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The COPD multi-dimensional phenotype: A new classification from the STORICO Italian observational study

BACKGROUND: This paper is aimed to (i) develop an innovative classification of COPD, multi-dimensional phenotype, based on a multidimensional assessment; (ii) describe the identified multi-dimensional phenotypes. METHODS: An exploratory factor analysis to identify the main classificatory variables a...

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Autores principales: Antonelli Incalzi, Raffaele, Canonica, Giorgio Walter, Scichilone, Nicola, Rizzoli, Sara, Simoni, Lucia, Blasi, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743765/
https://www.ncbi.nlm.nih.gov/pubmed/31518364
http://dx.doi.org/10.1371/journal.pone.0221889
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author Antonelli Incalzi, Raffaele
Canonica, Giorgio Walter
Scichilone, Nicola
Rizzoli, Sara
Simoni, Lucia
Blasi, Francesco
author_facet Antonelli Incalzi, Raffaele
Canonica, Giorgio Walter
Scichilone, Nicola
Rizzoli, Sara
Simoni, Lucia
Blasi, Francesco
author_sort Antonelli Incalzi, Raffaele
collection PubMed
description BACKGROUND: This paper is aimed to (i) develop an innovative classification of COPD, multi-dimensional phenotype, based on a multidimensional assessment; (ii) describe the identified multi-dimensional phenotypes. METHODS: An exploratory factor analysis to identify the main classificatory variables and, then, a cluster analysis based on these variables were run to classify the COPD-diagnosed 514 patients enrolled in the STORICO (trial registration number: NCT03105999) study into multi-dimensional phenotypes. RESULTS: The circadian rhythm of symptoms and health-related quality of life, but neither comorbidity nor respiratory function, qualified as primary classificatory variables. Five multidimensional phenotypes were identified: the MILD COPD characterized by no night-time symptoms and the best health status in terms of quality of life, quality of sleep, level of depression and anxiety, the MILD EMPHYSEMATOUS with prevalent dyspnea in the early-morning and day-time, the SEVERE BRONCHITIC with nocturnal and diurnal cough and phlegm, the SEVERE EMPHYSEMATOUS with nocturnal and diurnal dyspnea and the SEVERE MIXED COPD distinguished by higher frequency of symptoms during 24h and worst quality of life, of sleep and highest levels of depression and anxiety. CONCLUSIONS: Our results showed that properly collected respiratory symptoms play a primary classificatory role of COPD patients. The longitudinal observation will disclose the discriminative and prognostic potential of the proposed multidimensional phenotype. TRIAL REGISTRATION: Trial registration number: NCT03105999, date of registration: 10th April 2017.
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spelling pubmed-67437652019-09-20 The COPD multi-dimensional phenotype: A new classification from the STORICO Italian observational study Antonelli Incalzi, Raffaele Canonica, Giorgio Walter Scichilone, Nicola Rizzoli, Sara Simoni, Lucia Blasi, Francesco PLoS One Research Article BACKGROUND: This paper is aimed to (i) develop an innovative classification of COPD, multi-dimensional phenotype, based on a multidimensional assessment; (ii) describe the identified multi-dimensional phenotypes. METHODS: An exploratory factor analysis to identify the main classificatory variables and, then, a cluster analysis based on these variables were run to classify the COPD-diagnosed 514 patients enrolled in the STORICO (trial registration number: NCT03105999) study into multi-dimensional phenotypes. RESULTS: The circadian rhythm of symptoms and health-related quality of life, but neither comorbidity nor respiratory function, qualified as primary classificatory variables. Five multidimensional phenotypes were identified: the MILD COPD characterized by no night-time symptoms and the best health status in terms of quality of life, quality of sleep, level of depression and anxiety, the MILD EMPHYSEMATOUS with prevalent dyspnea in the early-morning and day-time, the SEVERE BRONCHITIC with nocturnal and diurnal cough and phlegm, the SEVERE EMPHYSEMATOUS with nocturnal and diurnal dyspnea and the SEVERE MIXED COPD distinguished by higher frequency of symptoms during 24h and worst quality of life, of sleep and highest levels of depression and anxiety. CONCLUSIONS: Our results showed that properly collected respiratory symptoms play a primary classificatory role of COPD patients. The longitudinal observation will disclose the discriminative and prognostic potential of the proposed multidimensional phenotype. TRIAL REGISTRATION: Trial registration number: NCT03105999, date of registration: 10th April 2017. Public Library of Science 2019-09-13 /pmc/articles/PMC6743765/ /pubmed/31518364 http://dx.doi.org/10.1371/journal.pone.0221889 Text en © 2019 Antonelli Incalzi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Antonelli Incalzi, Raffaele
Canonica, Giorgio Walter
Scichilone, Nicola
Rizzoli, Sara
Simoni, Lucia
Blasi, Francesco
The COPD multi-dimensional phenotype: A new classification from the STORICO Italian observational study
title The COPD multi-dimensional phenotype: A new classification from the STORICO Italian observational study
title_full The COPD multi-dimensional phenotype: A new classification from the STORICO Italian observational study
title_fullStr The COPD multi-dimensional phenotype: A new classification from the STORICO Italian observational study
title_full_unstemmed The COPD multi-dimensional phenotype: A new classification from the STORICO Italian observational study
title_short The COPD multi-dimensional phenotype: A new classification from the STORICO Italian observational study
title_sort copd multi-dimensional phenotype: a new classification from the storico italian observational study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743765/
https://www.ncbi.nlm.nih.gov/pubmed/31518364
http://dx.doi.org/10.1371/journal.pone.0221889
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