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Erythropoiesis stimulating agent recommendation model using recurrent neural networks for patient with kidney failure with replacement therapy

 Hae-Ryong Yun  ;  Gyubok Lee  ;  Myeong Jun Jeon  ;  Hyung Woo Kim  ;  Young Su Joo  ;  Hyoungnae Kim  ;  Tae Ik Chang  ;  Jung Tak Park  ;  Seung Hyeok Han  ;  Shin-Wook Kang  ;  Wooju Kim  ;  Tae-Hyun Yoo 
 COMPUTERS IN BIOLOGY AND MEDICINE, Vol.137 : 104718, 2021-10 
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Anemia ; Erythropoiesis stimulating agent ; Kidney failure with replacement therapy ; Recurrent neural networks
In patients with kidney failure with replacement therapy (KFRT), optimizing anemia management in these patients is a challenging problem because of the complexities of the underlying diseases and heterogeneous responses to erythropoiesis-stimulating agents (ESAs). Therefore, we propose a ESA dose recommendation model based on sequential awareness neural networks. Data from 466 KFRT patients (12,907 dialysis sessions) in seven tertiary-care general hospitals were included in the experiment. First, a Hb prediction model was developed to simulate longitudinal heterogeneous ESA and Hb interactions. Based on the prediction model as a prospective study simulator, we built an ESA dose recommendation model to predict the required amount of ESA dose to reach a target hemoglobin level after 30 days. Each model's performance was evaluated in the mean absolute error (MAE). The MAEs presenting the best results of the prediction and recommendation model were 0.59 (95% confidence interval: 0.56-0.62) g/dL and 43.2 μg (ESAs dose), respectively. Compared to the results in the real-world clinical data, the recommendation model achieved a reduction of ESA dose (Algorithm: 140 vs. Human: 150 μg/month, P < 0.001), a more stable monthly Hb difference (Algorithm: 0.6 vs. Human: 0.8 g/dL, P < 0.001), and an improved target Hb success rate (Algorithm: 79.5% vs. Human: 62.9% for previous month's Hb < 10.0 g/dL; Algorithm: 95.7% vs. Human:73.0% for previous month's Hb 10.0-12.0 g/dL). We developed an ESA dose recommendation model for optimizing anemia management in patients with KFRT and showed its potential effectiveness in a simulated prospective study.
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1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
Yonsei Authors
Kang, Shin Wook(강신욱) ORCID logo https://orcid.org/0000-0002-5677-4756
Kim, Hyung Woo(김형우) ORCID logo https://orcid.org/0000-0002-6305-452X
Park, Jung Tak(박정탁) ORCID logo https://orcid.org/0000-0002-2325-8982
Yoo, Tae Hyun(유태현) ORCID logo https://orcid.org/0000-0002-9183-4507
Yun, Hae Ryong(윤해룡) ORCID logo https://orcid.org/0000-0002-7038-0251
Joo, Young Su(주영수) ORCID logo https://orcid.org/0000-0002-7890-0928
Han, Seung Hyeok(한승혁) ORCID logo https://orcid.org/0000-0001-7923-5635
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