Background: Early diagnosis and treatment of mental illnesses is hampered by the lack of reliable markers. This study used machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder (MDD), and alcohol use disorder (AUD).
Methods: Case-control samples (aged 18-25 years), including participants with Anorexia Nervosa (AN), Bulimia Nervosa (BN), MDD, AUD, and matched controls, were used for diagnostic classification.
Objective: To investigate fractures history in women with first episode anorexia nervosa (AN) (FE-AN: ≤ 3 years duration) and those with persistent AN (P-AN: ≥ 7 years), compared to healthy controls (HC).
Method: One hundred nineteen women (FE-AN = 49, P-AN = 46 and HC = 24) completed online questionnaires on eating disorders symptoms, their menstrual and their fracture history.
Results: Average illness duration was 1.