4.5 Article

The fraction of exhaled nitric oxide improves prediction of clinical allergic reaction to peanut challenge in children

期刊

CLINICAL AND EXPERIMENTAL ALLERGY
卷 44, 期 3, 页码 371-380

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WILEY
DOI: 10.1111/cea.12258

关键词

Ara h2; diagnostic algorithm; FeNO; objective screening; peanut allergy diagnosis

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BackgroundRetrospective studies of childhood peanut allergy demonstrate serum-specific IgE (IgE) levels against the peanut allergen Ara h2 may help predict a clinical reaction at food challenge. Fraction of exhaled nitric oxide (FeNO) is a non-invasive tool correlating to allergic airways inflammation and has been independently associated with increased food-specific IgE. ObjectiveTo assess the validity of serum-specific Ara h2 IgE measured prospectively to diagnose peanut allergy and explore the utility of FeNO as a non-invasive screening tool for childhood food challenge. MethodsWe recruited 53 participants from a cohort of consecutive children scheduled for an open-labelled peanut food challenge (OFC) by their paediatric allergist. Participants underwent skin prick test (SPT) measurement for sensitization to whole peanut extract, and serum was collected for Ara h2-specific IgE. FeNO was also measured in all cooperative children before the challenge. OFC and assessment of reaction were undertaken by clinicians blinded to test results. ResultsAra h2-specific IgE and FeNO each showed improved diagnostic accuracy when compared to SPT. Receiver operator characteristic curve analysis gave an area under the curve (AUC) for Ara h2 sIgE of 0.84 (95% CI, 0.72-0.96). The AUC for FeNO, 0.83 (95% CI, 0.71-0.95), was equivalent to that of Ara h2. Combined AUC for SPT, sIgE to Ara h2 and FeNO was 0.96 (95% CI 0.90-1.00). There was no correlation between FeNO and serum nitrite levels (rs=-0.13, P=0.6, n=18). Conclusion and clinical relevanceProspectively measured Ara h2-specific IgE improves diagnostic accuracy and reduces unsuccessful challenge to peanut. FeNO levels may provide improved diagnostic accuracy in a paediatric population undergoing OFC. The proposed FeNO-based diagnostic algorithm requires further validation studies.

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