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Development and Internal Evaluation of a Clinical-Physiological Model for Predicting Methacholine-Defined Airway
Jiangjiao Qin1,2, Sha Liu1,2, Ying Lin1,2
1Department of Pulmonary Function, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Insights
This study developed a non-invasive nomogram to predict airway hyperresponsiveness (AHR) in young children, aiding early asthma diagnosis. The tool uses clinical factors and FeNO levels for better prediction in suspected asthma cases.
Area of Science:
- Pediatric Pulmonology
- Asthma Diagnostics
- Respiratory Medicine
Background:
- Assessing airway hyperresponsiveness (AHR) in children 0-3 years is vital for early asthma diagnosis.
- The methacholine challenge test (MCT) is challenging due to safety and complexity in this age group.
Purpose of the Study:
- Develop and evaluate a non-invasive nomogram to predict methacholine-defined AHR in children aged 0-3 years with suspected asthma.
- Provide an alternative to MCT for AHR assessment in young children.
Main Methods:
- Retrospective cohort study of children aged 0-3 years with suspected asthma.
- Collected data on pulmonary function, FeNO, MCT, symptoms, and atopy.
- Used multivariable logistic regression to identify predictors and build a predictive nomogram.
Main Results:
- Identified seven predictors: family history of asthma, wheeze, allergy, rhinitis, FeNO, age, and TPTEF/TE.
- The nomogram achieved an AUC of 0.81 (training) and 0.76 (evaluation).
- Family history of asthma, wheeze, and FeNO were the most influential predictors.
Conclusions:
- A clinical-physiological nomogram was developed to predict methacholine-defined AHR in children aged 0-3 years.
- This nomogram can serve as an adjunctive tool in tertiary care to identify children likely to have AHR.
Purpose:
Assessing airway hyperresponsiveness (AHR) in children aged 0-3 years is crucial for early asthma diagnosis but is clinically challenging due to the safety risks and technical complexity of the methacholine challenge test (MCT). This study aimed to develop and internally evaluate a non-invasive, multidimensional nomogram to predict current methacholine-defined AHR in children aged 0-3 years with suspected asthma.
Patients And Methods:
We conducted a retrospective cohort study of children aged 0-3 years with suspected asthma who underwent same-day tidal breathing pulmonary function testing, fractional exhaled nitric oxide (FeNO) measurement, and MCT. Clinical symptoms and atopic history were extracted from electronic medical records. Multivariable logistic regression was used to identify independent predictors of AHR. The model was internally evaluated using a single 70/30 random split into training and evaluation cohorts. Model performance was assessed by discrimination, calibration, and decision curve analysis and compared with machine-learning approaches.
Results:
Seven independent predictors were identified: family history of asthma (OR = 3.90), presence of wheeze (OR = 3.85), history of allergy (OR = 2.34), history of rhinitis (OR = 1.69), FeNO (OR = 1.03), age (OR = 0.96), and TPTEF/TE (OR = 0.97). The model achieved an AUC of 0.81 (95% CI: 0.77-0.85) in the training cohort and 0.76 (95% CI: 0.69-0.84) in the evaluation cohort. At the optimal cutoff, the PPV and NPV were 0.89 and 0.39, respectively, in the evaluation cohort. SHAP analysis identified family history of asthma, wheeze, and FeNO as the most influential predictors.
Conclusion:
We developed a clinical-physiological nomogram for predicting methacholine-defined AHR in children aged 0-3 years. It serves as an adjunctive tool in tertiary care to identify patients with a high probability of AHR.
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