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Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis
Diagnosis of asthma is often challenging in primary-care physicians due to lack of tools measuring airway obstruction and variability. Symptom-based diagnosis of asthma utilizing objective diagnostic parameters and appropriate software would be useful in clinical practice. A total of 302 adult patie...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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The Korean Academy of Medical Sciences
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2693849/ https://www.ncbi.nlm.nih.gov/pubmed/17982231 http://dx.doi.org/10.3346/jkms.2007.22.5.832 |
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author | Choi, Byoung Whui Yoo, Kwang-Ha Jeong, Jae-Won Yoon, Ho Joo Kim, Sang-Heon Park, Yong-Mean Kim, Wo-Kyung Oh, Jae-Won Rha, Yeong-Ho Pyun, Bok-Yang Chang, Suk-Il Moon, Hee-Bom Kim, You-Young Cho, Sang-Heon |
author_facet | Choi, Byoung Whui Yoo, Kwang-Ha Jeong, Jae-Won Yoon, Ho Joo Kim, Sang-Heon Park, Yong-Mean Kim, Wo-Kyung Oh, Jae-Won Rha, Yeong-Ho Pyun, Bok-Yang Chang, Suk-Il Moon, Hee-Bom Kim, You-Young Cho, Sang-Heon |
author_sort | Choi, Byoung Whui |
collection | PubMed |
description | Diagnosis of asthma is often challenging in primary-care physicians due to lack of tools measuring airway obstruction and variability. Symptom-based diagnosis of asthma utilizing objective diagnostic parameters and appropriate software would be useful in clinical practice. A total of 302 adult patients with respiratory symptoms responded to a questionnaire regarding asthma symptoms and provoking factors. Questions were asked and recorded by physicians into a computer program. A definite diagnosis of asthma was made based on a positive response to methacholine bronchial provocation or bronchodilator response (BDR) testing. Multivariate logistic regression analysis was used to evaluate the significance of questionnaire responses in terms of discriminating asthmatics. Asthmatic patients showed higher total symptom scores than non-asthmatics (mean 5.93 vs. 4.93; p<0.01). Multivariate logistic regression analysis identified that response to questions concerning the following significantly discriminated asthmatics; wheezing with dyspnea, which is aggravated at night, and by exercise, cold air, and upper respiratory infection. Moreover, the presence of these symptoms was found to agree significantly with definite diagnosis of asthma (by kappa statistics). Receiver-operating characteristic curve analysis revealed that the diagnostic accuracy of symptom-based diagnosis was high with an area under the curve of 0.647±0.033. Using a computer-assisted symptom-based diagnosis program, it is possible to increase the accuracy of diagnosing asthma in general practice, when the facilities required to evaluate airway hyperresponsiveness or BDR are unavailable. |
format | Text |
id | pubmed-2693849 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | The Korean Academy of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-26938492009-06-11 Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis Choi, Byoung Whui Yoo, Kwang-Ha Jeong, Jae-Won Yoon, Ho Joo Kim, Sang-Heon Park, Yong-Mean Kim, Wo-Kyung Oh, Jae-Won Rha, Yeong-Ho Pyun, Bok-Yang Chang, Suk-Il Moon, Hee-Bom Kim, You-Young Cho, Sang-Heon J Korean Med Sci Original Article Diagnosis of asthma is often challenging in primary-care physicians due to lack of tools measuring airway obstruction and variability. Symptom-based diagnosis of asthma utilizing objective diagnostic parameters and appropriate software would be useful in clinical practice. A total of 302 adult patients with respiratory symptoms responded to a questionnaire regarding asthma symptoms and provoking factors. Questions were asked and recorded by physicians into a computer program. A definite diagnosis of asthma was made based on a positive response to methacholine bronchial provocation or bronchodilator response (BDR) testing. Multivariate logistic regression analysis was used to evaluate the significance of questionnaire responses in terms of discriminating asthmatics. Asthmatic patients showed higher total symptom scores than non-asthmatics (mean 5.93 vs. 4.93; p<0.01). Multivariate logistic regression analysis identified that response to questions concerning the following significantly discriminated asthmatics; wheezing with dyspnea, which is aggravated at night, and by exercise, cold air, and upper respiratory infection. Moreover, the presence of these symptoms was found to agree significantly with definite diagnosis of asthma (by kappa statistics). Receiver-operating characteristic curve analysis revealed that the diagnostic accuracy of symptom-based diagnosis was high with an area under the curve of 0.647±0.033. Using a computer-assisted symptom-based diagnosis program, it is possible to increase the accuracy of diagnosing asthma in general practice, when the facilities required to evaluate airway hyperresponsiveness or BDR are unavailable. The Korean Academy of Medical Sciences 2007-10 2007-10-31 /pmc/articles/PMC2693849/ /pubmed/17982231 http://dx.doi.org/10.3346/jkms.2007.22.5.832 Text en Copyright © 2007 The Korean Academy of Medical Sciences http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed 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 original work is properly cited. |
spellingShingle | Original Article Choi, Byoung Whui Yoo, Kwang-Ha Jeong, Jae-Won Yoon, Ho Joo Kim, Sang-Heon Park, Yong-Mean Kim, Wo-Kyung Oh, Jae-Won Rha, Yeong-Ho Pyun, Bok-Yang Chang, Suk-Il Moon, Hee-Bom Kim, You-Young Cho, Sang-Heon Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis |
title | Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis |
title_full | Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis |
title_fullStr | Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis |
title_full_unstemmed | Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis |
title_short | Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis |
title_sort | easy diagnosis of asthma: computer-assisted, symptom-based diagnosis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2693849/ https://www.ncbi.nlm.nih.gov/pubmed/17982231 http://dx.doi.org/10.3346/jkms.2007.22.5.832 |
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