https://www.selleckchem.com/products/Acadesine.html is also useful for the implementation of a decision support system using the temporal machine learning prediction model, as it can assist the clinicians to make correct decisions during the obstetric examinations and remind pregnant women to manage their weight. The results of this study are helpful for the birthweight prediction and development of guidelines for clinical delivery treatments. It is also useful for the implementation of a decision support system using the temporal machine learning prediction model, as it can assist the clinicians to make correct decisions during the obstetric examinations and remind pregnant women to manage their weight. Although the benefits of sodium-glucose cotransporter 2 inhibitors (SGLT2i) on cardiovascular events have been reported in patients with type 2 diabetes mellitus (T2DM) with or without heart failure (HF), the impact of SGLT2i on cardiac remodelling remains to be established. We searched the PubMed, Embase, Cochrane Library and Web of Science databases up to November 16th, 2020, for randomized controlled trials reporting the effects of SGLT2i on parameters of cardiac structure, cardiac function, plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) level or the Kansas City Cardiomyopathy Questionnaire (KCCQ) score in T2DM patients with or without chronic HF. The effect size was expressed as the mean difference (MD) or standardized mean difference (SMD) and its 95% confidence interval (CI). Subgroup analyses were performed based on the stage A-B or stage C HF population and HF types. Compared to placebo or other antidiabetic drugs, SGLT2i showed no significant effects on left ventricular mass index,fraction. The use of SGLT2i was associated with significant improvements in cardiac diastolic function, plasma NT-proBNP level, and the KCCQ score in T2DM patients with or without chronic HF, but did not significantly affect cardiac structural parameters indexed by bo