Evidence map›Paper›PMID 33537931›Full record

ArticleLasers in medical science2022

Analytical performance of Raman spectroscopy in assaying biochemical components in human serum.

Stella Giansante, Hector Enrique Giana, Adriana Barrinha Fernandes, Landulfo Silveira

Abstract read
PubMed Publisher
In one paragraph

Article in Lasers in medical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Stella GiansanteCenter for Innovation, Technology and Education - CITÉ, Universidade Anhembi Morumbi - UAM, Parque Tecnológico de São José dos Campos, Estr. Dr. Altino Bondensan, 500, São José dos Campos, SP, 12247-016, Brazil.
Hector Enrique GianaLaboratory of Clinical Analyses Oswaldo Cruz, Praça Cândida Maria Cesar Sawaya Giana, 128, Jardim Nova América, São José dos Campos, SP, 12243-003, Brazil.
Adriana Barrinha FernandesCenter for Innovation, Technology and Education - CITÉ, Universidade Anhembi Morumbi - UAM, Parque Tecnológico de São José dos Campos, Estr. Dr. Altino Bondensan, 500, São José dos Campos, SP, 12247-016, Brazil.
Landulfo SilveiraCenter for Innovation, Technology and Education - CITÉ, Universidade Anhembi Morumbi - UAM, Parque Tecnológico de São José dos Campos, Estr. Dr. Altino Bondensan, 500, São José dos Campos, SP, 12247-016, Brazil. landulfo.silveira@gmail.com.ORCID http://orcid.org/0000-0002-6616-3334

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 306344/2017-3Fundação de Amparo à Pesquisa do Estado de São Paulo 2009/01788-5
6 · The paper itself

Abstract

Chronic non-infectious diseases are important to research as they are the main causes of death in Brazil and worldwide. One very important chronic non-infectious disease is cardiovascular disease, whose risk factors (diabetes, dyslipidemia, and renal failure) can be detected through assessments of serum biochemical components. The objective of this study was to evaluate the analytical performance of Raman spectroscopy for analysis of lipid profile (total cholesterol, triglycerides, and HDL cholesterol), non-protein nitrogenous compounds (urea and creatinine), and glucose in 242 human serum samples. Models to discriminate and quantify the samples were developed using the predicted concentration by quantitative regression model based on partial least squares (PLS). The analytical error for the "leave-one-out" cross-validation based on the predicted PLS concentration was 10.5 mg/dL for total cholesterol, 21.4 mg/dL for triglyceride, 13.0 mg/dL for HDL cholesterol, 4.9 mg/dL for urea, 0.21 mg/dL for creatinine, and 15.4 mg/dL for glucose. The Kappa coefficient indicate very good agreement for cholesterol (0.83), good for triglyceride (0.77), urea (0.70) and creatinine (0.66), and fair for HDL cholesterol (0.38) and glucose (0.30). The results of the analytical performance demonstrated that Raman spectroscopy can be considered an important methodology to screen the population, especially for serum triglycerides and cholesterol.

Indexed as

CholesterolSpectrum Analysis, RamanHumansLeast-Squares AnalysisSerumTriglyceridesCholesterolTriglyceridesBiochemical profileDiscriminant analysisQuantificationRaman spectroscopySerum

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.