Background/Objectives: Magnesium plays a crucial role in immune function, influencing immunoglobulin synthesis, antibody-dependent cytolysis, and other immune processes. In renal transplant patients, magnesium deficiency is primarily induced by calcineurin inhibitor treatment, through the reduction of magnesium transporter proteins in the renal tubules, leading to magnesium loss. Methods: To assess the correlation between serum magnesium levels and the long-term outcomes of renal graft and transplant recipients, we conducted a retrospective study on 87 patients who have had a transplant for more than 5 years, a period considered immunologically stable. We evaluated laboratory parameters such as glycemia, creatinine, total protein, and C-reactive protein (CRP), as well as demographic data, primary kidney disease, donor type, comorbidities, and infection incidence. Results: This study revealed clinical stability at over 5 years post-transplantation, with no significant differences between the 5–15 and over-15-years groups with regard to major comorbidities, except for HCV infection (p = 0.018). Reduced magnesium levels were associated with impaired renal function (p = 0.017) and inflammatory syndrome (p = 0.012). Viral infections were correlated with living donor grafts (p = 0.05), hypoproteinemia, and decreased eGFR (estimated glomerular filtration rate), while bacterial infections, namely urinary tract infections (UTIs), were linked to reduced eGFR (p = 0.05, p = 0.046). Female patients with hypomagnesemia had a higher incidence of recurrent UTIs (p = 0.03). Conclusions: Hypomagnesemia correlates with increased infection risk in patients who received a renal transplant more than 5 years ago but does not significantly impact glycemic control or cardiovascular health.

Background: Hemodialysis (HD) patients have significantly higher mortality rates compared to the general population, primarily due to complex comorbidities. This systematic review and meta-analysis aimed to evaluate and compare the performance of various machine learning (ML) models in predicting mortality among HD patients. Methods: The analysis followed PRISMA guidelines, including studies that assessed the predictive capabilities of ML models for mortality in HD patients. Review Manager software version 5.4.1. was used for meta-analysis, and the performance of ML models was compared, including logistic regression, XGBoost, and Random Forest models. Results: The meta-analysis indicated that the logistic regression model predicted a true positive mortality rate of 8.23%, close to the actual rate of 10.53%. In contrast, the XGBoost and Random Forest models predicted rates of 9.93% and 8.94%, respectively, compared to the actual mortality rate of 13.73%. The highest area under the curve (AUC) was reported for the Random Forest model at a 3-year follow-up (AUC = 0.89). No significant difference was found between the performance of logistic regression and Random Forest models (p = 0.82). Conclusions: ML models, particularly Random Forest and logistic regression, demonstrated effective predictive capabilities for mortality in HD patients. These models can help identify high-risk patients early, facilitating personalized treatment strategies and potentially improving long-term outcomes. However, the observed heterogeneity among studies indicates a need for further research to refine model performance and standardize predictive features.

Background/Objectives: Urinary tract infections (UTI) represent a global problem with implications for mortality and morbidity. Published data present different bacterial incidences and different antibiotic resistance. The objective of our study is to evaluate the bacteria distribution in positive urine cultures in a mixed adult population and evaluate the differences in antibiotic resistance in in- and outpatients. Methods: We analyzed 1186 positive urine cultures in 2021 from the Emergency County Hospital “Pius Brinzeu” from Timisoara, Romania. We evaluated the bacteria distribution and antibiotic resistance stratified by in and outpatients from a mixed adult population. Results: The median age was 67, with 65.7% females and 28.5% were outpatients. In inpatients, the most commonly identified bacteria was E. coli, followed by Enterococcus spp., and Klebsiella spp., while in outpatients, E. coli, Enterococcus spp., and Klebsiella spp. were the leading ones. Overall, E. coli presented the highest resistance rate to ampicillin, Enterococcus spp. to ciprofloxacin, Klebsiella spp. to cephalosporins, and Proteus spp. to trimethoprim/sulfamethoxazole. Inpatients presented higher resistance rates for E. coli to ceftazidime, cefuroxime, gentamycin, ciprofloxacin, and trimethoprim/sulfamethoxazole, Klebsiella spp. to most cephalosporin, gentamycin and levofloxacin, Proteus spp. to gentamycin and Enterococcus spp. to gentamycin and quinolones when compared to outpatients. The highest incidence of extensively drug-resistant (XDR) bacteria was among Acinetobacter baumanii, followed by Pseudomonas spp., and Serratia spp. Conclusions: susceptibility. Bacteria identified in inpatients’ positive urine cultures present higher resistance rates to several antibiotics. Our study could be a foundation for a local or even national guideline for the antibiotic treatment of urinary tract infections.

Introduction: Contrast-induced nephropathy (CIN) has emerged as a prevalent and serious complication associated with the administration of iodinated contrast media during diagnostic and therapeutic procedures. Given the rising global prevalence of chronic kidney disease(CKD,) it is crucial to gain a deeper understanding of the risks linked to contrast media exposure. Therefore, the aim of this study, conducted at the Vascular Surgery Clinic in a tertiary hospital in Eastern Europe (Timisoara, Romania), is to assess the incidence of CIN and identify its associated risk factors among patients undergoing endovascular interventions. Methods: This retrospective cohort study was conducted using data from patients treated at a vascular surgery clinic in Timisoara, Romania, between 1 January 2018 and 31 December 2023. The study population included adult patients who underwent scheduled endovascular procedures and had serum creatinine measurements both before and after the procedure. Results: A total of 331 patients were included in the analysis (71.42% males with a mean age of 66.79 ± 9.86 years). In total, 9.22% of the patients had CKD, while 23.8% developed CIN. The mean age was significantly higher in the CIN group (68.4 years) compared to the non-CIN group (66.32 years) with a p-value of 0.093, indicating that older age is associated with a higher risk of CIN. A multivariate logistic regression analysis was performed to assess the association between various factors and the development of CIN. Higher hemoglobin levels were associated with reduced odds of CIN (OR = 0.792, 95% CI: 0.659–0.952, p = 0.0148), indicating that anemia is a significant risk factor for CIN, while CKD significantly increased the odds of CIN by 85.8% (OR = 1.858, 95% CI: 1.105–3.125, p = 0.0023), establishing CKD as a critical risk factor for CIN. Conclusions: While anemia and CKD were found to be significant predictors of CIN, further research on a wider population is required to validate these findings and explore additional risk factors. Our study shows that, in the context of elective endovascular procedures, addressing anemia correction and stabilizing creatinine levels to baseline represents a crucial strategy for reducing the risk of CIN.

Purpose: Adaptation to chronic disease is an important factor for the quality of life of patients and their families. This research aimed to identify the psychosocial and clinical factors that determine significant differences and best predict the patients’ adaptation to chronic diseases. Understanding these factors enables the design of evidence-based preventive interventions that promote early adaptation. Patients and Methods: A quantitative, non-experimental comparative and predictive study design was conducted. Several clinical, demographic, and psychological factors were measured with an online questionnaire. This study was conducted on a convenience sample of 263 patients with chronic diseases: 63 (24%) had chronic kidney disease with dialysis dependency, 49 (18.6%) had solid neoplasms, 61 (23.2%) had hemopathies, 64 (24.3%) had HIV infection, and 26 (9.9%) had tuberculosis. Results: Adaptation to chronic disease varies based on the type of diagnosis, with lower adaptation seen in conditions that significantly impact daily life, involve comorbidities, and require frequent treatments, like chronic kidney disease. The most significant predictor of adaptation to the chronic disease is the female gender. Other predictive factors are medication adherence, social support, and self-efficacy in managing chronic disease. Patients without comorbidities and fewer medications are more prone to illness denial, alongside younger, urban, employed, and higher-educated patients, potentially neglecting treatment. Patients with comorbidities and the older patients require greater emotional support, with psychological counseling and support groups being beneficial. Conclusion: Current data underlines the need for an individualized approach to chronic disease management, which should consider demographic and psychological factors in addition to clinical ones. It is important to design early interventions for the development of adaptation to chronic disease, which could include individual and family counseling and education programs for medication administration, treatment at home, adherence to a healthy lifestyle, and inclusion of the patient and his family in social support groups.

Background: Obesity, type 2 diabetes mellitus, and hypertension are increasingly prevalent components of metabolic syndrome and major contributors to cardiovascular disease and chronic kidney disease progression; however, in end-stage kidney disease an “obesity paradox” has been described, with higher body mass index (BMI) sometimes associated with improved survival on hemodialysis. Material and methods: This retrospective, single-center Eastern European cohort study aimed to characterize mortality and its causes around hemodialysis initiation in the contemporary era of cardiometabolic prevention and to test whether the obesity paradox persists at this high-risk transition. Adult patients initiating dialysis at the “Pius Brânzeu” Emergency Clinical Hospital (Timișoara, Romania) between January 2022 and December 2025 (n = 268; median age 66 years; 61% male; median eGFR 6.4 mL/min/1.73 m²) were analyzed using Kaplan–Meier methods and Cox regression, with comprehensive baseline clinical, laboratory, echocardiographic, medication, infection, and vascular access data; follow-up was obtained at 3, 6, 12, 24, and 36 months. Results: Late referral was common (61% < 3 months of nephrology follow-up), dialysis initiation was predominantly urgent (only 16% scheduled), and central venous catheters were the main access (81%), with substantial comorbidity burden (cardiovascular disease 71%, hypertension 90%) and frequent infections at initiation. BMI categories were non-obese (<25 kg/m², 30%), overweight (25–29.9 kg/m², 48%), and obese (≥30 kg/m², 22%); diabetes prevalence rose with BMI (32% to 58%). Unadjusted mortality did not differ by BMI (19.8%, 18.8%, 15.3%; log-rank p = 0.622), yet multivariable Cox models showed overweight status independently reduced mortality (HR 0.22 at 3 months, 0.29 at 1 year, 0.31 at 3 years vs. non-obese), whereas obesity was not protective. Early mortality was driven mainly by age ≥ 65 years, while diabetes and chronic obstructive pulmonary disease predicted later mortality; longer pre-dialysis follow-up time was strongly protective (HR per year 0.70 at 3 years), and higher intact parathyroid hormone showed an inverse association with 1-year mortality. Conclusions: These findings show a modified obesity paradox at dialysis initiation in which moderate excess weight, but not obesity, is associated with improved adjusted survival, underscoring the clinical importance of earlier nephrology engagement and individualized nutritional and risk-factor management during the pre-dialysis and early dialysis periods.