Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis.
10.3346/jkms.2007.22.5.832
- Author:
Byoung Whui CHOI
1
;
Kwang Ha YOO
;
Jae Won JEONG
;
Ho Joo YOON
;
Sang Heon KIM
;
Yong Mean PARK
;
Wo Kyung KIM
;
Jae Won OH
;
Yeong Ho RHA
;
Bok Yang PYUN
;
Suk Il CHANG
;
Hee Bom MOON
;
You Young KIM
;
Sang Heon CHO
Author Information
1. Department of Internal Medicine, Chung-Ang University College of Medicine, Seoul, Korea.
- Publication Type:Original Article ; Clinical Trial ; Research Support, Non-U.S. Gov't
- Keywords:
Asthma;
Diagnosis;
Questionnaires
- MeSH:
Adult;
Asthma/*diagnosis/*pathology;
*Bronchial Provocation Tests;
Bronchodilator Agents/pharmacology;
*Diagnosis, Computer-Assisted;
Female;
Humans;
Male;
Middle Aged;
Observer Variation;
Predictive Value of Tests;
Questionnaires;
ROC Curve;
Regression Analysis;
Sensitivity and Specificity
- From:Journal of Korean Medical Science
2007;22(5):832-838
- CountryRepublic of Korea
- Language:English
-
Abstract:
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.
