Urinary Sediment Research Articles

Peficitinib Halts Acute Kidney Injury Via JAK/STAT3 and Growth Factors Immunomodulation

Acute Kidney Injury (AKI) is characterized by a sudden loss of kidney function and its management continues to be a challenge. In this study the effect of peficitinib, a Janus kinase inhibitor (JAKi), was studied in an aim to stop the progression of AKI at an early point of injury. Adult male mice were injected with aristolochic acid (AA) a single dose (10 mg/kg, i.p) to induce AKI. Peficitinib was injected in one of the two tested doses (5 or 10 mg/kg, i.p) one hour after AA injection and was continued daily for seven days. Histopathological evaluation showed that peficitinib alleviated necrosis and hyaline cast formation induced by aristolochic acid. It decreased serum creatinine and the kidney injury molecule-1 (KIM-1) elevated by AA. Peficitinib also mitigated AA induced oxidative stress through regulating total antioxidant capacity (TAC) and reduced glutathione (GSH) level in renal tissue. Additionally, renal sections isolated from groups that received peficitinib revealed a decrease in vascular endothelial growth factor receptor 1 interstitial expression and transforming growth factor-beta 1 (TGF-β1) renal level. Peficitinib received groups showed a decrease in the active phosphorylated form of signal transducers and activators of transcription (STAT3). Moreover, peficitinib decreased renal protein levels and gene expression of the pro-inflammatory cytokines; interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α) and interferon gamma (IFN-γ). These findings suggest that peficitinib is helpful in halting AKI progression into chronic kidney disease through modulating JAK/STAT3 dependent inflammatory pathways and growth factors involved in normal glomerular function.

Urine Sediment Detection Algorithm Based on Channel Enhancement and Deformable Convolution.

Urine sediment detection is a vital method in clinical urine analysis for evaluating an individual's kidney and urinary system health, as well as identifying potential diseases. Nevertheless, urine sediment images exhibit the characteristic of diverse shapes for the same category of targets. These characteristics pose a considerable challenge to the accurate identification of the visible components within the images. We approach urine sediment detection as an object detection task and have introduced the specialized YOLOv7-CSD algorithm for this purpose. In particular, we have integrated channel enhancement feature pyramid network (CE-FPN) and selective kernel (SK) into the YOLOv7 model to address the issue of model confusion in classifying and identifying tasks caused by the feature aliasing effects of feature pyramid network (FPN). Furthermore, we enhance the efficient layer aggregation networks (ELAN) network by adding a second channel, enabling the model to acquire a more extensive set of feature information. On top of this, we introduce the deformable convolutional v3 (DCNv3) operator, allowing the model to dynamically adjust its receptive field, addressing the issue of variable shapes. Tested on the USE dataset and a dataset for urine crystals, YOLOv7-CSD achieves accuracies of 92.8 and 89.6 , respectively.

Urinary sediment mRNA as a potent biomarker of IgA nephropathy

BackgroundThe quantification of mRNA expression in urinary sediments is a reliable biomarker for various diseases. However, few studies have investigated the clinical relevance of urinary mRNA levels in IgA nephropathy (IgAN). Thus, we investigated the expression of urinary mRNAs and their clinical significance in IgAN.MethodsOverall, 200 patients with biopsy-proven IgAN, 48 disease controls, and 76 healthy controls were enrolled. We identified the differential expression of mRNAs in renal tissue between patients with IgAN and normal subjects using the Gene Expression Omnibus dataset and selected candidate mRNAs. mRNA expression in the urinary sediment was measured using quantitative real-time polymerase chain reaction. Associations between urinary mRNA levels and clinicopathological parameters were analyzed and the predictive value of mRNAs for disease progression was evaluated.ResultsThe urinary expression of CCL2, CD14, DNMT1, FKBP5, Nephrin, and IL-6 was significantly upregulated in patients with IgAN compared with healthy controls. C3, FLOT1, and Podocin levels were significantly correlated with renal function, where C3, FLOT1, and TfR levels were significantly correlated with urinary protein excretion. During follow-up, 26 (13.0%) patients with IgAN experienced disease progression, defined as a greater than 50% reduction in the estimated glomerular filtration rate or progression to end-stage renal disease. Urinary mRNA levels of FLOT1 (HR 3.706, 95% CI 1.373–10.005, P = 0.010) were independently associated with an increased risk of disease progression.ConclusionsOur results suggest that urinary sediment mRNAs are a useful biomarker in IgAN patients. Further studies with larger sample sizes and longer follow-up durations are required.

Development of an automated artificial intelligence-based system for urogenital schistosomiasis diagnosis using digital image analysis techniques and a robotized microscope.

Urogenital schistosomiasis is considered a Neglected Tropical Disease (NTD) by the World Health Organization (WHO). It is estimated to affect 150 million people worldwide, with a high relevance in resource-poor settings of the African continent. The gold-standard diagnosis is still direct observation of Schistosoma haematobium eggs in urine samples by optical microscopy. Novel diagnostic techniques based on digital image analysis by Artificial Intelligence (AI) tools are a suitable alternative for schistosomiasis diagnosis. Digital images of 24 urine sediment samples were acquired in non-endemic settings. S. haematobium eggs were manually labeled in digital images by laboratory professionals and used for training YOLOv5 and YOLOv8 models, which would achieve automatic detection and localization of the eggs. Urine sediment images were also employed to perform binary classification of images to detect erythrocytes/leukocytes with the MobileNetv3Large, EfficientNetv2, and NasNetLarge models. A robotized microscope system was employed to automatically move the slide through the X-Y axis and to auto-focus the sample. A total number of 1189 labels were annotated in 1017 digital images from urine sediment samples. YOLOv5x training demonstrated a 99.3% precision, 99.4% recall, 99.3% F-score, and 99.4% mAP0.5 for S. haematobium detection. NasNetLarge has an 85.6% accuracy for erythrocyte/leukocyte detection with the test dataset. Convolutional neural network training and comparison demonstrated that YOLOv5x for the detection of eggs and NasNetLarge for the binary image classification to detect erythrocytes/leukocytes were the best options for our digital image database. The development of low-cost novel diagnostic techniques based on the detection and identification of S. haematobium eggs in urine by AI tools would be a suitable alternative to conventional microscopy in non-endemic settings. This technical proof-of-principle study allows laying the basis for improving the system, and optimizing its implementation in the laboratories.

Single cell profiling of tubular epithelial cells under adaptive state in urine sediment from early and advanced diabetic kidney disease patients

IntroductionTubular epithelial cells under adaptive state (aTEC) have been frequently reported in the injured kidney closely associated with disease progression. However, whether aTEC is present in the urine of Diabetic Kidney Disease (DKD) patients and its clinical implication have not been assessed. MethodsUrine samples from early and advanced DKD patients were collected and subjected to single cell RNA sequencing (scRNA-seq). Kidney single nucleus RNA-seq, spatial scRNA-seq and bulk RNA-seq datasets were employed to reconstruct their local environment and to delineate differences between shed cells and local residence. ResultsMost urinary TEC in DKD patients are under adaptive states. While the composition of urinary TEC is consistent in early and advanced DKD, higher ratio of aTEC under progenitor and fibrosis state is defined in early DKD. Trajectory inference reveals some aTEC are early derivatives of injured PT. Spatial mapping reveals proliferative and fibrosis aTEC reside close to glomerulus region. Systemic evaluation of different states of urinary aTEC in patients of diverse-cause kidney injury suggests that the ratio of progenitor/proliferative aTEC and fibrosis aTEC is of diagnostic value. ConclusionUrine is an underestimated source of aTEC providing us non-invasive manner to interrogate the injured state of tubule. The ratio of fibrosis aTEC and progenitor/proliferative aTEC in urine features tubular injury state and may help improve DKD diagnosis.

Dq-YOLOF: An Effective Improvement with Deformable Convolution and Sample Quality Optimization Based on the YOLOF Detector

Single-stage detectors have drawbacks of insufficient accuracy and poor coverage capability. YOLOF (You Only Look One-level Feature) has achieved better performance in this regard, but there is still room for improvement. To enhance the coverage capability for objects of different scales, we propose an improved single-stage object detector: Dq-YOLOF. We have designed an output encoder that employs a series of modules utilizing deformable convolution and SimAM (Simple Attention Module). This module replaces the dilated convolution in YOLOF. This design significantly improves the ability to express details. Simultaneously, we have redefined the sample selection strategy, which optimizes the quality of positive samples based on SimOTA. It can dynamically allocate positive samples according to their quality, reducing computational load and making it more suitable for small objects. Experiments conducted on the COCO 2017 dataset also verify the effectiveness of our method. Dq-YOLOF achieved 38.7 AP, 1.5 AP higher than YOLOF. To confirm performance improvements on small objects, our method was tested on urinary sediment and aerial drone datasets for generalization. Notably, it enhances performance while also lowering computational costs.

The Usefulness of Lordosis Load Test and Urinary Biochemistry in the Diagnosis of Orthostatic Proteinuria.

Introduction Renal disease is commonly suspected in patients with proteinuria. Renal biopsy might be considered based on the patient's clinical history and the results of diagnostic tests. However, as orthostatic proteinuria is benign and requires no treatment, it is important to obtain a diagnosis without renal biopsy whenever possible. Therefore, up to now, for the diagnosis of orthostatic proteinuria, in addition to resting urinalysis evaluation (disappearance of proteinuria), we have performed the lordosis load test and urine biochemistry of the samples showing peak proteinuria in a lordosis load test. Method We retrospectively enrolled all patients who visited the pediatric department and underwent the lordosis load test at Kanazawa Medical Center between 2011 and 2020. In the present study, samples with the highest concentrations of protein after the lordosis load test were subjected to general urinary biochemistry and urinary sediment analysis. Patients were followed up with the lordosis load test for several years. Results Enrolled in the study were 68 patients with OP. The mean age at the time of diagnosis was 11.5 years (range, six to 16 years). General urinary tests, urinary sediment, and urinary biochemistry including N-acetyl-beta-D-glucosaminidase (NAG), alpha1-microglobulin(α1MG), and beta 2-microglobulin (β2MG) were normal in all patients with orthostatic proteinuria except one case who was a premature baby. Conclusion If proteinuria disappears after two hours of rest, and urinary biochemistry of the samples showing peak proteinuria in the lordosis load test is normal, orthostatic proteinuria can be diagnosed more accurately.

The Clinical Impact of Urinalysis Screened by Automated Microscopy Compared to Reference Manual Analysis.

Clinical laboratories have replaced conventional manual urine microscopy with automated urinalysis; however, concerns persist regarding its validity in detecting specific elements of urinary sediment crucial for evaluating kidney diseases. This study aimed to assess the accuracy of urinary sediment analysis performed by a large hospital laboratory compared to a standardized microscopic review, focusing on patients both with and without kidney disease. Urine samples were randomly selected from routine laboratory specimens at a university hospital. Laboratory analysis was performed using LabUmat 2 and Urised 3 PRO equipment (Abbott Diagnostics). In the automated analysis, technicians had the option to reclassify urinary sediment elements and, if needed, conduct manual microscopic evaluations to validate findings. The laboratory's analysis was compared with a "reference" analysis, which was double-blinded and conducted by two experienced technicians using bright-field and phase-contrast microscopy. 503 samples were selected, with 52.3% originating from nephrology outpatient clinic patients. Overall agreement between the laboratory results and the reference analysis was 42.1%. The sensitivity (SN) of the laboratory examination for detecting pathological casts, lipiduria, and renal tubular cells was low (<50%), while specificity (SP) was high (>98%). However, for hyaline casts (SN: 50.4%; SP: 80.9%) and dysmorphic red blood cells (SN: 62.3%; SP: 96.2%), accuracy was intermediate. Performance was better for hematuria (SN: 86.1%; SP: 82.3%; ICC: 0.703; R: 0.828) and leukocyturia (SN: 84.9%; SP: 95.1%; ICC: 0.807; R: 0.861). In patients with kidney disease (N=248) and in samples manually reviewed by the laboratory (N=115), accuracy for each urinary element was comparable to the overall sample findings. However, when assessing the ability to identify elements suggestive of nephropathy, only samples manually reviewed by the laboratory showed statistically similar results to those obtained by the reference analysis (p= 0.503, McNemar's test). Employing automated urinalysis seems to be accurate for detecting hematuria and leukocyturia, as well as for screening patients without kidney diseases. However, clinical laboratories attending complex patients should employ personalized strategies to help decide when to perform manual review, thus avoiding misleading urinalysis results.

Human Schistosomiasis due to Schistosoma bovis in Nigeria.

Schistosomiasis is a global public health challenge, especially in sub-Saharan Africa, where Nigeria has the highest burden of disease. Schistosoma hybrids have been discovered in various countries, including Nigeria, where livestock and human beings share common water resources. This study, carried out in three communities, two of which are endemic for urinary schistosomiasis, aimed to identify the urinary schistosomiasis causative agent by using a species-specific molecular technique and their evolutionary relationship. Polymerase chain reaction using primers specific for a partial DNA sequence of the mitochondrial cox1 gene of Schistosoma haematobium was carried out on pooled urine sediments preserved in 70% ethanol. DNA from the high-intensity pooled samples from Onye-Uku camp amplified, and a BLAST search identified the pooled samples as Schistosoma bovis, whereas S. haematobium DNA did not amplify. The phylogenetic relationship of the sequence showed that it clustered with an S. bovis hybrid obtained from a human host in Côte d'Ivoire and had close ancestry with isolates from cattle in Cameroon. This finding revealed the prevalence of S. bovis among some inhabitants in a zone in Nigeria where schistosomiasis is endemic.

GENERAL CLINICAL AND CYTOLOGICAL METHODS FOR STUDYING THE URINARY SYSTEM ORGANS

The lecture covers general clinical and cytological methods for urine analysis, specifically the determination of its physical properties, chemical analysis for the presence of protein, glucose, ketone bodies, and pigments, which allow for the assessment of kidney function, urinary system condition, and metabolic disorders. It also includes microscopic analysis of sediment to identify cellular elements, casts, and salts, aiding in the diagnosis of infectious and inflammatory processes in the kidneys and urinary system. Methods for qualitative and quantitative examination of urine sediment are discussed for diagnosing renal function disturbances, urinary system issues, as well as metabolic and systemic diseases. The lecture emphasizes the importance of these studies in clinical practice for detecting various pathological conditions and monitoring patient treatment.

Deconvolution of Human Urine across the Transcriptome and Metabolome.

Early detection of the cell type changes underlying several genitourinary tract diseases largely remains an unmet clinical need, where existing assays, if available, lack the cellular resolution afforded by an invasive biopsy. While messenger RNA in urine could reflect the dynamic signal that facilitates early detection, current measurements primarily detect single genes and thus do not reflect the entire transcriptome and the underlying contributions of cell type-specific RNA. We isolated and sequenced the cell-free RNA (cfRNA) and sediment RNA from human urine samples (n = 6 healthy controls and n = 12 kidney stone patients) and measured the urine metabolome. We analyzed the resulting urine transcriptomes by deconvolving the noninvasively measurable cell type contributions and comparing to plasma cfRNA and the measured urine metabolome. Urine transcriptome cell type deconvolution primarily yielded relative fractional contributions from genitourinary tract cell types in addition to cell types from high-turnover solid tissues beyond the genitourinary tract. Comparison to plasma cfRNA yielded enrichment of metabolic pathways and a distinct cell type spectrum. Integration of urine transcriptomic and metabolomic measurements yielded enrichment for metabolic pathways involved in amino acid metabolism and overlapped with metabolic subsystems associated with proximal tubule function. Noninvasive whole transcriptome measurements of human urine cfRNA and sediment RNA reflects signal from hard-to-biopsy tissues exhibiting low representation in blood plasma cfRNA liquid biopsy at cell type resolution and are enriched in signal from metabolic pathways measurable in the urine metabolome.

Screening for Peripheral Vascular Disease: The Role of Ankle-Brachial Index (ABI) and Estimated Glomerular Filtration Rate (eGFR) Changes in Chronic Kidney Disease.

Background Chronic kidney disease (CKD) is a significant public health issue worldwide, closely linked with cardiovascular events such as atherosclerosis, peripheral arterial disease (PAD), stroke, coronary artery disease (CAD), and heart failure. The ankle-brachial index (ABI) is a simple tool that compares blood pressure in the ankle and arm, helping to detect PAD and assess the risk of cardiovascular events. An increased ABI signifies an increased risk of cardiovascular disease (CVD), whereas a diminished ABI correlates with angiographically verified atherosclerosis along with heightened death rates. Recent research indicates a U-shaped relationship between ABI and mortality, underscoring the necessity for early detection and action to mitigate potential consequences. Aim This study aimed to correlate ABI changes with estimated glomerular filtration rate (eGFR) changes in CKD patients to screen for the development of peripheral vascular disease. Materials and methods This prospective cross-sectional study was conducted in the outpatient department of a tertiary care hospital in India, focusing on patients diagnosed with CKD admitted to the general medicine department. The inclusion criteria were CKD patients with an eGFR less than 60 ml/min/1.73 m², accompanied by indicators of renal damage such as albuminuria, reduced kidney size on ultrasound, abnormal urinary sediment, or biopsy-proven kidney disease. Patients with peripheral vascular disease, with end-stage renal disease (on dialysis), with limb amputations, with hemodynamic instability, or who declined participation were excluded. eGFR was calculated using the Modification of Diet in Renal Disease (MDRD) equation, and the ABI was measured at baseline, three months, and six months. ABI values below 0.9 indicated peripheral vascular disease, and the study aimed to correlate changes in ABI with eGFR to assess vascular disease development in non-dialyzed CKD patients. Results By the end of the third month, a positive correlation was observed between ABI and eGFR (r=0.259), which persisted at the end of the sixth month (r=0.245). Conclusion The study concludes that a direct relationship exists between decreasing eGFR and ABI, which increases susceptibility to PAD and CVD. A low ABI is linked to an accelerated decline in eGFR, indicating that systemic atherosclerosis predicts kidney function deterioration.

An updated approach to the evaluation of the urinary sediment.

Examination of the urinary sediment (U-sed) is an important non-invasive, rapid, and inexpensive tool for the diagnosis and surveillance over time of renal diseases. In this Educational Review, we describe first how to collect, prepare, and examine urine samples in order to obtain reliable results. Then, we describe the U-sed findings in isolated microscopic hematuria, glomerular diseases, acute interstitial nephritis, acute kidney injury, reactivation of the BK virus in kidney transplant recipients, and crystalluric genetic diseases.

Relation between Urine Cytological Findings and Renal Function in Patients with Kidney Stones in Taif, Saudi Arabia

Background and Objectives: Urine serves as a vital diagnostic fluid, and urine cytology analysis plays a crucial role in identifying urinary system illnesses such as bladder cancer and kidney stones. The Paris System for Reporting Urinary Cytology establishes a uniform method for diagnosing urinary tract cancer. This study aimed to provide valuable insights that can inform diagnostic strategies related to kidney stones and ultimately improve patient outcomes via the early detection of the cellular changes associated with kidney stones and their relation to kidney function tests. Materials and Methods: A comparative study was conducted and comprised two groups: group 1, consisting of 50 patients diagnosed with kidney stones, and group 2, comprising 50 patients diagnosed with other kidney diseases. Renal function tests and urinalysis (via the PAP staining of urine cellular deposits to detect nuclear changes) were performed, and the results were analyzed. Results: There was a statistically significant increase in urinary red blood cells, white blood cells, and nuclear reactive atypical changes in urinary sediments of kidney stone patients compared to the patients without stones, while there was a decrease in the estimated glomerular filtration rate (eGFR). eGFR showed a 96.7% specificity in detecting cases with nuclear reactive atypia. Conclusions: eGFR emerges as a reliable diagnostic marker for the comprehensive assessment of kidney stones, particularly when associated with nuclear atypia. The significant correlation between the indicators of chronic kidney disease, such as decreased eGFR, and the presence of kidney stones emphasizes the urgent need for efficient diagnostic practices.

Does the standard proteinuria cut-off for renal biopsy in lupus nephritis as per the current guidelines hold good for Asian population? A single-centre study from South India.

Current rheumatology and nephrology society guidelines in lupus nephritis do not recommend renal biopsy for proteinuria of less than 500mg/24h. This might lead to a significant delay in the early diagnosis of lupus nephritis. The main aim of this study is to determine the nature of renal lesions in patients with low-grade proteinuria and to analyze the predictors for clinically significant lupus nephritis. This was a single-center, retrospective study. All consecutive patients of lupus nephritis, with low-grade proteinuria (200mg to 500mg/24h) undergoing renal biopsy were enrolled in this study. The renal biopsies were classified into significant lesions (Class III/IV/V) and non-significant lesions (Class I and II). Treatment naïve groups and treatment-modified groups were analyzed separately. Predictive factors for significant renal lesions were determined by univariate and multivariate analysis. We identified 183 patients of lupus with proteinuria between 200 and 500mg / 24h. Mean (SD) age was 30.2 (11.39) years with 167 (91.2%) of them being females. The mean (SD) baseline proteinuria was 351.03 (98.1) mg/24h 85 patients (46.5%) had proliferative lupus nephritis where whereas 17 patients (9.3%) had membranous nephropathy. Crescents and fibrinoid necrosis were seen in 10 (5.46%) and 24 (13.11 %) patients respectively. Isolated proteinuria without any other sediments was seen in 95 patients (51.9%) of which 29 patients had proliferative lupus nephritis. Elevated Anti-double stranded DNA (anti-dsDNA), low C3, low C4 and the presence of urinary sediments were significantly associated with significant renal lesions in biopsy. Significant renal lesions were seen in around half of the patients with low-grade proteinuria underscoring the importance of performing a renal biopsy in this set of patients. Low C3 and C4, urinary sediments, and elevated anti-dsDNA were predictors for significant renal lesions.

Getting the most from urine and sediment analysis

Urine sediment examination is an integral part of urinalysis which is frequently overlooked as it can be time consuming and requires a functional microscope, a centrifuge and staff with both the time and expertise to perform the exam. Sediment examination allows the operator to identify crystals, casts, cells and bacteria in a urine sample. Failure to perform sediment examination promptly can lead to ageing artefacts which may negatively affect case management. Examination of the urine sediment should ideally be performed within 1–2 hours of urine collection.

B-118 Comparison of Statistical Methods, Chauvenet Test, and Interquartile Deviation for Urinary Sediment Inter Microscopists Evaluation

Abstract Background Comparison among microscopists is a quality process aimed at achieving comparability of analyses among collaborators who perform microscopy or manual analysis examinations, as in the case of urinary sediment examination. The current laboratory process evaluates red blood cell and white blood cell counts among microscopists within the same unit, aiming to identify discrepant counts through the application of statistical tools, with Chauvenet Statistics and Interquartile Deviation (IQD) being the most common in the literature. The purpose was to systematically compare Chauvenet Statistics and IQD as evaluation criteria for the comparison among microscopists for urinary sediment examination in our laboratories. Methods A total of 45 laboratory units within a total of 684 participants were analyzed throughout 2023. The results reported by microscopists from the same unit were evaluated using Chauvenet Statistics and IQD, calculating the adequacy rate for each type of assessment. Results Adopting IQD as the evaluation criterion, adequacy rates of 94.20% for red blood cell counts and 93.73% for white blood cell counts were observed. Using Chauvenet Statistics, the adequacy rates were 96.20% for red blood cells and 95.65% for white blood cells. This difference stems from 233 results identified as inadequate by the IQD method but deemed adequate by Chauvenet Statistics. In these cases, the results did not exhibit a normal distribution, approaching an expected distribution for categorical (discrete) variables. Additionally, 35 results identified as inadequate by Chauvenet Statistics were evaluated as adequate by the IQD method. These occurrences were observed when the reported results approached a normal distribution. Conclusions Regarding Chauvenet Statistics, IQD is a more efficient statistical tool for use as an evaluation criterion in the comparison among microscopists who perform red and white blood cell counts for urinary sediment examination in the selected laboratory units. However, the present study illustrated that each of the statistical tools will be more efficient in identifying outliers depending on the dataset analyzed. Therefore, it is important to consider the laboratory's epidemiology and population to decide which statistical tool is most suitable for each scenario.

B-006 Use of Sysmex UN-3000 Research Parameters for Semiquantitative Analysis of Urine Microscopic Elements

Abstract Background Microscopic examination of urine is an important component of urine analysis. However, it is labor-intensive and requires a skilled microscopist. The Sysmex UN-3000 (Kobe, JP) combines a Siemens CLINITEK Novus (Munich, GER) with a Sysmex UF-5000 flow cytometer and Sysmex UD-10 digital imaging device for fully automated urine analysis. It is FDA-approved for quantitation of red and white blood cells, epithelial cells, casts, and bacteria. It also flags for other particles such as sperm, yeast, pathologic casts, and crystals, which can then be confirmed on the UD-10. We sought to determine if and how the UF-5000 research parameter results could be used for semi-quantitative grading of pathologic casts, squamous epithelial cells, non-squamous epithelial cells, and crystals to match our reporting system. Methods Urine samples were analyzed by the UN-3000 and by manual review of urine sediment per laboratory protocols. Epithelial cells and crystals grades were none seen, few, moderate, many. Cast grades were 0, 1-3, 4-10, and >10. Results of manual microscopy were used to determine numerical cutoffs for the UF-5000 results which would agree within one grade in ≥90% of samples. Sperm and yeast are reported as either present or absent. For these particles, manual microscopy was compared to the results of the UF-5000 flagging and subsequent review of the UD-10 images. Results Rate of agreement between the methods is shown in the table. For sperm the UN-3000 showed 91.7% sensitivity and 100% specificity; for yeast, 93.8% sensitivity and 97.7% specificity. Conclusions We were able to use the research parameters from the UF-5000, in conjunction with the UD-10, to perform semi-quantitative grading. Adoption of this analyzer increases automation, with 70% of samples auto-validating per our protocols, while still conforming to our previous reporting system.

Are Waxy Casts in the Urinary Sediment Associated with Advanced Kidney Disease?

Are Waxy Casts in the Urinary Sediment Associated with Advanced Kidney Disease?

Novel High-Resolution Three-Dimensional Fluorescent Confocal Imaging Resolves Differences in Urinary Sediment

Novel High-Resolution Three-Dimensional Fluorescent Confocal Imaging Resolves Differences in Urinary Sediment