A Prediction Model for Assessing Prognosis in Critically Ill Patients with Sepsis-associated Acute Kidney Injury-Reference-Cited by-同舟云学术

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A Prediction Model for Assessing Prognosis in Critically Ill Patients with Sepsis-associated Acute Kidney Injury

Published:2021-03-03 Issue:4 Volume:56 Page:564-572
ISSN:1073-2322
Container-title:Shock
language:en
Short-container-title:

Author:

Hu Hongbin,Li Lulan,Zhang Yuan,Sha Tong,Huang Qiaobing,Guo Xiaohua,An Shengli,Chen Zhongqing,Zeng Zhenhua

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Critical Care and Intensive Care Medicine,Emergency Medicine

Reference37 articles.

1. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3);Singer;JAMA,2016

2. Clinical characteristics of patients developing ARF due to sepsis/systemic inflammatory response syndrome: results of a prospective study;Yegenaga;Am J Kidney Dis,2004

3. Acute renal failure in critically ill patients: a multinational, multicenter study;Uchino;JAMA,2005

4. Acute kidney injury in septic shock: clinical outcomes and impact of duration of hypotension prior to initiation of antimicrobial therapy;Bagshaw;Intensive Care Med,2009

5. Septic acute kidney injury in critically ill patients: clinical characteristics and outcomes;Bagshaw;Clin J Am Soc Nephrol,2007

Cited by 26 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms;Annals of Medicine;2024-08-19

2. Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review;Renal Failure;2024-07-31

3. Artificial intelligence and machine learning’s role in sepsis-associated acute kidney injury;Kidney Research and Clinical Practice;2024-07-31

4. Using machine learning to predict the risk of short-term and long-term death in acute kidney injury patients after commencing CRRT;BMC Nephrology;2024-07-30

5. Machine learning for the prediction of 1-year mortality in patients with sepsis-associated acute kidney injury;BMC Medical Informatics and Decision Making;2024-07-25

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