Li Bo, Huo Yan, Zhang Kun, Chang Limin, Zhang Haohua, Wang Xinrui, Li Leying, Hu Zhenjie
Intensive Care Unit, Hebei Medical University Fourth Affiliated Hospital and Hebei Provincial Tumor Hospital, Shijiazhuang, China.
Front Med (Lausanne). 2022 Aug 18;9:853989. doi: 10.3389/fmed.2022.853989. eCollection 2022.
This study aimed to develop and validate a set of practical predictive tools that reliably estimate the 28-day prognosis of acute kidney injury patients undergoing continuous renal replacement therapy.
The clinical data of acute kidney injury patients undergoing continuous renal replacement therapy were extracted from the Medical Information Mart for Intensive Care IV database with structured query language and used as the development cohort. An all-subset regression was used for the model screening. Predictive models were constructed a logistic regression, and external validation of the models was performed using independent external data.
Clinical prediction models were developed with clinical data from 1,148 patients and validated with data from 121 patients. The predictive model based on seven predictors (age, vasopressor use, red cell volume distribution width, lactate, white blood cell count, platelet count, and phosphate) exhibited good predictive performance, as indicated by a C-index of 0.812 in the development cohort, 0.811 in the internal validation cohort and 0.768 in the external validation cohort.
The model reliably predicted the 28-day prognosis of acute kidney injury patients undergoing continuous renal replacement therapy. The predictive items are readily available, and the web-based prognostic calculator (https://libo220284.shinyapps.io/DynNomapp/) can be used as an adjunctive tool to support the management of patients.
本研究旨在开发并验证一套实用的预测工具，以可靠地估计接受持续肾脏替代治疗的急性肾损伤患者的28天预后。
采用结构化查询语言从重症监护医学信息数据库IV中提取接受持续肾脏替代治疗的急性肾损伤患者的临床数据，并将其用作开发队列。采用全子集回归进行模型筛选。构建逻辑回归预测模型，并使用独立的外部数据对模型进行外部验证。
利用1148例患者的临床数据开发了临床预测模型，并使用121例患者的数据进行了验证。基于七个预测因子（年龄、血管升压药使用情况、红细胞体积分布宽度、乳酸、白细胞计数、血小板计数和磷酸盐）的预测模型表现出良好的预测性能，开发队列中的C指数为0.812，内部验证队列中为0.811，外部验证队列中为0.768。
该模型可靠地预测了接受持续肾脏替代治疗的急性肾损伤患者的28天预后。预测指标易于获得，基于网络的预后计算器（https://libo220284.shinyapps.io/DynNomapp/）可作为辅助工具支持患者管理。
