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Computational phenotyping of obstructive airway diseases: protocol for a systematic review
BACKGROUND: Over the last decade, computational sciences have contributed immensely to characterization of phenotypes of airway diseases, but it is difficult to compare derived phenotypes across studies, perhaps as a result of the different decisions that fed into these phenotyping exercises. We aim...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559879/ https://www.ncbi.nlm.nih.gov/pubmed/36229872 http://dx.doi.org/10.1186/s13643-022-02078-0 |
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author | Bashir, Muwada Bashir Awad Basna, Rani Zhang, Guo-Qiang Backman, Helena Lindberg, Anne Ekerljung, Linda Axelsson, Malin Hedman, Linnea Vanfleteren, Lowie Lundbäck, Bo Rönmark, Eva Nwaru, Bright I. |
author_facet | Bashir, Muwada Bashir Awad Basna, Rani Zhang, Guo-Qiang Backman, Helena Lindberg, Anne Ekerljung, Linda Axelsson, Malin Hedman, Linnea Vanfleteren, Lowie Lundbäck, Bo Rönmark, Eva Nwaru, Bright I. |
author_sort | Bashir, Muwada Bashir Awad |
collection | PubMed |
description | BACKGROUND: Over the last decade, computational sciences have contributed immensely to characterization of phenotypes of airway diseases, but it is difficult to compare derived phenotypes across studies, perhaps as a result of the different decisions that fed into these phenotyping exercises. We aim to perform a systematic review of studies using computational approaches to phenotype obstructive airway diseases in children and adults. METHODS AND ANALYSIS: We will search PubMed, Embase, Scopus, Web of Science, and Google Scholar for papers published between 2010 and 2020. Conferences proceedings, reference list of included papers, and experts will form additional sources of literature. We will include observational epidemiological studies that used a computational approach to derive phenotypes of chronic airway diseases, whether in a general population or in a clinical setting. Two reviewers will independently screen the retrieved studies for eligibility, extract relevant data, and perform quality appraisal of included studies. A third reviewer will arbitrate any disagreements in these processes. Quality appraisal of the studies will be undertaken using the Effective Public Health Practice Project quality assessment tool. We will use summary tables to describe the included studies. We will narratively synthesize the generated evidence, providing critical assessment of the populations, variables, and computational approaches used in deriving the phenotypes across studies CONCLUSION: As progress continues to be made in the area of computational phenotyping of chronic obstructive airway diseases, this systematic review, the first on this topic, will provide the state of the art on the field and highlight important perspectives for future works. ETHICS AND DISSEMINATION: No ethical approval is needed for this work is based only on the published literature and does not involve collection of any primary or human data. REGISTRATION AND REPORTING: SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020164898 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-022-02078-0. |
format | Online Article Text |
id | pubmed-9559879 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-95598792022-10-14 Computational phenotyping of obstructive airway diseases: protocol for a systematic review Bashir, Muwada Bashir Awad Basna, Rani Zhang, Guo-Qiang Backman, Helena Lindberg, Anne Ekerljung, Linda Axelsson, Malin Hedman, Linnea Vanfleteren, Lowie Lundbäck, Bo Rönmark, Eva Nwaru, Bright I. Syst Rev Protocol BACKGROUND: Over the last decade, computational sciences have contributed immensely to characterization of phenotypes of airway diseases, but it is difficult to compare derived phenotypes across studies, perhaps as a result of the different decisions that fed into these phenotyping exercises. We aim to perform a systematic review of studies using computational approaches to phenotype obstructive airway diseases in children and adults. METHODS AND ANALYSIS: We will search PubMed, Embase, Scopus, Web of Science, and Google Scholar for papers published between 2010 and 2020. Conferences proceedings, reference list of included papers, and experts will form additional sources of literature. We will include observational epidemiological studies that used a computational approach to derive phenotypes of chronic airway diseases, whether in a general population or in a clinical setting. Two reviewers will independently screen the retrieved studies for eligibility, extract relevant data, and perform quality appraisal of included studies. A third reviewer will arbitrate any disagreements in these processes. Quality appraisal of the studies will be undertaken using the Effective Public Health Practice Project quality assessment tool. We will use summary tables to describe the included studies. We will narratively synthesize the generated evidence, providing critical assessment of the populations, variables, and computational approaches used in deriving the phenotypes across studies CONCLUSION: As progress continues to be made in the area of computational phenotyping of chronic obstructive airway diseases, this systematic review, the first on this topic, will provide the state of the art on the field and highlight important perspectives for future works. ETHICS AND DISSEMINATION: No ethical approval is needed for this work is based only on the published literature and does not involve collection of any primary or human data. REGISTRATION AND REPORTING: SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020164898 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-022-02078-0. BioMed Central 2022-10-13 /pmc/articles/PMC9559879/ /pubmed/36229872 http://dx.doi.org/10.1186/s13643-022-02078-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Protocol Bashir, Muwada Bashir Awad Basna, Rani Zhang, Guo-Qiang Backman, Helena Lindberg, Anne Ekerljung, Linda Axelsson, Malin Hedman, Linnea Vanfleteren, Lowie Lundbäck, Bo Rönmark, Eva Nwaru, Bright I. Computational phenotyping of obstructive airway diseases: protocol for a systematic review |
title | Computational phenotyping of obstructive airway diseases: protocol for a systematic review |
title_full | Computational phenotyping of obstructive airway diseases: protocol for a systematic review |
title_fullStr | Computational phenotyping of obstructive airway diseases: protocol for a systematic review |
title_full_unstemmed | Computational phenotyping of obstructive airway diseases: protocol for a systematic review |
title_short | Computational phenotyping of obstructive airway diseases: protocol for a systematic review |
title_sort | computational phenotyping of obstructive airway diseases: protocol for a systematic review |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559879/ https://www.ncbi.nlm.nih.gov/pubmed/36229872 http://dx.doi.org/10.1186/s13643-022-02078-0 |
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