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Deep Learning for Intradialytic Hypotension Prediction in Hemodialysis Patients

Authors :
Kuo-Chuan Wu
Sin-Hua Moi
Cheng-Hong Yang
Jin-Bor Chen
Li-Yeh Chuang
Source :
IEEE Access, Vol 8, Pp 82382-82390 (2020)
Publication Year :
2020
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2020.

Abstract

Intradialytic hypotension is a common problem during hemodialysis treatment. Despite several clinical variables have been authenticated for associations during dialysis session, the interaction effects between variables has not yet been presented. Our study aimed to investigate clinical factors associated with intradialytic hypotension by deep learning. A total of 279 participants with 780 hemodialysis sessions on an outpatient in a hospital-facilitated hemodialysis center were enrolled in March 2018. Associations between clinical factors and intradialytic hypotension were determined using linear regression method and deep neural network. A full-adjusted model indicated that intradialytic hypotension is positively associated with body mass index (Beta = 0.17, p = 0.028), hypertension comorbidity (Beta = 0.17, p = 0.008), and ultrafiltration amount (Beta = 0.31, p

Details

ISSN :
21693536
Volume :
8
Database :
OpenAIRE
Journal :
IEEE Access
Accession number :
edsair.doi.dedup.....f6ca6cc22dc321f2f41d5388529a27a5