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.

在接受替代疗法 (KFRT) 的肾功能衰竭患者中，由于潜在疾病的复杂性和对红细胞生成刺激剂 (ESAs) 的异质反应，优化这些患者的贫血管理是一个具有挑战性的问题。因此，我们提出了一种基于序列意识神经网络的 ESA 剂量推荐模型。来自 7 家三级保健综合医院的 466 名 KFRT 患者（12,907 次透析）的数据被纳入实验。首先，开发了 Hb 预测模型来模拟纵向异质 ESA 和 Hb 相互作用。基于作为前瞻性研究模拟器的预测模型，我们建立了一个 ESA 剂量推荐模型，以预测 30 天后达到目标血红蛋白水平所需的 ESA 剂量。每个型号' s 性能以平均绝对误差 (MAE) 进行评估。呈现预测和推荐模型最佳结果的 MAE 分别为 0.59（95% 置信区间：0.56–0.62）g/dL 和 43.2 μg（ESAs 剂量）。与真实世界临床数据中的结果相比，推荐模型实现了 ESA 剂量的降低（算法：140 与人类：150 μg/月，P < 0.001），更稳定的月 Hb 差异（算法：0.6 与. 人类：0.8 g/dL，P < 0.001），并且提高了目标 Hb 成功率（算法：79.5% 与人类：62.9% 上个月的 Hb < 10.0 g/dL；算法：95.7% 与人类：73.0 % 为上个月的 Hb 10.0–12.0 g/dL）。