Severity classification for idiopathic pulmonary fibrosis by using fuzzy logic

Detalhes bibliográficos
Autor(a) principal: Lopes, Agnaldo José
Data de Publicação: 2011
Outros Autores: Capone, Domenico, Mogami, Roberto, Lanzillotti, Regina Serrão, Melo, Pedro Lopes de, Jansen, José Manoel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Clinics
Texto Completo: https://www.revistas.usp.br/clinics/article/view/19520
Resumo: OBJECTIVE: To set out a severity classification for idiopathic pulmonary fibrosis (IPF) based on the interaction of pulmonary function parameters with high resolution computed tomography (CT) findings. INTRODUCTION: Despite the contribution of functional and radiological methods in the study of IPF, there are few classification proposals for the disease based on these examinations. METHODS: A cross-sectional study was carried out, in which 41 non-smoking patients with IPF were evaluated. The following high resolution CT findings were quantified using a semi-quantitative scoring system: reticular abnormality, honeycombing and ground-glass opacity. The functional variables were measured by spirometry, forced oscillation technique, helium dilution method, as well as the single-breath method of diffusing capacity of carbon monoxide. With the interaction between functional indexes and high resolution CT scores through fuzzy logic, a classification for IPF has been built. RESULTS: Out of 41 patients studied, 26 were male and 15 female, with a mean age of 70.8 years. Volume measurements were the variables which showed the best interaction with the disease extension on high resolution CT, while the forced vital capacity showed the lowest estimative errors in comparison to total lung capacity. A classification for IPF was suggested based on the 95% confidence interval of the forced vital capacity %: mild group (>92.7); moderately mild (76.9-92.6); moderate (64.3-76.8%); moderately severe (47.1-64.2); severe (24.3-47.0); and very severe (
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spelling Severity classification for idiopathic pulmonary fibrosis by using fuzzy logic Fuzzy logicIdiopathic pulmonary fibrosisRespiratory function testsRespiratory mechanicsTomographyX-ray computed OBJECTIVE: To set out a severity classification for idiopathic pulmonary fibrosis (IPF) based on the interaction of pulmonary function parameters with high resolution computed tomography (CT) findings. INTRODUCTION: Despite the contribution of functional and radiological methods in the study of IPF, there are few classification proposals for the disease based on these examinations. METHODS: A cross-sectional study was carried out, in which 41 non-smoking patients with IPF were evaluated. The following high resolution CT findings were quantified using a semi-quantitative scoring system: reticular abnormality, honeycombing and ground-glass opacity. The functional variables were measured by spirometry, forced oscillation technique, helium dilution method, as well as the single-breath method of diffusing capacity of carbon monoxide. With the interaction between functional indexes and high resolution CT scores through fuzzy logic, a classification for IPF has been built. RESULTS: Out of 41 patients studied, 26 were male and 15 female, with a mean age of 70.8 years. Volume measurements were the variables which showed the best interaction with the disease extension on high resolution CT, while the forced vital capacity showed the lowest estimative errors in comparison to total lung capacity. A classification for IPF was suggested based on the 95% confidence interval of the forced vital capacity %: mild group (>92.7); moderately mild (76.9-92.6); moderate (64.3-76.8%); moderately severe (47.1-64.2); severe (24.3-47.0); and very severe (Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo2011-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/clinics/article/view/1952010.1590/S1807-59322011000600016Clinics; Vol. 66 No. 6 (2011); 1015-1019 Clinics; v. 66 n. 6 (2011); 1015-1019 Clinics; Vol. 66 Núm. 6 (2011); 1015-1019 1980-53221807-5932reponame:Clinicsinstname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/clinics/article/view/19520/21583Lopes, Agnaldo JoséCapone, DomenicoMogami, RobertoLanzillotti, Regina SerrãoMelo, Pedro Lopes deJansen, José Manoelinfo:eu-repo/semantics/openAccess2012-05-23T16:46:20Zoai:revistas.usp.br:article/19520Revistahttps://www.revistas.usp.br/clinicsPUBhttps://www.revistas.usp.br/clinics/oai||clinics@hc.fm.usp.br1980-53221807-5932opendoar:2012-05-23T16:46:20Clinics - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Severity classification for idiopathic pulmonary fibrosis by using fuzzy logic
title Severity classification for idiopathic pulmonary fibrosis by using fuzzy logic
spellingShingle Severity classification for idiopathic pulmonary fibrosis by using fuzzy logic
Lopes, Agnaldo José
Fuzzy logic
Idiopathic pulmonary fibrosis
Respiratory function tests
Respiratory mechanics
Tomography
X-ray computed
title_short Severity classification for idiopathic pulmonary fibrosis by using fuzzy logic
title_full Severity classification for idiopathic pulmonary fibrosis by using fuzzy logic
title_fullStr Severity classification for idiopathic pulmonary fibrosis by using fuzzy logic
title_full_unstemmed Severity classification for idiopathic pulmonary fibrosis by using fuzzy logic
title_sort Severity classification for idiopathic pulmonary fibrosis by using fuzzy logic
author Lopes, Agnaldo José
author_facet Lopes, Agnaldo José
Capone, Domenico
Mogami, Roberto
Lanzillotti, Regina Serrão
Melo, Pedro Lopes de
Jansen, José Manoel
author_role author
author2 Capone, Domenico
Mogami, Roberto
Lanzillotti, Regina Serrão
Melo, Pedro Lopes de
Jansen, José Manoel
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Lopes, Agnaldo José
Capone, Domenico
Mogami, Roberto
Lanzillotti, Regina Serrão
Melo, Pedro Lopes de
Jansen, José Manoel
dc.subject.por.fl_str_mv Fuzzy logic
Idiopathic pulmonary fibrosis
Respiratory function tests
Respiratory mechanics
Tomography
X-ray computed
topic Fuzzy logic
Idiopathic pulmonary fibrosis
Respiratory function tests
Respiratory mechanics
Tomography
X-ray computed
description OBJECTIVE: To set out a severity classification for idiopathic pulmonary fibrosis (IPF) based on the interaction of pulmonary function parameters with high resolution computed tomography (CT) findings. INTRODUCTION: Despite the contribution of functional and radiological methods in the study of IPF, there are few classification proposals for the disease based on these examinations. METHODS: A cross-sectional study was carried out, in which 41 non-smoking patients with IPF were evaluated. The following high resolution CT findings were quantified using a semi-quantitative scoring system: reticular abnormality, honeycombing and ground-glass opacity. The functional variables were measured by spirometry, forced oscillation technique, helium dilution method, as well as the single-breath method of diffusing capacity of carbon monoxide. With the interaction between functional indexes and high resolution CT scores through fuzzy logic, a classification for IPF has been built. RESULTS: Out of 41 patients studied, 26 were male and 15 female, with a mean age of 70.8 years. Volume measurements were the variables which showed the best interaction with the disease extension on high resolution CT, while the forced vital capacity showed the lowest estimative errors in comparison to total lung capacity. A classification for IPF was suggested based on the 95% confidence interval of the forced vital capacity %: mild group (>92.7); moderately mild (76.9-92.6); moderate (64.3-76.8%); moderately severe (47.1-64.2); severe (24.3-47.0); and very severe (
publishDate 2011
dc.date.none.fl_str_mv 2011-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/clinics/article/view/19520
10.1590/S1807-59322011000600016
url https://www.revistas.usp.br/clinics/article/view/19520
identifier_str_mv 10.1590/S1807-59322011000600016
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/clinics/article/view/19520/21583
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo
publisher.none.fl_str_mv Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo
dc.source.none.fl_str_mv Clinics; Vol. 66 No. 6 (2011); 1015-1019
Clinics; v. 66 n. 6 (2011); 1015-1019
Clinics; Vol. 66 Núm. 6 (2011); 1015-1019
1980-5322
1807-5932
reponame:Clinics
instname:Universidade de São Paulo (USP)
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instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Clinics
collection Clinics
repository.name.fl_str_mv Clinics - Universidade de São Paulo (USP)
repository.mail.fl_str_mv ||clinics@hc.fm.usp.br
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