Chronic kidney disease (CKD) represents one of the leading causes of morbidity and mortality worldwide, being diabetes its first cause. Besides the strict management of risk factors (i.e. hyperglycemia, hypertension and dyslipidemia), several pharmacological strategies aiming at reducing the progression of CKD, including ACE-inhibitors, have been proposed. Finerenone is the first non-steroidal selective mineralocorticoid receptor antagonist (ns-MRA) drug developed for the treatment of diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D). Its properties include a high selectivity for MRs with a lower incidence of side effects such as gynecomastia and hyperkalemia with respect to older steroidal MRAs. In addition, a significant reduction of fibrosis, inflammation and hypertrophy both on myocardium and kidney has been observed. At present, several studies demonstrating the efficacy and safety of finerenone on clinical outcomes have been published. In the phase III studies, FIDELIO-DKD and FIGARO-DKD, finerenone significantly reduced the combined primary endpoints (progression of chronic kidney disease, renal failure or renal death for renal outcomes, and cardiovascular mortality, non-fatal myocardial infarction, non-fatal stroke or hospitalisation for heart failure for cardiovascular outcomes) when compared to placebo and added to the standard of care. A pooled-analysis (FIDELITY) performed on a prespecified pool of patients derived from the combination of the previous two studies confirmed the ability of finerenone to significantly reduce both the incidence or progression of DKD and cardiovascular events. A higher incidence of hyperkalemia in patients treated with finerenone compared to placebo was confirmed. However, the incidence of adverse events with clinical impact was low, and only 1,7% of finerenone-treated patients versus 0,6% of placebo-treated patients discontinued treatment during a 3-year follow-up. Finerenone broadly demonstrates an effective renal and cardiovascular protective capacity in patients with T2D and DKD in the presence of good safety in its use.

KEY WORDS: diabetic nephropathy; cardiovascular disease; end stage renal disease; type 2 diabetes.

There has long been strong emphasis on personalization in the treatment of diabetes; evidence of individual differences in symptomatology, presentation, behavior, preferences, social status, response to treatment, comorbidity or clinical course have led clinicians to seek greater focus on the individual. However, this approach cannot yet be called Precision Medicine in diabetes. In this article we want to describe the state of the art of Precision Medicine starting from the two Consensus documents published by the Precision Medicine in Diabetes Initiative (PMDI) born in 2018 within American Diabetes Association (ADA) and European Association for the Study of Diabetes (EASD) with the aim of understanding the state of the art, the possibilities of application and future lines of research in the construction of a precision medicine applied to diabetes. The five pillars of precision medicine applied to diabetes will be examined: precision diagnosis, precision prevention, precision treatment, precision prognostics and precision monitoring. Following will be described the fields of applications and the possible developments and insights, also within italian diabetological reality.

KEY WORDS precision medicine; diabetes; personalization; diagnosis; prevention.

In the Covid 19 pandemic, diabetes mellitus (DM) has been identified as one of the comorbidities associated with the most severe forms of the infection, with an increase in hospitalization and mortality. The aim of the study was to evaluate which clinical variables were associated with severe forms of Covid-19 (with or without pneumonia), in people with type 2 DM (DM 2), regularly attending Italian diabetes services, participating to the data collection of Annals 2021.
MATERIALS
DM2 patients assisted during 2020 by the diabetes services participating to the AMD Annals Initiative were evaluated. The presence of Covid-19 was recorded using the appropriate ICD-9 codes relating to forms with and without pneumonia. Anthropometric parameters, blood tests and therapy werealso specifically assessed.
RESULTS
The presence of Covid-19 was reported in 2,331 cases (0.6%): 1,299 patients were affected by Covid-19 without pneumonia (55.7%), while 1,032 patients were affected by infection associated with pneumonia (44, 3%). The risk of infection with pneumonia increased with increasing age and the risk of severe forms was almost 50% higher in males (OR=1.48; 95% CI 1.23-1.79), while it was about 50% lower in people with diabetes duration greater than 10 years than in those with diabetes duration of 5 years or less. The risk of acquiring an infection with pneumonia was strongly associated with kidney function, particularly with albuminuria.
CONCLUSIONS
Despite some limitations related to the under recording of the event in the elecronic chart, our data confirm that DM2 patients with more severe COVID-19 infections were on average older, male, with higher mean HbA1c levels and with a higher prevalence albuminuria, but they did not differ for BMI, lipid profile, blood pressure, and estimated glomerular filtration rate from those who experienced milder forms.

KEYWORDS Covid 19; T2 diabetes mellitus; AMD annals.

Artificial Intelligence (AI) is a tremendous resource. Undoubtedly the medical profession must be equipped for proper training so that these new technologies can be integrated into day-to-day operations, including clinical activities. Scientific societies, whose mission is to ensure the professional growth of the graduates, and who support their members in their professional life, play an important role in the training courses. The mission of Scientific societies is also to “take them to the future by guaranteeing high skills”, therefore it is essential to move in this direction as AMD has been doing for several years. One of the hallmarks of transparent AI algorithms is that make explicit the patterns and reasoning behind the decisions they make and suggest. This enables a clinician to intervene and to some extent guide the machine’s reasoning. AMD’s choice was to adopt transparent AI solutions, and it has begun a number of projects using its Annali database with the adoption of a Machine Learning tool with clear rules, the Logic Learning Machine, for its analyses. This experience revealed that, in addition to the notable advantages of the speed and efficiency of the analysis process, this technology fulfils a “steering function” guiding analysts and diabetologists in the study, in the in-depth analysis and in interpreting the findings, which may be: explanatory (what is this), predictive (what will be) and scenario simulation (what if).

KEY WORDS artificial Intelligence; machine learning; descriptive analysis; predictive analysis; prescriptive analysis; what-if analysis.

Since few years Glucose monitoring, which contributes to good metabolic control, has available a new tool, sensors, which automatically and continuously measure interstitial glucose levels in two modes: continuous (Continuous Glucose Monitoring) and flash (Flash Glucose Monitoring). Flash Glucose Monitoring has been shown to be efficient and improve the quality of life in type 1 diabetic patients; and also for type 2 diabetic patients there are a growing number of studies, which have evaluated efficacy, the frequency of hypoglycemia and glycemic variability in these patients. The purpose of this review is to take stock of use of Flash Glucose Monitoring in type 2 diabetic patients by examining international studies and Italian experiences, also reporting data on the costs and savings generated by use of this new technology.

KEY WORDS Flash Glucose Monitoring; type 2 diabetes; basal-bolus insulin therapy; elderly with type 2 diabetes; diabetes costs.

The Gender medicine strategic group of AMD promoted an online survey in summer 2022 in order to know the size of violence in the workplace in the diabetologist community and this phenomenon can be correlated to lacks of Risk Assessment in the workplaces. We asked 20 questions about any experiences of violence suffered in the workplaces. The partecipants were 137, mainly women (71,5%). The most representative age range is 45 - 60 years (43,1%). About half of the respondents (46%) regardless of genders had been subjected of some form of violence during the exercise of profession, more often in surgeries daily, mainly by male patients, while women are mainly exposed to the risk of both verbal and physical violence. Among the subjects who have suffered experience of violence, in 74,6% of cases the phenomenon was repeated. Probably this data cannot exclude that some health workers due to personal characteristics or context are more often the target of this phenomenon, especially since health services and or companies do not provide readily available and effective strategies for rescue and or escape. It is a low propensity to report the violence and the lack of standardized procedures for the report management. Establishing a violence prevention program must the business goal aimed at guaranteeing safety in the workplace.

KEY WORDS violence in the workplace; diabetology; age; gender; violence prevention program.