ArticleScientific reports2024
C-reactive protein (CRP) evaluation in human urine using optical sensor supported by machine learning.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Biomimetic Carbon-Based Nanomaterials: From Design Strategies to Next-Generation Biosensing and Theranostic Applications.Small (Weinheim an der Bergstrasse, Germany) · 2025Review
- Machine learning comparison for biomarker level estimation in wastewater dynamics monitoring.Scientific reports · 2025Article
- Alleviation of exercise-induced injury by hydrogen inhalation via the reduction of oxidative stress and inflammation in athletes.Journal of thoracic disease · 2025Article
- Optical Method for the Detection of Viral RNA Using an Optical Fiber Sensor.Journal of biophotonics · 2025Article
- Where Do We Stand in the Management of Rheumatoid Arthritis Ahead of EULAR/ACR 2025?Clinics and practice · 2025Review
- Enhanced Sensitivity Mach-Zehnder Interferometer-Based Tapered-in-Tapered Fiber-Optic Biosensor for the Immunoassay of C-Reactive Protein.Biosensors · 2025Article
- Enzyme-free immunoassay for rapid, sensitive, and selective detection of C-reactive protein.Analytical and bioanalytical chemistry · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
The rapid and sensitive indicator of inflammation in the human body is C-Reactive Protein (CRP). Determination of CRP level is important in medical diagnostics because, depending on that factor, it may indicate, e.g., the occurrence of inflammation of various origins, oncological, cardiovascular, bacterial or viral events. In this study, we describe an interferometric sensor able to detect the CRP level for distinguishing between no-inflammation and inflammation states. The measurement head was made of a single mode optical fiber with a microsphere structure created at the tip. Its surface has been biofunctionalized for specific CRP bonding. Standardized CRP solutions were measured in the range of 1.9 µg/L to 333 mg/L and classified in the initial phase of the study. The real samples obtained from hospitalized patients with diagnosed Urinary Tract Infection or Urosepsis were then investigated. 27 machine learning classifiers were tested for labeling the phantom samples as normal or high CRP levels. With the use of the ExtraTreesClassifier we obtained an accuracy of 95% for the validation dataset. The results of real samples classification showed up to 100% accuracy for the validation dataset using XGB classifier.
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What Socratic holds
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 Socratic graph.