J Korean Med Sci.  2007 Oct;22(5):832-838. 10.3346/jkms.2007.22.5.832.

Easy Diagnosis of Asthma: Computer-Assisted, Symptom-Based Diagnosis

• Choi BW
• Yoo KH
• Jeong JW
• Yoon HJ
• Kim SH
• Park YM
• Kim WK
• Oh JW
• Rha YH
• Pyun BY
• Chang SI
• Moon HB
• Kim YY
• Cho SH

• KMID: 1713289
• DOI: http://doi.org/10.3346/jkms.2007.22.5.832

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.

Keyword

Asthma; Diagnosis; Questionnaires

MeSH Terms

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

Figure

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  Fig. 1 Distribution of total symptom scores of total patients, asthmatics and non-asthmatics.

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  Fig. 2 Percentages of patients who responded "yes" to each question in asthmatics and non-asthmatics. At entry, the "yes" response rate to each question is shown according to definite diagnosis of asthma.

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  Fig. 3 ROC curve for the total symptom score. ROC curve was plotted by sensitivity and 1-specificity of total symptom scores.

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