ArticleLasers in medical science2016
Estimating the concentration of urea and creatinine in the human serum of normal and dialysis patients through Raman spectroscopy.
Article in Lasers in medical science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 28 citations in OpenAlex.
- FPAW fromNutrients · 2025Article
- Comparison of different Raman spectrometer models in the quantification of blood serum analytes.Lasers in medical science · 2025Article
- The effect of chlorpyrifos oral exposure on the histomorphometric and kidney function in Wistar rat.Indian journal of pharmacology · 2024Article
- Effects of essential mineral elements deficiency and supplementation on serum mineral elements concentration and biochemical parameters in grazing Mongolian sheep.Frontiers in veterinary science · 2023Article
- The Potential Applications of Raman Spectroscopy in Kidney Diseases.Journal of personalized medicine · 2022Review
- Diagnosing COVID-19 in human serum using Raman spectroscopy.Lasers in medical science · 2022Article
- Analytical performance of Raman spectroscopy in assaying biochemical components in human serum.Lasers in medical science · 2022Article
- Diagnosing COVID-19 in human sera with detected immunoglobulins IgM and IgG by means of Raman spectroscopy.Journal of Raman spectroscopy : JRS · 2021Article
- Review
- Diagnosing sickle cell disease and iron deficiency anemia in human blood by Raman spectroscopy.Lasers in medical science · 2020Article
- Detecting creatine excreted in the urine of swimming athletes by means of Raman spectroscopy.Lasers in medical science · 2020Article
- Total Iron Measurement in Human Serum With a Novel Smartphone-Based Assay.IEEE journal of translational engineering in health and medicine · 2020Article
- Discrimination model applied to urinalysis of patients with diabetes and hypertension aiming at diagnosis of chronic kidney disease by Raman spectroscopy.Lasers in medical science · 2017Article
- Quantifying glucose and lipid components in human serum by Raman spectroscopy and multivariate statistics.Lasers in medical science · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Urea and creatinine are commonly used as biomarkers of renal function. Abnormal concentrations of these biomarkers are indicative of pathological processes such as renal failure. This study aimed to develop a model based on Raman spectroscopy to estimate the concentration values of urea and creatinine in human serum. Blood sera from 55 clinically normal subjects and 47 patients with chronic kidney disease undergoing dialysis were collected, and concentrations of urea and creatinine were determined by spectrophotometric methods. A Raman spectrum was obtained with a high-resolution dispersive Raman spectrometer (830 nm). A spectral model was developed based on partial least squares (PLS), where the concentrations of urea and creatinine were correlated with the Raman features. Principal components analysis (PCA) was used to discriminate dialysis patients from normal subjects. The PLS model showed r = 0.97 and r = 0.93 for urea and creatinine, respectively. The root mean square errors of cross-validation (RMSECV) for the model were 17.6 and 1.94 mg/dL, respectively. PCA showed high discrimination between dialysis and normality (95 % accuracy). The Raman technique was able to determine the concentrations with low error and to discriminate dialysis from normal subjects, consistent with a rapid and low-cost test.
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.