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Identifying viral infections in vaccinated Chronic Obstructive Pulmonary Disease (COPD) patients using clinical features and inflammatory markers
Background Known inflammatory markers have limited sensitivity and specificity to differentiate viral respiratory tract infections from other causes of acute exacerbation of COPD (AECOPD). To overcome this, we developed a multi‐factorial prediction model combining viral symptoms with inflammatory m...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Blackwell Publishing Ltd
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4941951/ https://www.ncbi.nlm.nih.gov/pubmed/20021505 http://dx.doi.org/10.1111/j.1750-2659.2009.00113.x |
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author | Hutchinson, Anastasia F. Black, Jim Thompson, Michelle A. Bozinovski, Steven Brand, Caroline A. Smallwood, David M. Irving, Louis B. Anderson, Gary P. |
author_facet | Hutchinson, Anastasia F. Black, Jim Thompson, Michelle A. Bozinovski, Steven Brand, Caroline A. Smallwood, David M. Irving, Louis B. Anderson, Gary P. |
author_sort | Hutchinson, Anastasia F. |
collection | PubMed |
description | Background Known inflammatory markers have limited sensitivity and specificity to differentiate viral respiratory tract infections from other causes of acute exacerbation of COPD (AECOPD). To overcome this, we developed a multi‐factorial prediction model combining viral symptoms with inflammatory markers. Methods Interleukin‐6 (IL‐6), serum amyloid A (SAA) and viral symptoms were measured in stable COPD and at AECOPD onset and compared with the viral detection rates on multiplex PCR. The predictive accuracy of each measure was assessed using logistic regression and receiver operating characteristics curve (ROC) analysis. Results There was a total of 33 viruses detected at the onset of 148 AECOPD, the majority 26 (79%) were picornavirus. Viral symptoms with the highest predictive values were rhinorrhoea [Odds ratio (OR) 4·52; 95% CI 1·99–10·29; P < 0·001] and sore throat (OR 2·64; 95% CI 1·14–6·08; P = 0·022), combined the AUC ROC curve was 0·67. At AECOPD onset patients experienced a 1·6‐fold increase in IL‐6 (P = 0·008) and 4·5‐fold increase in SAA (P < 0·001). The addition of IL‐6 to the above model significantly improved diagnostic accuracy compared with symptoms alone (AUC ROC 0·80 (P = 0·012). Conclusion The addition of inflammatory markers increases the specificity of a clinical case definition for viral infection, particularly picornavirus infection. |
format | Online Article Text |
id | pubmed-4941951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Blackwell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-49419512016-07-20 Identifying viral infections in vaccinated Chronic Obstructive Pulmonary Disease (COPD) patients using clinical features and inflammatory markers Hutchinson, Anastasia F. Black, Jim Thompson, Michelle A. Bozinovski, Steven Brand, Caroline A. Smallwood, David M. Irving, Louis B. Anderson, Gary P. Influenza Other Respir Viruses Original Articles Background Known inflammatory markers have limited sensitivity and specificity to differentiate viral respiratory tract infections from other causes of acute exacerbation of COPD (AECOPD). To overcome this, we developed a multi‐factorial prediction model combining viral symptoms with inflammatory markers. Methods Interleukin‐6 (IL‐6), serum amyloid A (SAA) and viral symptoms were measured in stable COPD and at AECOPD onset and compared with the viral detection rates on multiplex PCR. The predictive accuracy of each measure was assessed using logistic regression and receiver operating characteristics curve (ROC) analysis. Results There was a total of 33 viruses detected at the onset of 148 AECOPD, the majority 26 (79%) were picornavirus. Viral symptoms with the highest predictive values were rhinorrhoea [Odds ratio (OR) 4·52; 95% CI 1·99–10·29; P < 0·001] and sore throat (OR 2·64; 95% CI 1·14–6·08; P = 0·022), combined the AUC ROC curve was 0·67. At AECOPD onset patients experienced a 1·6‐fold increase in IL‐6 (P = 0·008) and 4·5‐fold increase in SAA (P < 0·001). The addition of IL‐6 to the above model significantly improved diagnostic accuracy compared with symptoms alone (AUC ROC 0·80 (P = 0·012). Conclusion The addition of inflammatory markers increases the specificity of a clinical case definition for viral infection, particularly picornavirus infection. Blackwell Publishing Ltd 2009-12-09 2010-01 /pmc/articles/PMC4941951/ /pubmed/20021505 http://dx.doi.org/10.1111/j.1750-2659.2009.00113.x Text en © 2009 Blackwell Publishing Ltd |
spellingShingle | Original Articles Hutchinson, Anastasia F. Black, Jim Thompson, Michelle A. Bozinovski, Steven Brand, Caroline A. Smallwood, David M. Irving, Louis B. Anderson, Gary P. Identifying viral infections in vaccinated Chronic Obstructive Pulmonary Disease (COPD) patients using clinical features and inflammatory markers |
title | Identifying viral infections in vaccinated Chronic Obstructive Pulmonary Disease (COPD) patients using clinical features and inflammatory markers |
title_full | Identifying viral infections in vaccinated Chronic Obstructive Pulmonary Disease (COPD) patients using clinical features and inflammatory markers |
title_fullStr | Identifying viral infections in vaccinated Chronic Obstructive Pulmonary Disease (COPD) patients using clinical features and inflammatory markers |
title_full_unstemmed | Identifying viral infections in vaccinated Chronic Obstructive Pulmonary Disease (COPD) patients using clinical features and inflammatory markers |
title_short | Identifying viral infections in vaccinated Chronic Obstructive Pulmonary Disease (COPD) patients using clinical features and inflammatory markers |
title_sort | identifying viral infections in vaccinated chronic obstructive pulmonary disease (copd) patients using clinical features and inflammatory markers |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4941951/ https://www.ncbi.nlm.nih.gov/pubmed/20021505 http://dx.doi.org/10.1111/j.1750-2659.2009.00113.x |
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