Identifying Suicidal Ideation Among Chinese Patients with Major Depressive Disorder: Evidence from a Real-World Hospital-Based Study in China

Fenfen Ge,1,* Jingwen Jiang,2,* Yue Wang,1 Cui Yuan,1 Wei Zhang1 1Mental Health Center of West China Hospital, Sichuan University, Chengdu, Sichuan 610041, People’s Republic of China; 2West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041,...

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Autores principales:	Ge F, Jiang J, Wang Y, Yuan C, Zhang W
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2020
Materias:	depression suicide ideation real-word machine learning Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Neurology. Diseases of the nervous system RC346-429
Acceso en línea:	https://doaj.org/article/2f2a2ca056804313b1f832d580c275fd
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spelling	oai:doaj.org-article:2f2a2ca056804313b1f832d580c275fd2021-12-02T09:11:31ZIdentifying Suicidal Ideation Among Chinese Patients with Major Depressive Disorder: Evidence from a Real-World Hospital-Based Study in China1178-2021https://doaj.org/article/2f2a2ca056804313b1f832d580c275fd2020-03-01T00:00:00Zhttps://www.dovepress.com/identifying-suicidal-ideation-among-chinese-patients-with-major-depres-peer-reviewed-article-NDThttps://doaj.org/toc/1178-2021Fenfen Ge,1,* Jingwen Jiang,2,* Yue Wang,1 Cui Yuan,1 Wei Zhang1 1Mental Health Center of West China Hospital, Sichuan University, Chengdu, Sichuan 610041, People’s Republic of China; 2West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wei ZhangMental Health Center of West China Hospital, Sichuan University, Chengdu, Sichuan 610041, People’s Republic of ChinaTel +86 18980601010Email weizhanghx@163.comBackground: A growing body of research suggests that major depressive disorder (MDD) is one of the most common psychiatric conditions associated with suicide ideation (SI). However, how a combination of easily accessible variables built a utility clinically model to estimate the probability of an individual patient with SI via machine learning is limited.Methods: We used the electronic medical record database from a hospital located in western China. A total of 1916 Chinese patients with MDD were included. Easily accessible data (demographic, clinical, and biological variables) were collected at admission (on the first day of admission) and were used to distinguish SI with MDD from non-SI using a machine learning algorithm (neural network).Results: The neural network algorithm distinguished 1356 out of 1916 patients translating into 70.08% accuracy (70.68% sensitivity and 67.09% specificity) and an area under the curve (AUC) of 0.76. The most relevant predictor variables in identifying SI from non-SI included free thyroxine (FT4), the total scores of Hamilton Depression Scale (HAMD), vocational status, and free triiodothyronine (FT3).Conclusion: Risk for SI among patients with MDD can be identified at an individual subject level by integrating demographic, clinical, and biological variables as possible as early during hospitalization (at admission).Keywords: depression, suicide ideation, real-world, machine learningGe FJiang JWang YYuan CZhang WDove Medical Pressarticledepressionsuicide ideationreal-wordmachine learningNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571Neurology. Diseases of the nervous systemRC346-429ENNeuropsychiatric Disease and Treatment, Vol Volume 16, Pp 665-672 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	depression suicide ideation real-word machine learning Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Neurology. Diseases of the nervous system RC346-429
spellingShingle	depression suicide ideation real-word machine learning Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Neurology. Diseases of the nervous system RC346-429 Ge F Jiang J Wang Y Yuan C Zhang W Identifying Suicidal Ideation Among Chinese Patients with Major Depressive Disorder: Evidence from a Real-World Hospital-Based Study in China
description	Fenfen Ge,1,* Jingwen Jiang,2,* Yue Wang,1 Cui Yuan,1 Wei Zhang1 1Mental Health Center of West China Hospital, Sichuan University, Chengdu, Sichuan 610041, People’s Republic of China; 2West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wei ZhangMental Health Center of West China Hospital, Sichuan University, Chengdu, Sichuan 610041, People’s Republic of ChinaTel +86 18980601010Email weizhanghx@163.comBackground: A growing body of research suggests that major depressive disorder (MDD) is one of the most common psychiatric conditions associated with suicide ideation (SI). However, how a combination of easily accessible variables built a utility clinically model to estimate the probability of an individual patient with SI via machine learning is limited.Methods: We used the electronic medical record database from a hospital located in western China. A total of 1916 Chinese patients with MDD were included. Easily accessible data (demographic, clinical, and biological variables) were collected at admission (on the first day of admission) and were used to distinguish SI with MDD from non-SI using a machine learning algorithm (neural network).Results: The neural network algorithm distinguished 1356 out of 1916 patients translating into 70.08% accuracy (70.68% sensitivity and 67.09% specificity) and an area under the curve (AUC) of 0.76. The most relevant predictor variables in identifying SI from non-SI included free thyroxine (FT4), the total scores of Hamilton Depression Scale (HAMD), vocational status, and free triiodothyronine (FT3).Conclusion: Risk for SI among patients with MDD can be identified at an individual subject level by integrating demographic, clinical, and biological variables as possible as early during hospitalization (at admission).Keywords: depression, suicide ideation, real-world, machine learning
format	article
author	Ge F Jiang J Wang Y Yuan C Zhang W
author_facet	Ge F Jiang J Wang Y Yuan C Zhang W
author_sort	Ge F
title	Identifying Suicidal Ideation Among Chinese Patients with Major Depressive Disorder: Evidence from a Real-World Hospital-Based Study in China
title_short	Identifying Suicidal Ideation Among Chinese Patients with Major Depressive Disorder: Evidence from a Real-World Hospital-Based Study in China
title_full	Identifying Suicidal Ideation Among Chinese Patients with Major Depressive Disorder: Evidence from a Real-World Hospital-Based Study in China
title_fullStr	Identifying Suicidal Ideation Among Chinese Patients with Major Depressive Disorder: Evidence from a Real-World Hospital-Based Study in China
title_full_unstemmed	Identifying Suicidal Ideation Among Chinese Patients with Major Depressive Disorder: Evidence from a Real-World Hospital-Based Study in China
title_sort	identifying suicidal ideation among chinese patients with major depressive disorder: evidence from a real-world hospital-based study in china
publisher	Dove Medical Press
publishDate	2020
url	https://doaj.org/article/2f2a2ca056804313b1f832d580c275fd
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Identifying Suicidal Ideation Among Chinese Patients with Major Depressive Disorder: Evidence from a Real-World Hospital-Based Study in China

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