[Predictive factors of asymptomatic airway hyperresponsiveness in chronic rhinosinusitis with nasal polyps]

Objective:To explore the predictive factors for asymptomatic airway hyperresponsiveness（AAHR） in patients with chronic rhinosinusitis with nasal polyps（CRSwNP）. Methods:A total of 76 CRSwNP patients who were hospitalized in the Department of Otorhinolaryngology of Fenyang Hospital affiliated to Shanxi Medical University from May 2016 to October 2020 were retrospectively analyzed, including 40 patients in AAHR group and 36 patients in non-airway hyperresponsiveness（non-airway hyperresponsiveness, NAHR） group. The clinical symptoms, CT score of paranasal sinuses, eosinophil（EOS） count in peripheral blood and nasal polyp tissue were compared and analyzed. Logistic regression was used to analyze the risk factors of AAHR, and receiver operating characteristics curve was used to judge the predictive value of the parameters. Results:Compared with NAHR group, AAHR group had more symptoms of mouth breathing and postnasal drip, higher total score of CT in ethmoid sinus, sphenoid sinus, olfactory cleft, and more EOS count in peripheral blood and nasal polyp tissue. The differences were statistically significant. There was a positive correlation between EOS count in peripheral blood and in nasal polyp tissue（r=0.324, P<0.01）. Postnasal drip, high posterior ethmoid sinus（PE） score and nasal polyp tissue EOS count were risk factors for AAHR. The predictive value of nasal polyp tissue EOS count was higher than that of PE score（AUC=0.786 and 0.685, respectively）. When the PE score was ≥1.5, the sensitivity was 80.0% and the specificity was 55.6%. When the nasal polyp tissue EOS count was ≥5.67/HPF, the sensitivity was 82.5% and the specificity was 66.7%. Conclusion:The occurrence of AAHR in patients with CRSwNP was related to clinical symptoms, paranasal sinus CT score, peripheral and nasal polyp tissue EOS count. PE score and nasal polyp tissue EOS count can be used to predict AAHR, however nasal polyp tissue EOS has higher predictive value.