A Machine-Learning-Algorithm-Based Prediction Model for Psychotic Symptoms in Patients with Depressive Disorder

Author:

Kim Kiwon,Ryu Je il,Lee Bong Ju,Na EuihyeonORCID,Xiang Yu-Tao,Kanba Shigenobu,Kato Takahiro A.,Chong Mian-Yoon,Lin Shih-Ku,Avasthi Ajit,Grover Sandeep,Kallivayalil Roy Abraham,Pariwatcharakul PornjiraORCID,Chee Kok YoonORCID,Tanra Andi J.,Tan Chay-Hoon,Sim KangORCID,Sartorius Norman,Shinfuku Naotaka,Park Yong Chon,Park Seon-CheolORCID

Abstract

Psychotic symptoms are rarely concurrent with the clinical manifestations of depression. Additionally, whether psychotic major depression is a subtype of major depression or a clinical syndrome distinct from non-psychotic major depression remains controversial. Using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, we developed a machine-learning-algorithm-based prediction model for concurrent psychotic symptoms in patients with depressive disorders. The advantages of machine learning algorithms include the easy identification of trends and patterns, handling of multi-dimensional and multi-faceted data, and wide application. Among 1171 patients with depressive disorders, those with psychotic symptoms were characterized by significantly higher rates of depressed mood, loss of interest and enjoyment, reduced energy and diminished activity, reduced self-esteem and self-confidence, ideas of guilt and unworthiness, psychomotor agitation or retardation, disturbed sleep, diminished appetite, and greater proportions of moderate and severe degrees of depression compared to patients without psychotic symptoms. The area under the curve was 0.823. The overall accuracy was 0.931 (95% confidence interval: 0.897–0.956). Severe depression (degree of depression) was the most important variable in the prediction model, followed by diminished appetite, subthreshold (degree of depression), ideas or acts of self-harm or suicide, outpatient status, age, psychomotor retardation or agitation, and others. In conclusion, the machine-learning-based model predicted concurrent psychotic symptoms in patients with major depression in connection with the “severity psychosis” hypothesis.

Funder

research fund of Hanyang University

Publisher

MDPI AG

Subject

Medicine (miscellaneous)

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