Predicting long-term outcome in anorexia nervosa: a machine learning analysis of brain structure at different stages of weight recovery.

ABSTRACT:

Background

Anorexia 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.

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SUBMITTER: Arold D 

PROVIDER: S-EPMC10758339 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature