A Prediction Model for Progression of preserved ratio impaired spirometry (PRISm) Based on Longitudinal Pulmonary Function Trajectories

Background Preserved ratio impaired spirometry (PRISm) represents a significant clinical phenotype. However, its lung function evolution exhibits marked heterogeneity, leading to substantial variability in the risk of progression to chronic obstructive pulmonary disease (COPD). This study aimed to analyze the longitudinal trajectories of lung function in patients with PRISm, identify independent risk factors for lung function decline, and develop and validate a clinical model for individualized risk prediction. Methods A total of 100 patients were followed prospectively for 3 years. Logistic regression was employed to analyze factors influencing the longitudinal lung function trajectories and to establish a corresponding clinical risk prediction model. Results Sex, smoking status, a COPD Assessment Test (CAT) score ≥ 20, and metabolic syndrome were identified as influencing factors for lung function decline in patients with PRISm. The area under the ROC curve for the risk prediction model was 0.84. Decision curve analysis demonstrated that intervention based on the nomogram model yielded superior net benefit within a threshold probability range of 0.04 to 0.93. Conclusion The risk prediction model, constructed based on influencing factors for lung function decline in a PRISm population, can identify high-risk PRISm patients and provide a reference for preventing their progression to COPD.