A transparent machine learning algorithm uncovers HbA1c patterns associated with therapeutic inertia in patients with type 2 diabetes and failure of metformin monotherapy.

Aims: This study aimed to identify and categorize the determinants influencing the intensification of therapy in Type 2 Diabetes (T2D) patients with suboptimal blood glucose control despite metformin monotherapy.

Methods: Employing the Logic Learning Machine (LLM), an advanced artificial intelligence system, we scrutinized electronic health records of 1.5 million patients treated in 271 diabetes clinics affiliated with the Italian Association of Medical Diabetologists from 2005 to 2019.

Profiles of sulfonylurea use in Diabetes Mellitus type 2: an analysis of clinical practice over the last 10 years.

Aims: Describing the evolution over time in the use of sulfonylureas (SUs) and the characteristics of patients at first prescription and at interruption of treatment with SUs.

Methods: Retrospective evaluation of data from the Italian Association of Diabetologists (AMD) Annals registry (2010-2020), about T2D patients who started treatment with SUs. The longitudinal probability of remaining on SUs was estimated by Kaplan Meier survival curves.

Achieving Good Metabolic Control Without Weight Gain with the Systematic Use of GLP-1-RAs and SGLT-2 Inhibitors in Type 2 Diabetes: A Machine-learning Projection Using Data from Clinical Practice.

Purpose: Recently, the 2022 American Diabetes Association and European Association for the Study of Diabetes (ADA-EASD) consensus report stressed the importance of weight control in the management of patients with type 2 diabetes; weight control should be a primary target of therapy. This retrospective analysis evaluated, through an artificial-intelligence (AI) projection of data from the AMD Annals database-a huge collection of most Italian diabetology medical records covering 15 years (2005-2019)-the potential effects of the extended use of sodium-glucose co-transporter 2 inhibitors (SGLT-2is) and of glucose-like peptide 1 receptor antagonists (GLP-1-RAs) on HbA and weight.

Methods: Data from 4,927,548 visits in 558,097 patients were retrospectively extracted using these exclusion criteria: type 1 diabetes, pregnancy, age >75 years, dialysis, and lack of data on HbA or weight.

Time to Treatment Intensification in Patients Receiving DPP4 Inhibitors Sulfonylureas as the First Add-On to Metformin Monotherapy: A Retrospective Cohort Study.

To verify whether, in patients on metformin (MET) monotherapy for type 2 diabetes (T2D), the add-on of a dipeptidyl peptidase inhibitor (DPP4i) compared to a sulfonylurea (SU) can delay the time to the subsequent treatment intensification (TI). Population-based administrative data banks from four Italian geographic areas were used. Patients aged ≥18 years on MET monotherapy receiving first DPP4i or SU dispensing between 2008 and 2015 (cohort entry) were followed up to the occurrence of TI (insulin dispensing or add-on of a third non-insulin hypoglicemic >180 days after cohort entry), treatment discontinuation, switch, cancer, death, TI occurrence within, end of data availability, end of study period (31 December 2016), whichever came first.

Impact of severe and symptomatic hypoglycemia on quality of life and fear of hypoglycemia in type 1 and type 2 diabetes. Results of the Hypos-1 observational study.

Background And Aims: Hypoglycemia represents a relevant burden in people with diabetes. Consequences of hypoglycemia/fear of hypoglycemia on quality of life (QoL) and behaviors of patients with T1DM and T2DM were assessed.

Methods And Results: HYPOS-1 was an observational retrospective study.