Yoshihiro Kanemitsu1, Hisako Matsumoto2, Nuriamina Osman3, Tsuyoshi Oguma3, Tadao Nagasaki3, Yumi Izuhara3, Isao Ito3, Tomoko Tajiri3, Toshiyuki Iwata3, Akio Niimi1, Michiaki Mishima3. 1. Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoinkawahra-cho, Sakyo-ku, Kyoto, Japan; Department of Respiratory Medicine, Allergy and Clinical Immunology, Graduate School of Medical Science, Nagoya City University, Aichi, Japan. 2. Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoinkawahra-cho, Sakyo-ku, Kyoto, Japan. Electronic address: hmatsumo@kuhp.kyoto-u.ac.jp. 3. Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoinkawahra-cho, Sakyo-ku, Kyoto, Japan.
Abstract
BACKGROUND: Fractional exhaled nitric oxide (FeNO) is considered an alternative marker of eosinophilic airway inflammation and is sometimes incorporated in the diagnosis of asthma. However, many patients with cough variant asthma (CVA) demonstrate an FeNO in the normal range. Therefore, additional information is needed to confirm the diagnosis of CVA, particularly in patients with low FeNO levels. We aimed to investigate the feasibility of using cough triggers to help diagnose CVA. METHODS: We studied 163 patients presenting with prolonged/chronic cough alone (including 104 CVA patients) who underwent FeNO measurements and an airway responsiveness test, and answered a questionnaire listing 18 cough triggers. The sensitivity and specificity of FeNO levels and cough triggers for the diagnosis of CVA were determined. RESULTS: CVA patients showed higher FeNO levels than non-CVA patients. When the cut-off value of FeNO levels for the diagnosis of CVA was set at 22ppb, its sensitivity was 57%. CVA patients more frequently responded to "cold air" and "talking" as cough triggers than non-CVA patients. When the analysis was confined to those with a low FeNO (<22ppb) group, the sensitivity and positive predictive values of "cold air" and "talking" for the diagnosis of CVA were 36% and 70% for "cold air", and 44% and 74% for "talking", respectively. Their specificity was 81%. "Cold air" was associated with airway hyperresponsiveness in all patients with an emphasis on those with low FeNO levels. CONCLUSION: "Cold air" and/or "talking" as cough triggers could be signs for the diagnosis of CVA, particularly when FeNO levels are low. Copyright Â
BACKGROUND: Fractional exhaled nitric oxide (FeNO) is considered an alternative marker of eosinophilic airway inflammation and is sometimes incorporated in the diagnosis of asthma. However, many patients with cough variant asthma (CVA) demonstrate an FeNO in the normal range. Therefore, additional information is needed to confirm the diagnosis of CVA, particularly in patients with low FeNO levels. We aimed to investigate the feasibility of using cough triggers to help diagnose CVA. METHODS: We studied 163 patients presenting with prolonged/chronic cough alone (including 104 CVApatients) who underwent FeNO measurements and an airway responsiveness test, and answered a questionnaire listing 18 cough triggers. The sensitivity and specificity of FeNO levels and cough triggers for the diagnosis of CVA were determined. RESULTS:CVApatients showed higher FeNO levels than non-CVApatients. When the cut-off value of FeNO levels for the diagnosis of CVA was set at 22ppb, its sensitivity was 57%. CVApatients more frequently responded to "cold air" and "talking" as cough triggers than non-CVApatients. When the analysis was confined to those with a low FeNO (<22ppb) group, the sensitivity and positive predictive values of "cold air" and "talking" for the diagnosis of CVA were 36% and 70% for "cold air", and 44% and 74% for "talking", respectively. Their specificity was 81%. "Cold air" was associated with airway hyperresponsiveness in all patients with an emphasis on those with low FeNO levels. CONCLUSION: "Cold air" and/or "talking" as cough triggers could be signs for the diagnosis of CVA, particularly when FeNO levels are low. Copyright Â
Authors: Kawther S Alqudaihi; Nida Aslam; Irfan Ullah Khan; Abdullah M Almuhaideb; Shikah J Alsunaidi; Nehad M Abdel Rahman Ibrahim; Fahd A Alhaidari; Fatema S Shaikh; Yasmine M Alsenbel; Dima M Alalharith; Hajar M Alharthi; Wejdan M Alghamdi; Mohammed S Alshahrani Journal: IEEE Access Date: 2021-07-15 Impact factor: 3.367
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