ArticleDiagnostics (Basel, Switzerland)2020
Novel Assessment of Urinary Albumin Excretion in Type 2 Diabetes Patients by Raman Spectroscopy.
Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
12 citing papers in PubMed, 33 citations in OpenAlex.
- Development of a smartphone based spectrometer for high-resolution urinalysis.Scientific reports · 2026Article
- Fluorescent biosensor based cerium-doped carbon quantum dots for albumin detection.RSC advances · 2026Article
- Article
- Exploring Surface-Enhanced Raman Spectroscopy of Pyrazine-2-Carbonitrile for Indirect Label-Free Albumin Quantification in anAnalytical chemistry · 2025Article
- Applications and prospects of biomaterials in diabetes management.Frontiers in bioengineering and biotechnology · 2025Review
- Article
- Label-Free SERS of Urine Components: A Powerful Tool for Discriminating Renal Cell Carcinoma through Multivariate Analysis and Machine Learning Techniques.International journal of molecular sciences · 2024Article
- Surface-enhanced Raman Spectroscopy in urinalysis of hypertension patients with kidney disease.Scientific reports · 2024Article
- Rapid diagnosis of membranous nephropathy based on serum and urine Raman spectroscopy combined with deep learning methods.Scientific reports · 2023Article
- SERS for Detection of Proteinuria: A Comparison of Gold, Silver, Al Tape, and Silicon Substrates for Identification of Elevated Protein Concentration in Urine.Sensors (Basel, Switzerland) · 2023Article
- The Potential Applications of Raman Spectroscopy in Kidney Diseases.Journal of personalized medicine · 2022Review
- Biochemical Analysis of Urine Samples from Diabetic and Hypertensive Patients without Renal Dysfunction Using Spectrophotometry and Raman Spectroscopy Techniques Aiming Classification and Diagnosis.Bioengineering (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
. Urinary albumin excretion remains the key biomarker to detect renal complications in type 2 diabetes. As diabetes epidemy increases, particularly in low-income countries, efficient and low-cost methods to measure urinary albumin are needed. In this pilot study, we evaluated the performance of Raman spectroscopy in the assessment of urinary albumin in patients with type 2 diabetes. The spectral Raman analysis of albumin was performed using artificial urine, at five concentrations of albumin and 24 h collection urine samples from ten patients with Type 2 Diabetes. The spectra were obtained after removing the background fluorescence and fitting Gaussian curves to spectral regions containing features of such metabolites. In the samples from patients with type 2 diabetes, we identified the presence of albumin in the peaks of the spectrum located at 663.07, 993.43, 1021.43, 1235.28, 1429.91 and 1633.91 cm
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.