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Multivariate analysis applied in dataset of Poison Control Center of São Paulo, Brazil

Multivariate analysis techniques could be used to identify possible intercorrelations in intoxications cases. The statistical analyses used were a multiple logistic regression, multiple correspondence analysis, principal component and hierarchical cluster analysis. Of the 320 samples analysed, 192 s...

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Autores principales: Eller, Sarah, Zucoloto, Alexandre Dias, de Oliveira, Carolina Dizioli Rodrigues, Hernandez, Edna Maria Miello, Fruchtengarten, Ligia Veras Gimenez, de Oliveira, Flávia Neri Meira, de Oliveira, Tiago Franco, Yonamine, Mauricio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289857/
https://www.ncbi.nlm.nih.gov/pubmed/32528027
http://dx.doi.org/10.1038/s41598-020-66485-w
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author Eller, Sarah
Zucoloto, Alexandre Dias
de Oliveira, Carolina Dizioli Rodrigues
Hernandez, Edna Maria Miello
Fruchtengarten, Ligia Veras Gimenez
de Oliveira, Flávia Neri Meira
de Oliveira, Tiago Franco
Yonamine, Mauricio
author_facet Eller, Sarah
Zucoloto, Alexandre Dias
de Oliveira, Carolina Dizioli Rodrigues
Hernandez, Edna Maria Miello
Fruchtengarten, Ligia Veras Gimenez
de Oliveira, Flávia Neri Meira
de Oliveira, Tiago Franco
Yonamine, Mauricio
author_sort Eller, Sarah
collection PubMed
description Multivariate analysis techniques could be used to identify possible intercorrelations in intoxications cases. The statistical analyses used were a multiple logistic regression, multiple correspondence analysis, principal component and hierarchical cluster analysis. Of the 320 samples analysed, 192 samples were positive for some of the investigated toxic agents, of which 100 were positive for ethanol and 131 were positive for other substances. It was possible to group the patients into 3 clusters, which appears 66.5% of this information in the three first factorial axes. On the first axis, the male patients were separated from the female patients. Patients exposed to drugs, between 30 and 39 years old were grouped in the same cluster. On the second factorial axis, patients who were intoxicated with ethanol and who became intoxicated with diazepam were grouped. This work contributed to the mapping of intoxication cases at the Poison Control Centre of the São Paulo city, Brazil (CCI-SP) and serves as an initial study for the creation of a database that could be updated constantly and thus could provide a toxicovigilance system for educational policies.
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spelling pubmed-72898572020-06-15 Multivariate analysis applied in dataset of Poison Control Center of São Paulo, Brazil Eller, Sarah Zucoloto, Alexandre Dias de Oliveira, Carolina Dizioli Rodrigues Hernandez, Edna Maria Miello Fruchtengarten, Ligia Veras Gimenez de Oliveira, Flávia Neri Meira de Oliveira, Tiago Franco Yonamine, Mauricio Sci Rep Article Multivariate analysis techniques could be used to identify possible intercorrelations in intoxications cases. The statistical analyses used were a multiple logistic regression, multiple correspondence analysis, principal component and hierarchical cluster analysis. Of the 320 samples analysed, 192 samples were positive for some of the investigated toxic agents, of which 100 were positive for ethanol and 131 were positive for other substances. It was possible to group the patients into 3 clusters, which appears 66.5% of this information in the three first factorial axes. On the first axis, the male patients were separated from the female patients. Patients exposed to drugs, between 30 and 39 years old were grouped in the same cluster. On the second factorial axis, patients who were intoxicated with ethanol and who became intoxicated with diazepam were grouped. This work contributed to the mapping of intoxication cases at the Poison Control Centre of the São Paulo city, Brazil (CCI-SP) and serves as an initial study for the creation of a database that could be updated constantly and thus could provide a toxicovigilance system for educational policies. Nature Publishing Group UK 2020-06-11 /pmc/articles/PMC7289857/ /pubmed/32528027 http://dx.doi.org/10.1038/s41598-020-66485-w Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Eller, Sarah
Zucoloto, Alexandre Dias
de Oliveira, Carolina Dizioli Rodrigues
Hernandez, Edna Maria Miello
Fruchtengarten, Ligia Veras Gimenez
de Oliveira, Flávia Neri Meira
de Oliveira, Tiago Franco
Yonamine, Mauricio
Multivariate analysis applied in dataset of Poison Control Center of São Paulo, Brazil
title Multivariate analysis applied in dataset of Poison Control Center of São Paulo, Brazil
title_full Multivariate analysis applied in dataset of Poison Control Center of São Paulo, Brazil
title_fullStr Multivariate analysis applied in dataset of Poison Control Center of São Paulo, Brazil
title_full_unstemmed Multivariate analysis applied in dataset of Poison Control Center of São Paulo, Brazil
title_short Multivariate analysis applied in dataset of Poison Control Center of São Paulo, Brazil
title_sort multivariate analysis applied in dataset of poison control center of são paulo, brazil
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7289857/
https://www.ncbi.nlm.nih.gov/pubmed/32528027
http://dx.doi.org/10.1038/s41598-020-66485-w
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