Background: Chronic kidney disease (CKD) affects up to 40% of individuals with diabetes mellitus. Given the fact that CKD in diabetics may result from various non-diabetic renal disorders, kidney biopsy remains essential in cases with atypical clinical presentation. The aim of this study was to assess the prevalence of diabetic nephropathy (DN) and other non-diabetic kidney diseases (NDKD) among diabetic patients who underwent renal biopsy. We also tried to find clinical and laboratory markers predicting the presence of DN in renal tissue. Methods: A retrospective analysis of all native renal biopsies in diabetic patients performed between 2010 and 2024 in one European nephrology center. Results: The cohort included 115 diabetic patients. DN was diagnosed in 43.5% individuals. Among NDKD cases, vasculitis (8.7%), membranous nephropathy (7.8%), and amyloidosis (7.8%) were most frequent. Compared with the NDKD group, patients with DN were younger, had a longer duration of DM, more often required insulin therapy, more frequently demonstrated diabetic retinopathy (DR) and nephrotic syndrome, and exhibited higher HbA1c levels. In multivariable logistic regression, younger age, need for insulin therapy, and presence of DR were the strongest predictors of DN. Conclusions: NDKD is common among DM patients. Patient’s younger age, the need for insulin therapy, and the presence of DR are strong predictive markers for diabetic nephropathy. Renal biopsy remains the most accurate method for diagnosis and should be considered in every case of suspected NDKD.

Background/Objectives: Non-adherence to immunosuppressive medication is a principal modifiable determinant of kidney allograft survival, yet its associations with objective graft function remain inconsistent, in part because the Basel Assessment of Adherence to Immunosuppressive Medications Scale (BAASIS) dichotomises infrequent and persistent non-adherence together. We tested whether a continuous adherence measure and psychological acceptance of illness are more closely associated with graft function than BAASIS. Methods: Cross-sectional, single-centre study of 230 adult kidney transplant recipients; the primary analysis included 199 recipients with eGFR measured on the day of assessment and complete covariate data. Approximately 95% of recipients had received a deceased-donor and 5% a living-donor graft. Adherence was measured by BAASIS, the Adherence in Chronic Diseases Scale (ACDS), and the Adherence to Refills and Medications Scale (ARMS). Psychosocial covariates included the Acceptance of Illness Scale (AIS), Hospital Anxiety and Depression Scale—Modified (HADS-M), WHO Quality of Life—BREF (WHOQOL-BREF), Tilburg Frailty Indicator (TFI), and Mini-Mental State Examination (MMSE). The primary outcome was eGFR on the day of assessment; secondary and exploratory outcomes were serum creatinine and the individual eGFR slope reconstructed from annual archival records (n = 147). Multivariable linear regression adjusted for age, sex, time since transplantation, and psychosocial covariates was complemented by a linear mixed-effects model (158 recipients, 747 eGFR observations) and by sensitivity analyses, including adjustment for the immunosuppressive regimen. Results: Among 199 recipients (46.2% female; mean age 58.5 ± 14.0 years; median time since transplantation 6.5 years; calcineurin inhibitor in 95.2% of those with regimen data), 36 (18.1%) met the BAASIS criterion for non-adherence, most frequently due to timing deviation > 2 h. BAASIS non-adherence was not associated with eGFR (p = 0.14) or eGFR slope (p = 0.23). ACDS correlated with eGFR (ρ = +0.22, p = 0.002) and was independently associated with higher eGFR (β = +1.78 mL/min/1.73 m² per ACDS point, 95% CI +0.56 to +3.00; p = 0.005; adjusted R² = 0.083) and with lower log-creatinine (β = −0.051; p = 0.025). Mean eGFR across ACDS tertiles was 35.9, 40.5, and 44.6 mL/min/1.73 m² (Kruskal–Wallis p = 0.034). The association was robust to adjustment for immunosuppressive regimen and to removal of the least consistent ACDS item. The mixed-effects model showed an average eGFR decline of 1.21 mL/min/1.73 m² per year (p < 0.001), with no significant adherence × time or psychosocial × time interactions. Acceptance of illness was not independently associated with eGFR (p = 0.17). Conclusions: In kidney transplant recipients, dichotomous BAASIS screening was not associated with graft function, whereas higher continuous ACDS scores were independently associated with higher eGFR. Given the cross-sectional design, the low internal consistency of the ACDS in this sample, and the modest explained variance, these findings are hypothesis-generating and warrant prospective confirmation with objective adherence measures.

Purpose: Glomerulopathies are a heterogeneous group of diseases characterized by complex immunopathogenesis and wide clinical variability. A wide range of laboratory and histopathological tests is used to assess glomerular diseases. However, the volume of data is often too great to analyze and to provide a clear diagnosis. The rapid development of artificial intelligence (AI) methodologies, including machine learning (ML) and deep learning, facilitates the integration of histopathological, clinical, and molecular data. This foundation enables the creation of more precise and objective diagnostic models. Method: Modular expert systems based on ML algorithms (XGBoost, Random Forest, and natural language processing were implemented. A retrospective comparative analysis was performed comparing physician decisions with algorithmic recommendations in a patient cohort from the Opole University Clinical Hospital and the Wroclaw Medical University Hospital (2018–2025), comprising idiopathic membranous glomerulonephritis (iMN, n = 56), focal segmental glomerulosclerosis (FSGS, n = 127), lupus nephritis (LN, n = 31), and minimal change disease (MCD, n = 187). Results: The iMN module achieved 100% accuracy in risk categorization. Retrospective analysis revealed significant gaps in clinical practice: 13.4% of decisions were suboptimal in the FSGS group, 25.8% of diagnoses were irregular in the LN cohort, and 10.8% of diagnoses were irregular in the MCD group. Conclusion: The integration of AI into clinical practice is a key element in the evolution of “precision nephrology,” supporting the detection of subtle disease patterns and the standardization of management.

Background: The Falls Efficacy Scale-International (FES-I) is an assessment tool designed to measure the level of fear of falling in older adults. This scale was developed to evaluate how much an individual fears falling during various daily activities. The aim of the study was to assess the discriminatory power of FES-I to predict falls within 2 years. The secondary objective was to evaluate the relationship between FES-I and vascular status. Material and Methods: In this prospective study, 130 patients (mean age, 64.7 ± 14.6 years) with chronic kidney disease (CKD) were analyzed. Of these, 90 patients had nondialysis CKD: 15 had stage G3 (G3a, n = 5; G3b, n = 10), 38 had stage G4, and 37 had stage G5. The remaining 40 patients (30.7%) were prevalent patients receiving maintenance hemodialysis. The most frequent cause of CKD was hypertension and diabetes in 57 (43.8%) of patients. The Falls Efficacy Scale-International (FES-I) was used to assess fear of falling. The Charlson Comorbidity Index (CCI) was used to measure comorbidity, and the 10-year cardiovascular risk was assessed using a web-based calculator QRESEARCH Cardiovascular Risk Algorithm, version 3 (QRISK^®3), and hemodynamic parameters were measured using a Mobil-O-Graph monitor. Participants were followed for 2 years to assess the occurrence of falls. Results: During the two-year follow-up, 49 of 130 participants (37.7%) experienced at least one fall. FES-I demonstrated good discrimination for falls (AUC 0.836; bootstrap 95% CI, 0.760–0.903). In multivariable logistic regression adjusted for age, sex, dialysis status, comorbidity, and functional status, FES-I remained independently associated with falls (adjusted OR per 1-point increase, 1.145; 95% CI, 1.060–1.237; p < 0.001). Addition of FES-I to the basic clinical model increased the AUC from 0.826 to 0.874, although the difference was of borderline statistical significance in paired receiver operating characteristics (ROC) comparison (p = 0.053). The data-derived Youden-optimal threshold was 25 points; however, bootstrap analysis indicated threshold variability, and this cut-off should be considered exploratory. Conclusions: Higher FES-I scores were independently associated with falls during two-year follow-up and may provide additional prognostic information beyond selected clinical risk factors. FES-I may represent a candidate screening instrument for fall-risk assessment in CKD; however, the proposed cut-off (25 points) requires prospective external validation.

Background: In recent years, Poland has observed fluctuations in kidney biopsy frequency and shifts in diagnostic patterns. These trends likely reflect evolving clinical practice, diagnostic advancements, and changing disease epidemiology. This study aimed to analyse these changes, assess biopsy-based diagnoses across age groups, and examine sex-related variability. Methods: We conducted a single-centre, retrospective study at a university hospital in southwestern Poland, covering 2010–2024. Data from 1969 kidney biopsies were collected, within 1291 native kidney cases analysed after excluding transplant recipients. Diagnoses were correlated with patients’ age, sex, presence of diabetes, and temporal trends, and compared with previous studies. Results: Biopsy numbers increased over time, peaking in 2021 (154 procedures). Most were performed in patients aged 40–64 years (46.1%), followed by 18–39 years (39.1%) and ≥65 years (14.8%), with a rising proportion of elderly patients. Repeated biopsies occurred in 7.7% (second) and 0.6% (third biopsy). The most frequent diagnoses were IgAN (16.9%), FSGS (14.7%), and lupus nephritis (11.4%). In patients ≥65 years, amyloidosis (13.6%), FSGS (13.1%), vasculitis (13.1%), and membranous nephropathy (12%) predominated. The most marked sex-related difference involved lupus nephritis, accounting for 20.3% of diagnoses in women, who made up 82.3% of lupus nephritis cases. While most diseases showed male predominance, this was not evident for several, including IgAN and diabetic nephropathy. Conclusions: Given CKD’s underdiagnosis and frequent late detection in Poland, updated multicentre studies are needed to better recognise disease patterns and raise public awareness.

Lupus nephritis is one of the most severe manifestations of systemic lupus erythematosus and remains a major cause of chronic kidney damage and progression to end-stage renal disease. Although kidney biopsy is considered the diagnostic gold standard, its invasive nature, risk of complications, sampling limitations, and limited suitability for repeated monitoring highlight the need for reliable non-invasive biomarkers. Urinary exosomes have emerged as a promising source of renal molecular information because they are easily accessible and contain stable bioactive molecules, including microRNAs, transfer RNA-derived fragments, messenger RNAs, long non-coding RNAs, and proteins. This review summarizes available evidence on urinary exosomal biomarkers in lupus nephritis, with particular emphasis on their potential utility in diagnosis, assessment of disease activity, monitoring of treatment response, and prognosis. The literature search was conducted in PubMed and Embase using the keywords “lupus nephritis” and “urinary exosomes”. Studies were included if they investigated urinary exosomes in lupus nephritis and evaluated their relevance to disease diagnosis, activity, therapeutic response, histopathological findings, or renal outcomes. Among the analyzed biomarkers, urinary exosomal miR-146a appears to be the most consistently reported diagnostic marker, showing increased expression in active lupus nephritis and the ability to distinguish patients with renal involvement from those without nephritis. Other molecules, including selected miRNAs, tsRNAs, long RNAs, and proteins, have also shown potential clinical relevance, although their validation remains limited. Current evidence suggests that urinary exosomes may provide a non-invasive platform for improving the clinical assessment of lupus nephritis. However, most available studies are limited by small sample sizes, single-center designs, heterogeneous methodologies, and insufficient external validation. Further large-scale prospective studies are required to standardize exosome isolation and biomarker quantification and to determine whether urinary exosomal biomarker panels can complement kidney biopsy in clinical practice.