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Spirometry Longitudinal Data Analysis Software (SPIROLA) for Analysis of Spirometry Data in Workplace Prevention or COPD Treatment
Chronic obstructive pulmonary disease (COPD) is one of the leading causes of morbidity and mortality. Periodic spirometry is often recommended for individuals with potential occupational exposure to respiratory hazards and in medical treatment of respiratory disease, to prevent COPD or improve treat...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Bentham Open
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2936036/ https://www.ncbi.nlm.nih.gov/pubmed/20835361 http://dx.doi.org/10.2174/1874431101004010094 |
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author | Hnizdo, Eva Yan, Tieliang Hakobyan, Artak Enright, Paul Beeckman-Wagner, Lu-Ann Hankinson, John Fleming, James Lee Petsonk, Edward |
author_facet | Hnizdo, Eva Yan, Tieliang Hakobyan, Artak Enright, Paul Beeckman-Wagner, Lu-Ann Hankinson, John Fleming, James Lee Petsonk, Edward |
author_sort | Hnizdo, Eva |
collection | PubMed |
description | Chronic obstructive pulmonary disease (COPD) is one of the leading causes of morbidity and mortality. Periodic spirometry is often recommended for individuals with potential occupational exposure to respiratory hazards and in medical treatment of respiratory disease, to prevent COPD or improve treatment outcome. To achieve the full potential of spirometry monitoring in preserving lung function, it is important to maintain acceptable precision of the longitudinal measurements, apply interpretive strategies that identify individuals with abnormal test results or excessive loss of lung function in a timely manner, and use the results for intervention on respiratory disease prevention or treatment modification. We describe novel, easy-to-use visual and analytical software, Spirometry Longitudinal Data Analysis software (SPIROLA), designed to assist healthcare providers in the above aspects of spirometry monitoring. Software application in ongoing workplace spirometry-based medical monitoring programs helped to identify increased spirometry data variability due to deteriorating test quality and subsequent improvement following interventions, and helped to enhance identification of individuals with excessive decline in lung function. |
format | Text |
id | pubmed-2936036 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Bentham Open |
record_format | MEDLINE/PubMed |
spelling | pubmed-29360362010-09-10 Spirometry Longitudinal Data Analysis Software (SPIROLA) for Analysis of Spirometry Data in Workplace Prevention or COPD Treatment Hnizdo, Eva Yan, Tieliang Hakobyan, Artak Enright, Paul Beeckman-Wagner, Lu-Ann Hankinson, John Fleming, James Lee Petsonk, Edward Open Med Inform J Article Chronic obstructive pulmonary disease (COPD) is one of the leading causes of morbidity and mortality. Periodic spirometry is often recommended for individuals with potential occupational exposure to respiratory hazards and in medical treatment of respiratory disease, to prevent COPD or improve treatment outcome. To achieve the full potential of spirometry monitoring in preserving lung function, it is important to maintain acceptable precision of the longitudinal measurements, apply interpretive strategies that identify individuals with abnormal test results or excessive loss of lung function in a timely manner, and use the results for intervention on respiratory disease prevention or treatment modification. We describe novel, easy-to-use visual and analytical software, Spirometry Longitudinal Data Analysis software (SPIROLA), designed to assist healthcare providers in the above aspects of spirometry monitoring. Software application in ongoing workplace spirometry-based medical monitoring programs helped to identify increased spirometry data variability due to deteriorating test quality and subsequent improvement following interventions, and helped to enhance identification of individuals with excessive decline in lung function. Bentham Open 2010-07-08 /pmc/articles/PMC2936036/ /pubmed/20835361 http://dx.doi.org/10.2174/1874431101004010094 Text en © Hnizdo et al.; Licensee Bentham Open. http://creativecommons.org/licenses/by-nc/3.0/ This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited. |
spellingShingle | Article Hnizdo, Eva Yan, Tieliang Hakobyan, Artak Enright, Paul Beeckman-Wagner, Lu-Ann Hankinson, John Fleming, James Lee Petsonk, Edward Spirometry Longitudinal Data Analysis Software (SPIROLA) for Analysis of Spirometry Data in Workplace Prevention or COPD Treatment |
title | Spirometry Longitudinal Data Analysis Software (SPIROLA) for Analysis of Spirometry Data in Workplace Prevention or COPD Treatment |
title_full | Spirometry Longitudinal Data Analysis Software (SPIROLA) for Analysis of Spirometry Data in Workplace Prevention or COPD Treatment |
title_fullStr | Spirometry Longitudinal Data Analysis Software (SPIROLA) for Analysis of Spirometry Data in Workplace Prevention or COPD Treatment |
title_full_unstemmed | Spirometry Longitudinal Data Analysis Software (SPIROLA) for Analysis of Spirometry Data in Workplace Prevention or COPD Treatment |
title_short | Spirometry Longitudinal Data Analysis Software (SPIROLA) for Analysis of Spirometry Data in Workplace Prevention or COPD Treatment |
title_sort | spirometry longitudinal data analysis software (spirola) for analysis of spirometry data in workplace prevention or copd treatment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2936036/ https://www.ncbi.nlm.nih.gov/pubmed/20835361 http://dx.doi.org/10.2174/1874431101004010094 |
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