AI Article Synopsis

  • Some patients with asthma have normal spirometry, making it hard to diagnose without additional tests like bronchial challenge testing (BCT).
  • The study aimed to identify clinical predictors for asthma in symptomatic adults and develop a tool to help doctors determine who needs BCT.
  • Among 132 participants with respiratory symptoms, 26% were diagnosed with asthma, with key predictors being experiences like coughing or wheezing during exercise and certain spirometry results; a nomogram was created to assist clinicians in identifying these patients.

Article Abstract

Background: Some patients with asthma demonstrate normal spirometry and remain undiagnosed without further testing.

Objective: To determine clinical predictors of asthma in symptomatic adults with normal spirometry, and to generate a tool to help clinicians decide who should undergo bronchial challenge testing (BCT).

Methods: Using random-digit dialling and population-based case-finding, we recruited adults from the community with respiratory symptoms and no previous history of diagnosed lung disease. Participants with normal pre- and post-bronchodilator spirometry subsequently underwent BCT. Asthma was diagnosed in those with symptoms and a methacholine provocative concentration (PC) of < 8 mg/ml. Sputum and blood eosinophils, and exhaled nitric oxide were measured. Univariate analyses identified potentially predictive variables, which were then used to construct a multivariable logistic regression model to predict asthma. Model sensitivity, specificity, and area under the receiver operating curve (AUC) were calculated.

Results: Of 132 symptomatic individuals with normal spirometry, 34 (26%) had asthma. Of those ultimately diagnosed with asthma, 33 (97%) answered 'yes' to a question asking whether they experienced cough, chest tightness or wheezing provoked by exercise or cold air. Other univariate predictors of asthma included female sex, pre-bronchodilator FEV1 percentage predicted, and percent positive change in FEV1 post bronchodilator. A multivariable model containing these predictive variables yielded an AUC of 0.82 (95% CI: 0.72-0.91), a sensitivity of 82%, and a specificity of 66%. The model was used to construct a nomogram to advise clinicians which patients should be prioritized for BCT.

Conclusions: Four readily available patient characteristics demonstrated a high sensitivity and AUC for predicting undiagnosed asthma in symptomatic adults with normal pre- and post-bronchodilator spirometry. These characteristics can potentially help clinicians to decide which individuals with normal spirometry should be investigated with bronchial challenge testing. However, further prospective validation of our decision tool is required.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10709915PMC
http://dx.doi.org/10.1186/s12890-023-02806-9DOI Listing

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