Evidence map›Paper›PMID 38857224›Full record

ArticlePloS one2024

Diagnosis of metabolic syndrome in nursing professionals: An accuracy study.

Érica Velasco Dias Gomes, Rebeca de Souza Vasconcelos, Natália Maria Freitas Coelho, Lorena de Carvalho Almeida, Dandara Almeida Reis da Silva, Monique Magnavita Borba da Fonseca Cerqueira, Jeane Magnavita da Fonseca Cerqueira, Sarah Dos Santos Conceição, Johelle de Santana Passos Soares, Lucélia Batista Neves Cunha Magalhães and 21 more

Abstract read
In one paragraph

Article in PloS one, 2024. 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.

  1. Article
  2. 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

31 authors.

Érica Velasco Dias GomesDepartment of Life Sciences, University of Bahia State (UNEB), Salvador, Bahia, Brazil.ORCID 0000-0003-0643-4355
Rebeca de Souza VasconcelosDepartment of Life Sciences, University of Bahia State (UNEB), Salvador, Bahia, Brazil.
Natália Maria Freitas CoelhoDepartment of Life Sciences, University of Bahia State (UNEB), Salvador, Bahia, Brazil.
Lorena de Carvalho AlmeidaDepartment of Life Sciences, University of Bahia State (UNEB), Salvador, Bahia, Brazil.
Dandara Almeida Reis da SilvaDepartment of Life Sciences, University of Bahia State (UNEB), Salvador, Bahia, Brazil.
Monique Magnavita Borba da Fonseca CerqueiraDepartment of Life Sciences, University of Bahia State (UNEB), Salvador, Bahia, Brazil.
Jeane Magnavita da Fonseca CerqueiraDepartment of Life Sciences, University of Bahia State (UNEB), Salvador, Bahia, Brazil.
Sarah Dos Santos ConceiçãoSchool of Health Sciences, University of Brasília (UNB), Brasília, Distrito Federal, Brazil.
Johelle de Santana Passos SoaresSchool of Odontology, Federal University of Bahia (UFBA), Salvador, Bahia Brazil.
Lucélia Batista Neves Cunha MagalhãesDepartment of Medicine, School of Technology and Sciences (UniFTC), Salvador, Bahia Brazil.
Iracema LuaDepartment of Health, State University of Feira de Santana (UEFS), Feira de Santana, Bahia, Brazil.
Ana Claúdia Morais Godoy FigueredoSchool of Health Sciences, University of Brasília, Brasília, Distrito Federal, Brazil.
Vitória Cézar Santos Gonçalves BritoDepartment of Health Science, Federal University of Bahia (UFBA), Salvador, Bahia Brazil.
Sandra Lúcia FernandesDepartment of Health Science, Federal University of Bahia (UFBA), Salvador, Bahia Brazil.
Dayanne de Aguiar VianaDepartment of Medicine, Dom Pedro II University Center (UNIDOMPEDRO), Salvador, Bahia, Brazil.ORCID 0000-0003-1674-3952
Ruan Pablo Duarte FreitasDepartment of Medicine, Dom Pedro II University Center (UNIDOMPEDRO), Salvador, Bahia, Brazil.ORCID 0000-0001-9881-7016
Gabriella Moreira RequiãoDepartment of Medicine, Dom Pedro II University Center (UNIDOMPEDRO), Salvador, Bahia, Brazil.
Luiz Alberto da Silva LimaDepartment of Social Science, State University of Bahia, Serrinha, Bahia, Brazil.
Barbara Kraychete HayesChildren's Hospital of Los Angeles, Los Angeles, California, United States of America.
Isabelle Matos PinheiroDepartment of Technology and Science, Federal Institute of Education, Science and Technology of Bahia, Salvador, Bahia, Brazil.
Maurício Mitsuo MonçãoDepartment of Technology and Science, Federal Institute of Education, Science and Technology of Bahia, Salvador, Bahia, Brazil.
Antônio Carlos Dos Santos SouzaDepartment of Information Technology, Federal Institute of Education, Science and Technology of Bahia. Salvador, Bahia, Brazil.
Simone Seixas da CruzDepartment of Collective Health, Federal University of Recôncavo of Bahia (UFRB), Santo Antônio de Jesus, Bahia, Brazil.
Antônio Marcos Tosoli GomesSchool of Nursing, State University of Rio de Janeiro (UERJ), Rio de Janeiro, Rio de Janeiro, Brazil.
Rodrigo Fernandes Weyll PimentelDepartment of Life Sciences, University of Bahia State (UNEB), Salvador, Bahia, Brazil.
Barbara Oliveira NardesInstitute of Health Science, Federal University of Bahia (UFBA), Salvador, Bahia Brazil.ORCID 0009-0005-1521-3644
Letícia Costa LopesInstitute of Health Science, Federal University of Bahia (UFBA), Salvador, Bahia Brazil.
Neiva Sueli Santana Gonçalves BastosInstitute of Health Science, Federal University of Bahia (UFBA), Salvador, Bahia Brazil.
Argemiro D'OliveiraDepartment of Health Science, Federal University of Bahia (UFBA), Salvador, Bahia Brazil.
Magno Conceição das MercêsDepartment of Life Sciences, University of Bahia State (UNEB), Salvador, Bahia, Brazil.
Julita Maria Freitas CoelhoDepartment of Life Sciences, University of Bahia State (UNEB), Salvador, Bahia, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic Syndrome (MetS) represents a group of cardiovascular risk factors. This article aims to evaluate the accuracy of the tools of MetS diagnosis in Nursing professionals from Primary Health Care (PHC) in Bahia, Brazil. A cross-sectional study with a random sample selected according to essential health information for the diagnostic of MetS. For MetS diagnostic, we used EGIR, NCEP-ATPIII, AACE, IDF, Barbosa et al. (2006), and IDF/AHA/NHLBI (defined as gold standard) definition. Sensitivity, specificity, predictive values, and likelihood ratio were estimated for each diagnostic tool and compared with the gold standard. Kappa statistic was used to determine the agreement between the diagnostic methods. One thousand one hundred and eleven nursing professionals were included in this study. Sensitivity varied from 15% to 95.1%, and specificity varied between 99.5% and 100%. IDF and Barbosa et al. (2006) definitions were more sensitive (95.1% and 92.8%, respectively), and EGIR, NCEP, ATP III, and IDF showed 100% specificity. IDF and Barbosa et al. (2006) use suitable metabolic syndrome identification and confirmation criteria. The highest agreement was found in the definition of the IDF, Barbosa et al. (2006) and the NCEP ATP III. Defining metabolic syndrome with a higher diagnostic accuracy could contribute to the screening and the early identification of nursing professionals with cardiovascular disease risk factors, which provide opportunities for appropriate prevention and treatment.

Indexed as

Metabolic SyndromeAdultBrazilCross-Sectional StudiesFemaleHumansMaleMiddle AgedNursesRisk FactorsSensitivity and Specificity

Identifiers

PMID38857224
PMCPMC11164393

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