Machine learning models for predicting metabolic dysfunction-associated steatotic liver disease prevalence using basic demographic and clinical characteristics

Journal of Translational Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: March 28, 2025

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health concern that necessitates early screening and timely intervention to improve prognosis. The current diagnostic protocols for MASLD involve complex procedures in specialised medical centres. This study aimed explore the feasibility of utilising machine learning models accurately screen large populations based on combination essential demographic clinical characteristics. A total 10,007 outpatients who underwent transient elastography at First Affiliated Hospital Gannan Medical University were enrolled form derivation cohort. Using eight characteristics (age, educational level, height, weight, waist hip circumference, history hypertension diabetes), we built predictive (classified as none or mild: controlled attenuation parameter (CAP) ≤ 269 dB/m; moderate: 269-296 severe: CAP > 296 dB/m) employing 10 algorithms: logistic regression (LR), multilayer perceptron (MLP), extreme gradient boosting (XGBoost), bootstrap aggregating, decision tree, K-nearest neighbours, light machine, naive Bayes, random forest, support vector machine. These externally validated using National Health Nutrition Examination Survey (NHANES) 2017-2023 datasets. In hospital outpatient cohort, algorithms demonstrated robust capabilities. Notably, LR achieved highest accuracy (ACC) 0.711 test cohort 0.728 validation coupled with areas under receiver operating characteristic curve (AUC) values 0.798 0.806, respectively. Similarly, MLP XGBoost showed promising results, achieving an ACC 0.735 registering AUC 0.798. External NHANES datasets yielded consistent (0.831), (0.823), (0.784) performing robustly. constructed can general population. approach significantly enhances feasibility, accessibility, compliance provides effective tool large-scale assessments strategies.

Language: Английский

Impact of Metabolic Dysfunction-Associated Steatotic Liver Disease on Cardiovascular Structure, Function, and the Risk of Heart Failure

Canadian Journal of Cardiology, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский