ArticleScientific reports2025
Continuous spectroscopic monitoring of urinary catheter output: advancements and clinical implications.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Sensing in Urinary Catheter Systems: From Measurands and Signal Fidelity to Supportable Clinical Claims.Sensors (Basel, Switzerland) · 2026Review
- Intelligent surgical drainage - digitizing the analysis of drainage fluid in patients with surgical drains.PloS one · 2025Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Urine diagnostics are crucial for identifying urological disorders and systemic diseases. Monitoring bladder catheters for urine output and early signs of urinary tract infections (UTIs) is essential but labor-intensive and prone to documentation errors. Recent advances in electronic monitoring and spectroscopy offer potential improvement in this process. This study introduces a novel smart sensor system for urinary catheters, enabling digital, continuous, automated real-time spectroscopic urine monitoring. A prototype consisting of a mini-spectrometer integrated with a custom lens array and hyperspectral illumination source was developed for urine analysis. It measures light intensity across 288 channels (340-850 nm) from multiple angles and exposure times, capturing detailed spectral data. Analyzing 401 urine samples from 168 patients, statistical models in R software were used to assess the dependency between spectral data and clinical laboratory values. The prototype accurately detected response variables like bilirubin, erythrocytes, pH, protein, specific gravity, and urobilinogen, with AUC values indicating good to very good discrimination. Response variables like glucose and nitrite, which do not absorb within the measured spectrum, showed minimal correlation. Our smart catheter system presents the potential for a significant advancement in urine monitoring, providing continuous, accurate analysis of parameters absorbing within the visible light spectrum.
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Registered trials
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