ReviewAnnals of laboratory medicine2019
Progress in Automated Urinalysis.
Review in Annals of laboratory medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
54 citing papers in PubMed, 145 citations in OpenAlex.
- Deep Learning-Assisted Classification of Urinary Red Blood Cell Morphology for Glomerular Hematuria Screening: A Pilot Study.Journal of clinical laboratory analysis · 2026Article
- Urinary Red Blood Cell Distribution for Detection of Glomerular Hematuria: A Biopsy-Based Comparison with Direct Microscopy.Diagnostics (Basel, Switzerland) · 2026Article
- Unveiling potential natural promoters of calcium oxalate kidney stones in the urine via anion-exchange chromatography, crystal assays, and proteomics.Molecular and cellular biochemistry · 2026Article
- Feasibility of Flow Cytometric Bacterial Count in Synovial Fluid to Detect Periprosthetic Joint Infection in Hip and Knee Arthroplasty.Journal of clinical medicine · 2026Article
- Clinical application of MALDI-TOF MS for direct and rapid pathogen identification: a comprehensive review focusing on bloodstream infections and sterile body fluids.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Review
- Multivariable Urine Flow Cytometry-Based Screening for Prediction of Urine Culture Positivity.Diagnostics (Basel, Switzerland) · 2026Article
- Comparative evaluation of three automated urine sediment analyzers excluding cutoff-related trade-offs.iScience · 2026Article
- Characterizing Urine and Sediment in Individuals with Lower Urinary Tract Dysfunction Utilizing Intermittent Catheters.Journal of clinical medicine · 2025Article
- Article
- Evaluation of urine albumin-to-creatinine ratio analysis using strip test as a screening method for urinary albumin determination in primary care.Advances in laboratory medicine · 2025Article
- Performance verification of the new UF-1500 urine particle analyser: a new opportunity for small and medium laboratories.Practical laboratory medicine · 2025Article
- Renal Tubular Epithelial Cells as Marker of Tubular Damage in Acute Kidney Disease.Kidney international reports · 2025Article
- Artificial Neural Network for the Fast Screening of Samples from Suspected Urinary Tract Infections.Antibiotics (Basel, Switzerland) · 2025Article
- Renal tubular epithelial cells as an easily accessible biomarker for diagnosing AKI post cardiac surgery.Intensive care medicine · 2025Article
- Quality indicators for urine sample contamination: can squamous epithelial cells and bacteria count be used to identify properly collected samples?Clinical chemistry and laboratory medicine · 2025Observational
- Artificial Intelligence in Diagnostics: Enhancing Urine Test Accuracy Using a Mobile Phone-Based Reading System.Annals of laboratory medicine · 2025Article
- A Spectroscopic Methodology to Early Detection of Urinary Tract Infections.Sensors (Basel, Switzerland) · 2025Article
- The Effects of Diet, Dietary Supplements, Drugs and Exercise on Physical, Diagnostic Values of Urine Characteristics.Nutrients · 2024Review
- Laboratory Tests, Bacterial Resistance, and Treatment Options in Adult Patients Hospitalized with a Suspected Urinary Tract Infection.Diagnostics (Basel, Switzerland) · 2024Review
- Comparison of Labsan Tricell-1000 and Dirui FUS-2000 automated urine analyzers with manual microscopy.Practical laboratory medicine · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
New technological advances have paved the way for significant progress in automated urinalysis. Quantitative reading of urinary test strips using reflectometry has become possible, while complementary metal oxide semiconductor (CMOS) technology has enhanced analytical sensitivity and shown promise in microalbuminuria testing. Microscopy-based urine particle analysis has greatly progressed over the past decades, enabling high throughput in clinical laboratories. Urinary flow cytometry is an alternative for automated microscopy, and more thorough analysis of flow cytometric data has enabled rapid differentiation of urinary microorganisms. Integration of dilution parameters (e.g., creatinine, specific gravity, and conductivity) in urine test strip readers and urine particle flow cytometers enables correction for urinary dilution, which improves result interpretation. Automated urinalysis can be used for urinary tract screening and for diagnosing and monitoring a broad variety of nephrological and urological conditions; newer applications show promising results for early detection of urothelial cancer. Concomitantly, the introduction of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) has enabled fast identification of urinary pathogens. Automation and workflow simplification have led to mechanical integration of test strip readers and particle analysis in urinalysis. As the information obtained by urinalysis is complex, the introduction of expert systems may further reduce analytical errors and improve the quality of sediment and test strip analysis. With the introduction of laboratory-on-a-chip approaches and the use of microfluidics, new affordable applications for quantitative urinalysis and readout on cell phones may become available. In this review, we present the main recent developments in automated urinalysis and future perspectives.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.