Bogdan Vlacho

Background: Erectile dysfunction (ED) is highly prevalent among men with type 2 diabetes mellitus (T2DM) and reflects systemic vascular and metabolic dysfunction. Shared mechanisms include endothelial dysfunction, oxidative stress, inflammation, autonomic neuropathy, and hypogonadism. Therefore, ED may function not only as a complication of T2DM but also as an early clinical marker of cardiometabolic disease. Objective: This narrative review summarizes current evidence on the epidemiology, mechanisms, and cardiometabolic implications of ED in men with T2DM, and evaluates the impact of major cardiometabolic therapies on erectile function. A real-world cohort study was conducted using the TriNetX Global Collaborative Network, a large federated electronic health record database comprising healthcare organizations across multiple countries. Content: ED is closely linked with hypertension, obesity, dyslipidaemia, heart failure, ischemic heart disease, and stroke in men with T2DM, reflecting shared microvascular and macrovascular diseases. Cohort and real-world studies indicate a strong bidirectional relationship: poor cardiometabolic control worsens erectile function, whereas improvements in glycaemia, weight, blood pressure, and lipids are associated with higher International Index of Erectile Function (IIEF) scores. Using data from the TriNetX Global Collaborative Network, large-scale real-world analyses further demonstrate that the coexistence of ED and T2DM substantially increases cardiovascular risk. In a propensity-score-matched cohort (>200,000 individuals per group), men with ED and T2DM had higher risks of ischemic heart disease (15.7% vs. 11.5%, OR: 1.44; 95% CI 1.41-1.46), stroke (OR 1.45; 95% CI 1.42-1.48), peripheral artery disease (OR 1.38; 95% CI 1.35-1.41), and heart failure (8.4% vs. 4.9%, OR 1.78; 95% CI 1.74-1.81). Conversely, among individuals with T2DM, the presence of ED was associated with increased ischemic heart disease, stroke, and peripheral artery disease. Mechanistic and clinical data suggest heterogeneous treatment effects: GLP-1 receptor agonists and SGLT2 inhibitors show promising vascular benefits with mixed erectile outcomes, whereas ARBs and finerenone appear favorable compared with older agents associated with sexual adverse effects. Conclusion: ED in T2DM should be regarded as a clinically relevant marker of systemic vascular disease. Routine assessment may enhance cardiovascular risk stratification and motivate earlier, comprehensive risk-factor intervention. Future prospective and randomized studies with erectile function as a predefined endpoint are needed.

Background: The management of type 2 diabetes mellitus (T2DM) remains a complex clinical challenge, particularly for patients requiring multiple daily insulin injections (MDI). Advances in precision medicine and continuous glucose monitoring (CGM) have created opportunities to personalize treatment and potentially reduce the therapeutic burden on people with T2DM. Assessing β cell function and autoimmunity could help identify patients with T2DM eligible for simplified regimens without compromising glycemic control. Objective: The aim of this study is to test a simple personalized medicine protocol in routine clinical practice for people with T2DM treated with MDI. The intervention is based on evaluating C-peptide and glutamic acid decarboxylase autoantibody status with the goal of improving diagnostic accuracy and optimizing treatment. Methods: This is a pragmatic before-and-after intervention study involving people with T2DM currently receiving MDI across primary care centers and a referral hospital in the Lleida health care region in Catalonia (Spain). Eligible participants will undergo clinical and laboratory assessment, including C-peptide and glutamic acid decarboxylase autoantibody testing, and wear a CGM device. On the basis of a predefined algorithm, patients may either continue or discontinue prandial insulin. The primary outcome is the proportion of patients in whom prandial insulin is discontinued and remains discontinued over 6 months. Secondary outcomes include changes in hemoglobin A _1c , CGM metric variables, quality of life, adherence, and treatment satisfaction. Results: Recruitment was completed on March 31, 2025. The follow-up phase is ongoing and expected to conclude by September 30, 2025. Data analysis will begin thereafter. Conclusions: This study will evaluate the feasibility and impact of implementing a personalized therapeutic approach for persons with T2DM receiving MDI in real-world clinical settings. If effective, this strategy could contribute to safer, simpler, and more individualized diabetes care.

Fasting during Ramadan is widely practiced, with nearly a quarter of the world’s population identifying as Muslim. However, it remains unclear whethe

Chronic kidney disease (CKD) is a major global health concern, often underdiagnosed in primary care settings. This study aimed to assess CKD screening practices using estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR) among individuals in a primary care population in Girona Sud, Catalonia. A cross-sectional analysis was conducted using anonymised electronic health records from Girona Sud primary care centres. We included active patients aged ≥ 15 years with a recorded medical history. Demographic, clinical, and laboratory data, including eGFR and UACR, were analysed. CKD was defined as eGFR < 60 ml/min/1.73 m² and/or UACR ≥ 30 mg/g. Descriptive and inferential statistical analyses were performed. Among the studied population (N = 230,922), 37% had mildly decreased eGFR (60–89 ml/min/1.73 m²), while 3% had more advanced CKD (G3b-G5). Albuminuria was mostly A1 (89%), with moderate (9.4%) and severe (1.8%) cases observed. Screening was more frequent in patients with type 2 diabetes, hypertension, and dyslipidaemia. Renal protective drugs, such as ACE inhibitors, ARBs, and SGLT2 inhibitors, were mainly prescribed in early CKD stages. Early-stage CKD is prevalent in our primary care population, particularly among those with cardiometabolic conditions. It is important to optimize the CKD detection and management in primary care. Despite the availability of renal protective treatments, their underutilization in advanced stages of CKD highlights missed opportunities for timely and optimal intervention.

Establishing risk factors associated with severity and prognosis in the early stages of the disease is important to identify patients who need specialized care. Creating new clinical tools to improve health decisions and outcomes in the population is essential. This study aimed to identify prognostic factors associated with poor outcomes of COVID-19 at diagnosis in Primary Health Care (PHC).We conducted a retrospective, longitudinal study using the SIDIAP database, part of the PHC Information System of Catalonia. The analysis included COVID-19 cases diagnosed in patients aged 18 and older from March 2020 to September 2022. Follow-up was conducted for 90 days post-diagnosis or until death. Various machine learning models of differing complexities were used to predict short-term events, including mortality and hospital complications. Each model was tailored to maximize the predictive accuracy for poor outcomes, exploring algorithms such as Generalized Linear Models, flexible GLMs with Lasso, Gradient Boosting Models, and Support Vector Machines, with the model demonstrating the highest Area Under the Curve (AUC) selected for optimal performance. A total of 2,162,187 COVID-19 cases were identified across five epidemic waves. Key predictors of short-term complications included age and the epidemic wave. Additional significant factors encompassed social deprivation (MEDEA), blood pressure, cardiovascular history, chronic obstructive pulmonary disease (COPD), obesity, and diabetes mellitus. The models exhibited high performance, with AUC values ranging from 0.73 to 0.95. A web application was developed to estimate the risk of adverse outcomes based on individual patient profiles ( https://dapcat.shinyapps.io/CovidScore ). In addition to age and epidemic wave, predictors such as social deprivation, diabetes mellitus, obesity, COPD, cardiovascular disease, high blood pressure, and dyslipidemia significantly indicate poor prognosis in COVID-19 patients diagnosed in PHC, and the developed application facilitates risk quantification for individual patients.