A Machine Learning-Derived Risk Score Based on Dietary Nutrient Intake for Early Detection and Prognostic Prediction of Preserved Ratio Impaired Spirometry - PubMed
7 hours ago
- #machine-learning
- #PRISm
- #dietary-nutrients
- PRISm (Preserved Ratio Impaired Spirometry) is linked to higher risks of COPD, cardiovascular disease, and mortality.
- A machine learning model was developed using NHANES data (2007-2012) to predict PRISm risk based on dietary and demographic factors.
- The model achieved an AUC of 0.818, showing strong predictive ability for PRISm.
- High-risk individuals had significantly higher mortality rates and associations with chronic conditions like hypertension, diabetes, and COPD.
- Healthy lifestyle adherence reduced adverse outcomes in low-risk individuals but not in high-risk groups.
- The study proposes a non-invasive tool for early PRISm detection and personalized prevention strategies.