PMID- 33995200
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230916
IS  - 1664-1078 (Print)
IS  - 1664-1078 (Electronic)
IS  - 1664-1078 (Linking)
VI  - 12
DP  - 2021
TI  - Roles of Anxiety and Depression in Predicting Cardiovascular Disease Among 
      Patients With Type 2 Diabetes Mellitus: A Machine Learning Approach.
PG  - 645418
LID - 10.3389/fpsyg.2021.645418 [doi]
LID - 645418
AB  - Cardiovascular disease (CVD) is a major complication of type 2 diabetes mellitus 
      (T2DM). In addition to traditional risk factors, psychological determinants play 
      an important role in CVD risk. This study applied Deep Neural Network (DNN) to 
      develop a CVD risk prediction model and explored the bio-psycho-social 
      contributors to the CVD risk among patients with T2DM. From 2017 to 2020, 834 
      patients with T2DM were recruited from the Department of Endocrinology, 
      Affiliated Hospital of Harbin Medical University, China. In this cross-sectional 
      study, the patients' bio-psycho-social information was collected through clinical 
      examinations and questionnaires. The dataset was randomly split into a 75% train 
      set and a 25% test set. DNN was implemented at the best performance on the train 
      set and applied on the test set. The receiver operating characteristic curve 
      (ROC) analysis was used to evaluate the model performance. Of participants, 272 
      (32.6%) were diagnosed with CVD. The developed ensemble model for CVD risk 
      achieved an area under curve score of 0.91, accuracy of 87.50%, sensitivity of 
      88.06%, and specificity of 87.23%. Among patients with T2DM, the top five 
      predictors in the CVD risk model were body mass index, anxiety, depression, total 
      cholesterol, and systolic blood pressure. In summary, machine learning models can 
      provide an automated identification mechanism for patients at CVD risk. 
      Integrated treatment measures should be taken in health management, including 
      clinical care, mental health improvement, and health behavior promotion.
CI  - Copyright (c) 2021 Chu, Chen, Yang, Qiu, Qiao, Song, Zhao, Zhou, Zhang, Mehmood, 
      Pan and Yang.
FAU - Chu, Haiyun
AU  - Chu H
AD  - Department of Medical Psychology, Harbin Medical University, Harbin, China.
FAU - Chen, Lu
AU  - Chen L
AD  - Department of Endocrinology, Peking Union Medical College Hospital, Beijing, 
      China.
FAU - Yang, Xiuxian
AU  - Yang X
AD  - Department of Medical Psychology, Harbin Medical University, Harbin, China.
FAU - Qiu, Xiaohui
AU  - Qiu X
AD  - Department of Medical Psychology, Harbin Medical University, Harbin, China.
FAU - Qiao, Zhengxue
AU  - Qiao Z
AD  - Department of Medical Psychology, Harbin Medical University, Harbin, China.
FAU - Song, Xuejia
AU  - Song X
AD  - Department of Medical Psychology, Harbin Medical University, Harbin, China.
FAU - Zhao, Erying
AU  - Zhao E
AD  - Department of Medical Psychology, Harbin Medical University, Harbin, China.
FAU - Zhou, Jiawei
AU  - Zhou J
AD  - Department of Medical Psychology, Harbin Medical University, Harbin, China.
FAU - Zhang, Wenxin
AU  - Zhang W
AD  - Department of Medical Psychology, Harbin Medical University, Harbin, China.
FAU - Mehmood, Anam
AU  - Mehmood A
AD  - Department of Medical Psychology, Harbin Medical University, Harbin, China.
FAU - Pan, Hui
AU  - Pan H
AD  - Department of Endocrinology, Peking Union Medical College Hospital, Beijing, 
      China.
FAU - Yang, Yanjie
AU  - Yang Y
AD  - Department of Medical Psychology, Harbin Medical University, Harbin, China.
LA  - eng
PT  - Journal Article
DEP - 20210428
PL  - Switzerland
TA  - Front Psychol
JT  - Frontiers in psychology
JID - 101550902
PMC - PMC8113686
OTO - NOTNLM
OT  - China
OT  - bio-psycho-social factors
OT  - cardiovascular disease
OT  - machine learning
OT  - type 2 diabetes mellitus
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a potential 
      conflict of interest.
EDAT- 2021/05/18 06:00
MHDA- 2021/05/18 06:01
PMCR- 2021/04/28
CRDT- 2021/05/17 06:03
PHST- 2020/12/23 00:00 [received]
PHST- 2021/03/17 00:00 [accepted]
PHST- 2021/05/17 06:03 [entrez]
PHST- 2021/05/18 06:00 [pubmed]
PHST- 2021/05/18 06:01 [medline]
PHST- 2021/04/28 00:00 [pmc-release]
AID - 10.3389/fpsyg.2021.645418 [doi]
PST - epublish
SO  - Front Psychol. 2021 Apr 28;12:645418. doi: 10.3389/fpsyg.2021.645418. eCollection 
      2021.