Evidence map›Paper›PMID 32666023›Full record

ArticleJBMR plus2020

Potential Biomarkers of the Turnover, Mineralization, and Volume Classification: Results Using NMR Metabolomics in Hemodialysis Patients.

Aline L Baptista, Kallyandra Padilha, Pamella A Malagrino, Gabriela Venturini, Ana Cm Zeri, Luciene M Dos Reis, Janaina S Martins, Vanda Jorgetti, Alexandre C Pereira, Silvia M Titan and 1 more

Open access · goldAbstract read
In one paragraph

Article in JBMR plus, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 43% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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

11 authors at 3 institutions in 2 countries.

Aline L BaptistaLaboratório de Investigação Médica/LIM 16, Nephrology Division Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo São Paulo Brazil.
Kallyandra PadilhaLaboratório de Genética e Cardiologia Molecular Instituto do Coração (INCOR), Faculdade de Medicina, Universidade de São Paulo São Paulo Brazil.
Pamella A MalagrinoLaboratório de Genética e Cardiologia Molecular Instituto do Coração (INCOR), Faculdade de Medicina, Universidade de São Paulo São Paulo Brazil.
Gabriela VenturiniLaboratório de Genética e Cardiologia Molecular Instituto do Coração (INCOR), Faculdade de Medicina, Universidade de São Paulo São Paulo Brazil.
Ana Cm ZeriBiosciences National Laboratory LNBio Campinas Brazil.
Luciene M Dos ReisLaboratório de Investigação Médica/LIM 16, Nephrology Division Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo São Paulo Brazil.
Janaina S MartinsEndocrine Unit Massachusetts General Hospital Boston MA USA.
Vanda JorgettiLaboratório de Investigação Médica/LIM 16, Nephrology Division Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo São Paulo Brazil.
Alexandre C PereiraLaboratório de Genética e Cardiologia Molecular Instituto do Coração (INCOR), Faculdade de Medicina, Universidade de São Paulo São Paulo Brazil.
Silvia M TitanNephrology Division Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo São Paulo Brazil.ORCID https://orcid.org/0000-0002-6206-1111
Rosa Ma MoysesLaboratório de Investigação Médica/LIM 16, Nephrology Division Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo São Paulo Brazil.ORCID https://orcid.org/0000-0002-7902-2127
Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo · BRBrazilian Biosciences National Laboratory · BRHarvard University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bone biopsy is still the gold standard to assess bone turnover (T), mineralization (M), and volume (V) in CKD patients, and serum biomarkers are not able to replace histomorphometry. Recently, metabolomics has emerged as a new technique that could allow for the identification of new biomarkers useful for disease diagnosis or for the understanding of pathophysiologic mechanisms, but it has never been assessed in the chronic kidney disease-mineral and bone disorder (CKD-MBD) scenario. In this study, we investigated the association between serum metabolites and the bone TMV classification in patients with end-stage renal disease by using serum NMR spectroscopy and bone biopsy of 49 hemodialysis patients from a single center in Brazil. High T was identified in 21 patients and was associated with higher levels of dimethylsulfone, glycine, citrate, and N-acetylornithine. The receiver-operating characteristic curve for the combination of PTH and these metabolites provided an area under the receiver-operating characteristic curve (AUC) of 0.86 (0.76 to 0.97). Abnormal M was identified in 30 patients and was associated with lower ethanol. The AUC for age, diabetes mellitus, and ethanol was 0.83 (0.71 to 0.96). Low V was identified in 17 patients and was associated with lower carnitine. The association of age, phosphate, and carnitine provided an AUC of 0.83 (0.70 to 0.96). Although differences among the curves by adding selected metabolites to traditional models were not statistically significant, the accuracy of the diagnosis according to the TMV classification seemed to be improved. This is the first study to evaluate the TMV classification system in relation to the serum metabolome assessed by NMR spectroscopy, showing that selected metabolites may help in the evaluation of bone phenotypes in CKD-MBD. © 2020 The Authors.

Indexed as

ANALYSIS/QUANTITATION OF BONEBIOCHEMICAL MARKERS OF BONE TURNOVERBONE HISTOMORPHOMETRYBONE MODELING AND REMODELINGDISEASES AND DISORDERS OF/RELATED TO BONENMR SPECTROSCOPY

Identifiers

PMID32666023
PMCPMC7340447
OpenAlexW3023270591

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.