Renal tubular epithelial cells (RTECs) are increasingly recognized as key players in kidney diseases. They integrate metabolic, inflammatory, and fibrotic signals. This article reviews new data suggesting that RTECs could function as central integrators within diagnostic networks, linking cellular stress responses to detectable blood and urine biomarkers. We discuss the latest advances in multi-omics, extracellular vesicles, and single-cell technologies that enable precise identification of RTEC states. Finally, we discuss the potential of RTEC-centric diagnostics and highlight current limitations in early disease recognition, stratification, and the development of personalized therapeutic interventions.

OBJECTIVES:Urinalysis is essential for detecting kidney disease, urinary tract infections, and diabetes mellitus. Point-of-care testing enables rapid screening in decentralized settings and supports low-throughput laboratories. This study evaluated the Sysmex UC-1000 according to the 2023 EFLM urinalysis guidelines in a real-life clinical point-of-care setting. METHODS:In total, 331 urine samples were analyzed on the UC-1000 using MEDITAPE™ UC-12S strips, of which 129 were processed by medical laboratory technologists (MLTs) and 202 by nurses at Ghent University Hospital, Belgium. All samples were reanalyzed within stability limits using reference methods (UC-3500, Cobas pro/c503, or Architect c16000). RESULTS:Imprecision based on reflectance data ranged from 0.3 % to 7.1 %, depending on the parameter and concentration level. Minimum ordinal scale agreement met EFLM criteria for all parameters in both groups, except urobilinogen and creatinine in nurses. Trueness analysis demonstrated optimal (<10 %) false-positive rates (FPR) at the limit of detection for all parameters except leukocyte esterase (MLTs and nurses) and protein-to-creatinine ratio, which met the desirable criteria (<20 %). Albumin and albumin-to-creatinine ratio exceeded desirable criteria, with FPR of 22.5-47.3 % in both groups. EFLM criteria for false-negative rates within the grey zone and above the limit of confirmation were met for all parameters. Diagnostic sensitivity and specificity ranged from 95.0 to 100 % and 52.7 to 100 %, respectively, with no significant differences between MLTs and nurses except for higher albumin specificity in nurses. CONCLUSIONS:The UC-1000 shows strong concordance with the UC-3500, meets EFLM performance specifications, and reliably detects clinically significant albuminuria and proteinuria, supporting its use in point-of-care settings.

OBJECTIVES:Value in healthcare has been defined as the ratio between clinical outcomes and costs, providing a valuable framework for laboratory medicine as well. Implementing this concept in laboratory medicine - referred to as Value-Based Laboratory Medicine (VBLM) - requires a shift from volume-driven activities to outcome-oriented practice. In particular, the value-based score (V-BS) represents a pragmatic tool for assessing and benchmarking laboratory performance. METHODS:The V-BS was designed by the experts of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Committee on the Value-Based Score (C-BS) and piloted in 12 European clinical laboratories of different sizes. Participating laboratories completed a structured Excel-based questionnaire covering five domains. Scores were assigned from 0 to 1 for each requirement and weighted to generate a final score out of 100. Descriptive statistics were used to summarize total and domain-specific performance. RESULTS:All invited laboratories completed the pilot evaluation. Total scores ranged from 44.64 to 86.18, with a mean of 68.90 and a median of 71.21. The highest scores were observed for indicators related to traceability throughout the total testing process and quality of laboratory information, whereas clinical interaction was consistently the weakest domain. CONCLUSIONS:The data reported by the clinical laboratories participating in the pilot study demonstrate strong interest in this initiative. Although relevant differences in value-based laboratory performance were observed across the 12 participating sites, overall satisfactory performance was achieved for most indicators related to traceability and quality of laboratory information. In contrast, indicators related to clinical interaction consistently received the lowest scores.

BACKGROUND:Urinalysis is a standard clinical test that includes the microscopic examination of urinary sediment to identify formed elements. Manual evaluation by laboratory technicians is time-intensive and subject to human error. Automated analysis using digital microscopy images presents a potential alternative. This study evaluates the integration of a deep learning approach to automatically classify urinary sediment images in the clinical laboratory, including independent prospective validation of its performance. METHODS:An annotated data set comprising 13 classes of urinary sediment elements was created from a database of Sysmex UD-10 digital microscope images. An EfficientNet-based model was trained and tested across three experimental scenarios to evaluate the effects of data collection strategies on performance. Uncertainty calibration was examined. The model's robustness and interpretability were examined using gradient-weighted class activation mapping (Grad-CAM) to visualize influential image regions and t-distributed stochastic neighbor embedding (t-SNE) to analyze learned feature embeddings. Lastly, a graphical user interface was developed for a prospective evaluation in the laboratory. RESULTS:The model achieved approximately 97% overall accuracy on the test set. Experiments revealed sensitivity to data set variability, suggesting that performance may improve by integrating additional training examples. Confidence scores aligned with accuracy, and interpretability analyses showed that the model focused on relevant image regions and learned embeddings demonstrated clear class separation. In the prospective evaluation, top 1 and top 3 accuracies decreased to approximately 78% and 92%, respectively. CONCLUSIONS:Our results indicate that a lightweight deep learning model can achieve high performance in classifying urine particles. Analysis of discrepancies between retrospective and prospective evaluations provides important insights toward reliable clinical application.

OBJECTIVES:The performance of a novel urine particle analyzer, fluidlab 2 (Anvajo GmbH, Dresden, Germany), was evaluated against phase-contrast visual microscopy according to the most recent EFLM European Urinalysis Guideline. METHODS:The fluidlab 2 device combines digital holographic microscopy with neural network-based object detection for particle classification. Its compact benchtop design is suitable for bedside use, reducing turnaround times. The analytical performance (imprecision, linearity, LoQ) was evaluated according to the 2023 EFLM Urinalysis Guideline. Method comparison involved the analysis of 450 urine samples, assessing RBC, WBC, and SEC counts against visual microscopy using Passing-Bablok regression and Spearman's correlation. Bland-Altman plots were used to evaluate the agreement with clinical performance standards, while weighted Cohen's kappa was used to measure diagnostic agreement on an ordinal scale. RESULTS:By applying Dahlberg's procedure, a desirable relative coefficient of variation R(CV) ≤2.0 was obtained for RBC and WBC. Linearity of up to 7 × 106/L and 6 × 106/L was achieved. The estimated LoQ at CV=30 % reached 20 × 106/L for RBC and 5 × 106/L for WBC. Spearman's correlation coefficient against visual microscopy was 0.86, 0.92 and 0.94 for RBC, WBC and SEC, respectively. Agreement with visual microscopy (Cohen's weighted kappa) was 0.92 for RBC, 0.93 for WBC, 0.96 for SEC, 0.86 for casts, 0.82 for non-SEC, 0.33 for crystals and 0.51 for bacterial counts. CONCLUSIONS:Fluidlab 2 provides desirable imprecision for RBC and WBC, and meets the criteria for linearity and LoQ. Cohen's weighted kappa coefficients show an optimal comparison to visual microscopy for RBC, WBC and SEC and a minimum comparison for casts and non-SEC. This evaluation demonstrated promising results for the use of the fluidlab 2 analyzer in a clinical setting to detect kidney-related diseases based on urine particle analysis.

The accuracy of urinalysis relies on proper sample handling, including collection, transport, and storage. Delays, inadequate temperature control, and lack of preservatives can compromise test quality. The VACUETTE® Urine STB Tube (Greiner Bio-One, Austria) is a sterile, pierceable, evacuated PET urine collection tube with a spray-dried stabilizer offering improved tube performance. This multicentric prospective study aimed to evaluate the analyte stability and precision performance of the Urine STB Tube for urine biochemistry, test strip, and particle analysis. The study took place between May and December 2024 at Cerba HealthCare Belgium laboratory and Ghent University Hospital in Belgium, using 411 anonymized leftover urine samples from two sites. These samples were analyzed for urinary creatinine, urea, uric acid, total protein, albumin, calcium, potassium, and chloride (Roche Cobas c702). Test strip analysis (Roche Cobas U601) and particle counts (erythrocytes, leukocytes, etc.) using automated microscopy (Roche U701) and fluorescence flow cytometry (FFC) (Sysmex UF-5000) were performed. The stability of analytes was assessed by comparing initial results (T0) with measurements taken at 4h, 8h, 24h, 48h, and 72h at room temperature. Bias between T0 and subsequent time points was acceptable if below the Total Change Limit (TCL). For the semiquantitative test strip and particles count analysis, a change of no more than one level in 95% of the samples was deemed acceptable, while for qualitative parameters, 95% had to remain consistent (positive or negative) compared with the T0 results. Analytical performance was evaluated by comparing imprecision for urine biochemistry, test strips, and particle counts between the STB tube and BD Vacutainer® Urinalysis Preservative Plus (UPT) Urine Tube. Coefficients of variation (CV) with 95% confidence intervals (CI) were compared. Imprecision was acceptable if the 95% CI lower bound of CV was = 1, otherwise compared with Acceptable Change Limit (ACL) and TCL. The same criteria from the stability study were applied for test strips and particle counts. All tested quantitative parameters in samples collected in STB tubes were stable at room temperature up to 72h. Further, all tested particle counts using both automated microscopy and FFC were stable at room temperature up to 72h, except for crystals, which were stable up to 8h when using the microscopy method. Additionally, stability was confirmed for all test strip parameters up to 72h, except for blood which was stable for 24h. Both STB and UPT tubes met the defined acceptance criteria for imprecision within tubes, between tubes and across different lots for all examined parameters. The VACUETTE® Urine STB Tube provides excellent analyte stability for up to 72h and robust precision performance for urine biochemistry, test strip, and particle analysis. Blood on test strips and crystals in automated microscopy, were less stable (24h and 8h, respectively). Whereas blood test strip assay was most probably affected by the rapid loss of hemoglobin’s pseudoperoxidase activity over time, due to its sensitivity to various preservatives, the low stability of crystals warrants further investigation, as this instability was observed only in automated microscopy and not in FFC.

The Ukrainian translation of the Guideline will facilitate more effective implementation of clinical recommendations into the routine practice of medical laboratories, by ensuring accessibility for a broader audience of professionals, simplifying the adaptation of international standards, and promoting the dissemination of advanced laboratory practices in Ukraine. This translation has been made possible through the collaboration of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) with Ukrainian professional organizations, including: NGO “Educational Institute of Clinical Laboratory Diagnostics” All-Ukrainian Association of Clinical Chemistry and Laboratory Medicine (AACCLM) NGO “School of Clinical Microbiologists” The translation was carried out thanks to the dedicated efforts of academic staff from the following departments: Department of Clinical Laboratory Diagnostics, Danylo Halytsky Lviv National Medical University Department of Clinical Laboratory Diagnostics, Shupyk National Healthcare University of Ukraine Department of Laboratory Medicine, Zaporizhzhia State Medical and Pharmaceutical University Department of Military Therapy, Ukrainian Military Medical Academy We hope that the publication of the translated Guideline in the Ukrainian Journal of Laboratory Medicine will contribute to its widespread use among professionals. The publication was made possible with the support of HLR LLC. We believe this translation will serve as a valuable tool for improving the professional competence of Ukrainian specialists and will enhance the quality of laboratory diagnostics, particularly in the area of urinalysis, which remains insufficiently standardized in Ukraine. Important: EFLM NSs/Associations are eligible to translate official EFLM documents into their local language, publish it in their NS journals and send a link to the PDF of the Translation to EFLM. This is a Ukrainian translation of The EFLM European Urinalysis Guideline 2023. The Association of Clinical Chemistry and Laboratory Medicine of Ukraine prepared this translation without any funding support. The publication of this version was made possible through the financial support of HLR LLC. The EFLM has not endorsed nor approved the contents of this translation. The official version of the Document is located at www.EFLM.eu. Users should cite this official version when citing the document: https://www.degruyter.com/document/doi/10.1515/cclm-2024-0070/html

Clinical laboratories play an important role in the diagnosis and monitoring of chronic kidney disease (CKD). Our aim was to evaluate the performance of qualitative and semi-quantitative albumin-to-creatinine ratio (ACR) and protein-to-creatinine ratio (PCR) test strip results as screening tools for albuminuria in multiple representative patient cohorts. ACR and PCR were evaluated in both cross-sectional (n = 940) and validation (n = 927) patient cohorts. Semi-quantitative urinary ACR and PCR were performed using a UC-3500 instrument (Sysmex, Kobe, Japan). The diagnostic performance of semi-quantitative ACR and PCR was determined using quantitative ACR and PCR as reference method. In the cross-sectional cohort, a sensitivity and specificity of 78.1

Bladder cancer (BCa) is a highly recurrent malignancy that requires sensitive and noninvasive diagnostic and predictive markers. Conventional diagnostic tools, such as cystoscopy and urine cytology, are far from ideal in terms of sensitivity, specificity, and patient compliance. In this narrative review, the development of novel urinary markers for the diagnosis of BCa is highlighted, with a focus on their application in the clinical arena, detection accuracy, and future potential. An extensive analysis of new urinary biomarkers, including proteinuria-based tests, DNA methylation biomarkers, and RNA-based molecular panels, has been conducted. Various molecular tests, such as Cxbladder®, Bladder EpiCheck®, and UroSEEK, are highly sensitive and clinically valid. Urinary biomarkers provide a promising noninvasive alternative for traditional BCa diagnostics with enhanced specificity and the possibility of early diagnosis. Future research should focus on large-scale clinical validation and standardization of biomarkers to facilitate their use in routine clinical practice.

Automated peritoneal dialysis (APD) consists of dwells with the same dwell volume and time. New cyclers allow modification of time and volume to prescribe adapted APD (AAPD), i.e., a series of short, small dwells followed by long, large dwells. Safety, efficacy, and underlying mechanisms of AAPD in children are uncertain. Two double mini-PET were performed in randomized sequence. The standard test consisted of two identical cycles (fill volume 1000 ml/m2, 75 min) and the adapted test of a short, small cycle (600 ml/m2 BSA, 30 min) followed by a long, large cycle (1400 ml/m2, 120 min). Solute and water fluxes were quantified together with intraperitoneal pressure (IPP). Nine pediatric PD patients (5–21 years) were treated per protocol. Residual dialysate volume was 422 ± 190 ml/m2 BSA. There were no differences in ultrafiltration rates, glucose uptake, and creatinine, urea, and electrolyte clearances with the adapted and standard double mini-PET, despite identical cumulative dialysate volume and time. IPP varied by 1.7 ± 3.4 (range −2 to 9) cm H2O with a drained volume of 1123 ± 386 and 1159 ± 210 ml/m2 BSA for each standard dwell. IPP decreased from 1.9 with small volume to 1.0 cm H2O /m2/100 ml with large volume dwells (p < 0.001) and was above 14 cm H2O in 21 out of 63 measurements. Within the limitation of small patient numbers, this proof-of-concept study suggests similar ultrafiltration and clearance rates with a single adapted versus standard double mini-PET. High residual dialysate volumes and high IPPs highlight the challenges of AAPD prescription in children.

Acute kidney injury (AKI) is a common clinical complication of cardiac surgeries. Although urinary particle analysis is useful for differentiating AKI, its value in AKI diagnosis has not yet been well described. We sought to determine the contribution of urinary particle analysis to the diagnosis of AKI. Two-hundred and thirty-nine adult patients were prospectively included after cardiac surgery. The diagnostic performance of urinary particle analysis at different time points after intensive care unit (ICU) admission was evaluated. AKI was diagnosed and classified according to the KDIGO definitions. Urinary particles, including renal tubular epithelial cells (RTEC) and non-hyaline casts, Nephrocheck®, urinary alpha-1-microglobulin and urinary γ-glutamyltransferase (GGT) levels were measured at 4, 12 and 24 h after ICU admission and evaluated against different endpoints. Of the 239 patients included, 39 (16.3

DOI original paper: 10.1515/cclm-2024-0070 Background The EFLM Task and Finish Group Urinalysis has updated the ECLM European Urinalysis Guidelines (2000) on urinalysis and urine bacterial culture, to improve accuracy of these examinations in European clinical laboratories, and to support diagnostic industry to develop new technologies. Recommendations Graded recommendations were built in the following areas: Medical needs and test requisition Strategies of urine testing are described to patients with complicated or uncomplicated urinary tract infection (UTI), and high or low-risk to kidney disease. Specimen collection Patient preparation, and urine collection are supported with two quality indicators: contamination rate (cultures), and density of urine (chemistry, particles). Chemistry Measurements of both urine albumin and α1-microglobulin are recommended for sensitive detection of kidney disease in high-risk patients. Performance specifications are given for urine protein measurements and quality control of multiproperty strip tests. Particles Procedures for microscopy are reviewed for diagnostic urine particles, including urine bacteria. Technologies in automated particle counting and visual microscopy are updated with advice how to verify new instruments with the reference microscopy. Bacteriology Chromogenic agar is recommended as primary medium in urine cultures. Limits of significant growth are reviewed, with an optimised workflow for routine specimens, using leukocyturia to reduce less important antimicrobial susceptibility testing. Automation in bacteriology is encouraged to shorten turn-around times. Matrix assisted laser desorption ionization time-of-flight mass spectrometry is applicable for rapid identification of uropathogens. Aerococcus urinae, A. sanguinicola and Actinotignum schaalii are taken into the list of uropathogens. A reference examination procedure was developed for urine bacterial cultures.

OBJECTIVES:We evaluated the performance of a novel flow cell morphology analyzer AUTION EYE AI-4510 for counting particles in urine. METHODS:Analytical performance was assessed according to the EFLM European Urinalysis Guideline 2023. Trueness was compared by analyzing 1.012 fresh urine samples with the AUTION EYE AI-4510 (ARKRAY, Inc., Kyoto, Japan) against phase-contrast visual microscopy. Poisson statistics were utilized in assessment of imprecision of particle counts both with quality control material and patient specimens. RESULTS:Relative imprecision against theoretical Poisson imprecision, R(CV), was estimated to be 1.1 for red blood cells (RBC), 1.0 for white blood cells (WBC), 0.9 for squamous epithelial cells (SEC) and 1.1 for bacteria. The agreement with visual microscopy (Cohen's weighted kappa) was 0.93 for RBC, 0.95 for WBC, 0.90 for SEC, 0.79 for non-squamous epithelial cells (NSEC), 0.67 for combined casts, 0.90 for crystals and 0.88 for bacteria. No clinically significant bias was observed. Limits of quantitation at CV=30 % reached 4 × 106/L for RBC and 5 × 106/L for WBC. Differentiation of urinary crystals was improved as compared to previous data on digital cuvette imaging. CONCLUSIONS:The ARKRAY AUTION EYE AI-4510 provided a desirable imprecision, met the criteria for linearity, LoQ and carry-over, and showed an optimum comparison to visual microscopy for RBC, WBC, SEC and crystals as defined in the EFLM European Urinalysis Guideline 2023. The identification of kidney damage is recommended to be improved by using user-defined review rules. Performance of bacteria counting needs to be confirmed against urine bacterial cultures.

The early detection of gynecological cancers, which is critical for improving patient survival rates, is challenging because of the vague early symptoms and the diagnostic limitations of current approaches. This comprehensive review delves into the game-changing potential of infrared (IR) spectroscopy, a noninvasive technology used to transform the landscape of cancer diagnosis in gynecology. By collecting the distinctive vibrational frequencies of chemical bonds inside tissue samples, Fourier-transform infrared (FTIR) spectroscopy provides a ‘molecular fingerprint’ that outperforms existing diagnostic approaches. We highlight significant advances in this field, particularly the identification of discrete biomarker bands in the mid- and near-IR spectra. Proteins, lipids, carbohydrates, and nucleic acids exhibited different absorption patterns. These spectral signatures not only serve to distinguish between malignant and benign diseases, but also provide additional information regarding the cellular changes associated with cancer. To underscore the practical consequences of these findings, we examined studies in which IR spectroscopy demonstrated exceptional diagnostic accuracy. This review supports the use of IR spectroscopy in normal clinical practice, emphasizing its capacity to detect and comprehend the intricate molecular underpinnings of gynecological cancers.

BACKGROUND:We aimed to investigate the clinical, imaging and fluid biomarker characteristics in patients with antidiacylglycerol lipase alpha (DAGLA)-autoantibody-associated cerebellitis. METHODS:Serum and cerebrospinal fliud (CSF) samples from four index patients were subjected to comprehensive autoantibody screening by indirect immunofluorescence assay (IIFA). Immunoprecipitation, mass spectrometry and recombinant protein assays were used to identify the autoantigen. Sera from 101 patients with various neurological symptoms and a similar tissue staining pattern as the index patient samples, and 102 healthy donors were analysed in recombinant cell-based IIFA (RC-IIFA) with the identified protein. Epitope characterisation of all positive samples was performed via ELISA, immunoblot, immunoprecipitation and RC-IIFA using different DAGLA fragments. RESULTS:All index patients were relatively young (age: 18-34) and suffered from pronounced gait ataxia, dysarthria and visual impairments. Paraclinical hallmarks in early-stage disease were inflammatory CSF changes and cerebellar cortex hyperintensity in MRI. Severe cerebellar atrophy developed in three of four patients within 6 months. All patient samples showed the same unclassified IgG reactivity with the cerebellar molecular layer. DAGLA was identified as the target antigen and confirmed by competitive inhibition experiments and DAGLA-specific RC-IIFA. In RC-IIFA, serum reactivity against DAGLA was also found in 17/101 disease controls, including patients with different clinical phenotypes than the one of the index patients, and in 1/102 healthy donors. Epitope characterisation revealed that 17/18 anti-DAGLA-positive control sera reacted with a C-terminal intracellular DAGLA 583-1042 fragment, while the CSF samples of the index patients targeted a conformational epitope between amino acid 1 and 157. CONCLUSIONS:We propose that anti-DAGLA autoantibodies detected in CSF, with a characteristic tissue IIFA pattern, represent novel biomarkers for rapidly progressive cerebellitis.