Association between impaired glucose metabolism and long-term prognosis at the time of diagnosis of depression: Impaired glucose metabolism as a promising biomarker proposed through a machine-learning approach

Association between impaired glucose metabolism and long-term prognosis at the time of diagnosis of depression: Impaired glucose metabolism as a promising biomarker proposed through a machine-learning approach

Abstract Background Predicting the course of depression is necessary for personalized treatment. Impaired glucose metabolism (IGM) was introduced as a promising depression biomarker, but no consensus was made. This study aimed to predict IGM at the time of depression diagnosis and examine the relati...

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Bibliographic Details
Main Authors: Dong Yun Lee, Yong Hyuk Cho, Myoungsuk Kim, Chang-Won Jeong, Jae Myung Cha, Geun Hui Won, Jai Sung Noh, Sang Joon Son, Rae Woong Park
Format: Article
Language:English
Published: Cambridge University Press 2023-01-01
Series:European Psychiatry
Subjects:
Biomarker
depression
impaired glucose metabolism
long-term prognosis
machine learning
Online Access:https://www.cambridge.org/core/product/identifier/S092493382300010X/type/journal_article

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