Background:Preserved Ratio Impaired Spirometry (PRISm) is a specific subtype of pre-chronic obstructive pulmonary disease (pre-COPD). People with PRISm are at risk of progression to chronic obstructive pulmonary disease (COPD). We developed a model to predict progression in subjects with PRISm.

Methods:We screened out 188 patients whose lung function transitioned from PRISm to COPD, 173 patients with PRISm who underwent at least two lung function tests and remained unchanged for two years in West China hospital. A total of 283 patients were finally included and they were randomly divided into training and validation groups at a 8:2 ratio. Logistic regression was used to create the model, which eventually emerges as a nomogram.

Results:A total of 283 patients were enrolled, 134 patients (47.35%) were eventually diagnosed with COPD. Through baseline feature comparison and logistic regression, we finally identified seven meaningful variables, including age, body mass index (BMI), FEV1 pred, FEV1/FVC, family history of respiratory disease, respiratory complications and immune related diseases. Accordingly, one nomogram was developed. The areas under the receiver operating characteristic (ROC) curves of this model were 0.89 and 0.86 in the training and validation cohorts, respectively. The model is well calibrated and decision curve analysis (DCA) , clinical impact curve (CIC) demonstrated that the predictive model was clinically meaningful.

Conclusion:We developed China?s first prediction model for the progression of lung function from PRISm to COPD in a real-world inpatient population.