Evidence map›Paper›PMID 36837911›Full record

ArticleMetabolites2023

Comparison of Diagnostic Models to Estimate the Risk of Metabolic Syndrome in a Chilean Pediatric Population: A Cross-Sectional Study.

Marlín Solorzano, Gislaine Granfeldt, Natalia Ulloa, Guillermo Molina-Recio, Rafael Molina-Luque, Claudio Aguayo, Fanny Petermann-Rocha, Miquel Martorell

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

8 authors at 4 institutions in 3 countries.

Marlín SolorzanoPrograma de Magíster en Nutrición Humana, Departamento de Nutrición y Dietética, Universidad de Concepción, Concepción 4070386, Chile.ORCID 0000-0001-5478-7337
Gislaine GranfeldtDepartamento de Nutrición y Dietética, Facultad de Farmacia, Universidad de Concepción, Concepción 4070386, Chile.
Natalia UlloaDepartamento de Bioquímica Clínica e Inmunología, Facultad de Farmacia, Universidad de Concepción, Concepción 4070386, Chile.ORCID 0000-0002-0437-5016
Guillermo Molina-RecioLifestyles, Innovation and Health (GA-16), Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Córdoba, Spain.ORCID 0000-0002-0005-4901
Rafael Molina-LuqueLifestyles, Innovation and Health (GA-16), Maimonides Biomedical Research Institute of Cordoba (IMIBIC), 14004 Córdoba, Spain.ORCID 0000-0002-5223-7400
Claudio AguayoCentro de Vida Saludable, Universidad de Concepción, Concepción 4070386, Chile.ORCID 0000-0003-4565-9602
Fanny Petermann-RochaCentro de Investigación Biomédica, Facultad de Medicina, Universidad Diego Portales, Santiago 8370068, Chile.ORCID 0000-0002-4384-4962
Miquel MartorellDepartamento de Nutrición y Dietética, Facultad de Farmacia, Universidad de Concepción, Concepción 4070386, Chile.ORCID 0000-0003-3183-7623
University of Concepción · CLInstituto Maimónides de Investigación Biomédica de Córdoba · ESPontificia Universidad Católica de Chile · CLUniversidad Diego Portales · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pediatric population has various criteria for measuring metabolic syndrome (MetS). The diversity of consensus for diagnosis has led to different non-comparable reported prevalence. Given the increase in its prevalence in pediatric ages, it is necessary to develop efficient methods to encourage early detection. Consequently, early screening for the risk of MetS could favor timely action in preventing associated comorbidities in adulthood. This study aimed to establish the diagnostic capacity of models that use non-invasive (anthropometric) and invasive (serum biomarkers) variables for the early detection of MetS in Chilean children. A cross-sectional study was carried out on 220 children aged 6 to 11. Multivariate logistic regressions and discriminant analyses were applied to determine the diagnostic capacity of invasive and non-invasive variables. Based on these results, four diagnostic models were created and compared: (i) anthropometric, (ii) hormonal (insulin, leptin, and adiponectin), (iii) Lipid A (high-density cholesterol lipoprotein [HDL-c] and triglycerides [TG]) and (iv) Lipid B (TG/HDL-c). The prevalence of MetS was 26.8%. Lipid biomarkers (HDL-c and TG) and their ratio (TG/HDL-c) presented higher diagnostic capacity, above 80%, followed by body mass index (BMI, 0.71-0.88) and waist-to-height ratio (WHtR, 0.70-0.87). The lipid model A was the most accurate (sensitivity [S] = 62.7%, specificity [E] = 96.9%, validity index 87.7%), followed by the anthropometric model (S = 69.5%, E = 88.8% and validity index = 83.6%). In conclusion, detecting MetS was possible through invasive and non-invasive methods tested in overweight and obese children. The proposed models based on anthropometric variables, or serum biomarkers of the lipid model A, presented acceptable validity indices. Moreover, they were higher than those that measured adipokines, leptin, and adiponectin. The anthropometric model was the most cost-effective and easy to apply in different environments.

Indexed as

adipokinesanthropometryearly diagnosismetabolic biomarkersmetabolic syndromepediatric obesity

Identifiers

PMID36837911
PMCPMC9958789
OpenAlexW4321107450

What Socratic 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 Socratic graph.