] and perform some sensitivity analysis of the newly acute human brucellosis cases and the basic reproduction number R0 in terms of model parameters. Our study demonstrates that reducing the birth number of sheep/cattle, raising the slaughter rate of infected sheep/cattle, increasing the vaccination rate of susceptible sheep/cattle, and decreasing the loss rate of vaccination are effective strategies to control brucellosis epidemic.