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Nomogram to predict progression from preserved ratio impaired spirometry to chronic obstructive pulmonary disease
Nomogram to predict progression from preserved ratio impaired spirometry to chronic obstructive pulmonary disease
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Nomogram to predict progression from preserved ratio impaired spirometry to chronic obstructive pulmonary disease
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Nomogram to predict progression from preserved ratio impaired spirometry to chronic obstructive pulmonary disease
Nomogram to predict progression from preserved ratio impaired spirometry to chronic obstructive pulmonary disease

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Nomogram to predict progression from preserved ratio impaired spirometry to chronic obstructive pulmonary disease
Nomogram to predict progression from preserved ratio impaired spirometry to chronic obstructive pulmonary disease
Journal Article

Nomogram to predict progression from preserved ratio impaired spirometry to chronic obstructive pulmonary disease

2025
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Overview
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. We screened 188 patients whose lung function transitioned from PRISm to COPD and 173 patients with PRISm who remained stable over two years. After excluding 78 patients due to incomplete clinical or laboratory data, a total of 283 patients were included in the final analysis. These patients were randomly divided into a training cohort (227 patients) and a validation cohort (56 patients) at a 8:2 ratio. LASSO regression and multivariate logistic regression were used to identify factors influencing progression. Among the 283 patients, 134 progressed to COPD. The model developed using six variables showed good performance, with areas under the receiver operating characteristic (ROC) curves of 0.87 in the training cohort and 0.79 in the validation cohort. The model demonstrated excellent calibration and was clinically meaningful, as shown by decision curve analysis (DCA) and clinical impact curve (CIC). We developed China’s first prediction model for the progression of lung function from PRISm to COPD in a real-world population. This model is conducive to early identification of high-risk groups of pulmonary function deterioration, so as to provide timely intervention and delay the occurrence and progression of the disease.