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Novel predictors of airway hyperresponsiveness in children with respiratory symptoms without obstructive pattern
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  • Max Reinsberg,
  • Stephanie Siebert,
  • Charlotte Dreher,
  • Thomas Bogs,
  • Rainer Ganschow,
  • S. Tolga Yavuz
Max Reinsberg
Children's Hospital, University of Bonn

Corresponding Author:s4marein@uni-bonn.de

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Stephanie Siebert
Children's Hospital, University of Bonn
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Charlotte Dreher
Children's Hospital, University of Bonn
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Thomas Bogs
Children's Hospital, University of Bonn
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Rainer Ganschow
Children's Hospital, University of Bonn
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S. Tolga Yavuz
Children's Hospital, University of Bonn
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Abstract

Background: Methacholine challenge (MCC) is the most common method to detect airway hyperresponsiveness (AHR). Although MCC is accepted as safe diagnostic tool, it is time consuming and could be exhausting for patients. Thus, it might be helpful to identify predictive factors for AHR. We aimed to develop a diagnostic tool for predicting AHR in children with respiratory symptoms without obstructive pattern. Methods: Data from children who had undergone MCC were analyzed retrospectively. The demographic features of patients along with laboratory results were collected. Results: A total of 123 children with a median age of 10.5 years were enrolled. AHR was detected in 81 children (65.8%). The age of the children with AHR was significantly younger. The prevalences of aeroallergen sensitization, nocturnal cough, wheezing and a baseline forced expiratory flow at 75% of vital capacity (FEF75) <65% were significantly more frequent in children with AHR. Multivariate logistic regression analysis revealed age, ever wheezing, nocturnal cough, tree pollen allergy and FEF75<65% as independent predictors of the AHR. A weighted clinical risk score was developed (range, 0-75 points). At a cutoff point of 35 the presence of AHR is predicted with a specificity of 90.5% and a positive predictive value (PPV) of 91.5%. Conclusion: In children suspected of having asthma, but without an obstructive pattern, combining independent predictors, which can be easily obtained in clinical practice, in a novel prediction rule might be used to identify children with AHR.