ArticlePsychological medicine2023
Predicting long-term outcome in anorexia nervosa: a machine learning analysis of brain structure at different stages of weight recovery.
Article in Psychological medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Neuroimaging and machine learning in eating disorders: a systematic review.Eating and weight disorders : EWD · 2025Pooled it
- Brain morphology in Anorexia Nervosa and its subtypes: A multi-cohort study of individual participant data.PLoS medicine · 2026Article
- Annual Research Review: Neural mechanisms of eating disorders in youth - from current theory and findings to future directions.Journal of child psychology and psychiatry, and allied disciplines · 2026Review
- Mapping the path to recovery: the intersection of cortical thickness reductions and serotonin transporter expression in anorexia nervosa.Molecular psychiatry · 2026Article
- Shared white matter connectome-based correlates of self-reproach, response failure, spatial planning, and resilience in patients with subthreshold depression: a graph theory approach.Scientific reports · 2026Article
- Multivariate patterns linking brain microstructure to temperament and behavior in adolescent eating disorders.Molecular psychiatry · 2025Article
- Examining the biological causes of eating disorders to inform treatment strategies.Nature reviews. Neuroscience · 2025Review
- Does restrictive anorexia nervosa impact brain aging? A machine learning approach to estimate age based on brain structure.Computers in biology and medicine · 2025Article
- Anthropometric, Nutritional, and Lifestyle Factors Involved in Predicting Food Addiction: An Agnostic Machine Learning Approach.Diseases (Basel, Switzerland) · 2025Article
- Predicting anorexia nervosa treatment efficacy: an explainable machine learning approach.Journal of eating disorders · 2025Article
- Weight gained during treatment predicts 6-month body mass index in a large sample of patients with anorexia nervosa using ensemble machine learning.The International journal of eating disorders · 2024Article
- Lower region-specific gray matter volume in females with atypical anorexia nervosa and anorexia nervosa.The International journal of eating disorders · 2024Article
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Authors and funding
9 authors.
Funding
Abstract
backgroundAnorexia nervosa (AN) is characterized by sizable, widespread gray matter (GM) reductions in the acutely underweight state. However, evidence for persistent alterations after weight-restoration has been surprisingly scarce despite high relapse rates, frequent transitions to other psychiatric disorders, and generally unfavorable outcome. While most studies investigated brain regions separately (univariate analysis), psychiatric disorders can be conceptualized as brain network disorders characterized by multivariate alterations with only subtle local effects. We tested for persistent multivariate structural brain alterations in weight-restored individuals with a history of AN, investigated their putative biological substrate and relation with 1-year treatment outcome.
methodsWe trained machine learning models on regional GM measures to classify healthy controls (HC) (
resultsPatients could be classified from HC when underweight (ROC-AUC = 0.90) but also after partial weight-restoration (ROC-AUC = 0.64). Alterations after partial weight-restoration were more pronounced in patients with worse outcome and were not detected in long-term weight-recovered individuals, i.e. those with favorable outcome. These alterations were more pronounced in regions with greater functional connectivity, not merely explained by body mass index, and even increases in cortical thickness were observed (insula, lateral orbitofrontal, temporal pole).
conclusionsAnalyzing persistent multivariate brain structural alterations after weight-restoration might help to develop personalized interventions after discharge from inpatient treatment.
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