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 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

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 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

Performance characterization of drop-on-demand micro-dispensing system with multi-printheads

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Comparison of micro-dispensing performance between micro-valve and piezoelectric printhead

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