Evidence map›Paper›PMID 37322087›Full record

ArticleScientific reports2023

Spectrochemical analysis of blood combined with chemometric techniques for detecting osteosarcopenia.

Tales Gomes da Silva, Camilo L M Morais, Marfran C D Santos, Leomir A S de Lima, Raysa Vanessa de Medeiros Freitas, Ricardo Oliveira Guerra, Kássio M G Lima

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

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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

7 authors.

Tales Gomes da SilvaInstitute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, 59075-970, Brazil.
Camilo L M MoraisInstitute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, 59075-970, Brazil.
Marfran C D SantosInstitute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, 59075-970, Brazil.
Leomir A S de LimaEstácio de Sá Goiás, North Regional, Goiânia, GO, 74063-010, Brazil.
Raysa Vanessa de Medeiros FreitasPostgraduation Program in Health Sciences, Federal University of Rio Grande do Norte, Natal, 59075-970, Brazil.
Ricardo Oliveira GuerraPostgraduation Program in Health Sciences, Federal University of Rio Grande do Norte, Natal, 59075-970, Brazil.
Kássio M G LimaInstitute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, 59075-970, Brazil. kassio.lima@ufrn.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among several complications related to physiotherapy, osteosarcopenia is one of the most frequent in elderly patients. This condition is limiting and quite harmful to the patient's health by disabling several basic musculoskeletal activities. Currently, the test to identify this health condition is complex. In this study, we use mid-infrared spectroscopy combined with chemometric techniques to identify osteosarcopenia based on blood serum samples. The purpose of this study was to evaluate the mid-infrared spectroscopy power to detect osteosarcopenia in community-dwelling older women (n = 62, 30 from patients with osteosarcopenia and 32 healthy controls). Feature reduction and selection techniques were employed in conjunction with discriminant analysis, where a principal component analysis with support vector machines (PCA-SVM) model achieved 89% accuracy to distinguish the samples from patients with osteosarcopenia. This study shows the potential of using infrared spectroscopy of blood samples to identify osteosarcopenia in a simple, fast and objective way.

Indexed as

ChemometricsSupport Vector MachineAgedDiscriminant AnalysisFemaleHumansPrincipal Component AnalysisSpectrophotometry, Infrared

Identifiers

PMID37322087
PMCPMC10272198

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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.