Literature DB >> 34849084

A History of Recurrent Episodes of Prolonged Cough as a Predictive Value for Determining Cough Variant Asthma in a Primary Care Setting.

Masaaki Mikami1, Katsuyuki Tomita2, Akira Yamasaki3.   

Abstract

BACKGROUND: Many patients visit primary care clinics with a complaint of cough. General practitioners (GPs) developed a list of the causative diseases of cough that can produce a patient's symptoms and signs. Then, the patients' medical histories were evaluated to determine whether the diagnosis of cough variant asthma (CVA) or post-infectious cough (PIC) could have been predicted.
METHODS: We retrospectively investigated 195 outpatients with a complaint of cough. Medical histories of "recurrent episodes of prolonged cough" and "upper respiratory infection" were obtained during the initial visit. The accuracy of medical histories in predicting CVA and PIC was calculated on the area under the curve (AUC).
RESULTS: Among eligible patients with cough, PIC was diagnosed in 99 patients (50.8%), CVA in 40 patients (20.5%), upper airway cough syndrome in 28 patients (14.4%), and chronic obstructive pulmonary disease in 11 patients (5.6%). Among the patients with CVA and those with PIC, 93% and 12%, respectively, had a history of recurrent episodes of prolonged cough. For the diagnosis of CVA, having a history of recurrent episodes of prolonged cough showed a moderately accurate AUC (0.76, 95% CI: 0.71-0.82). On the other hand, for the diagnosis of PIC, having no history of recurrent episodes of prolonged cough also showed a moderately accurate AUC (0.87, 95% CI: 0.82-0.92).
CONCLUSION: The medical history of recurrent episodes of prolonged cough is useful for the prediction of CVA as well as PIC. ©2021 Tottori University Medical Press.

Entities:  

Keywords:  cough variant asthma; post-infectious cough; prolonged cough; recurrent episodes

Year:  2021        PMID: 34849084      PMCID: PMC8612878          DOI: 10.33160/yam.2021.11.005

Source DB:  PubMed          Journal:  Yonago Acta Med        ISSN: 0513-5710            Impact factor:   1.641


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