The assessment, serial evaluation, and subsequent sequelae of acute kidney injury (ASSESS-AKI) study: design and methods

AS Go, CR Parikh, TA Ikizler, S Coca, ED Siew… - BMC nephrology, 2010 - Springer
Background The incidence of acute kidney injury (AKI) has been increasing over time and is
associated with a high risk of short-term death. Previous studies on hospital-acquired AKI …

[HTML][HTML] The severity of acute kidney injury predicts progression to chronic kidney disease

LS Chawla, RL Amdur, S Amodeo, PL Kimmel… - Kidney international, 2011 - Elsevier
Acute kidney injury (AKI) is associated with progression to advanced chronic kidney disease
(CKD). We tested whether patients who survive AKI and are at higher risk for CKD …

Machine learning for the prediction of acute kidney injury in critical care patients with acute cerebrovascular disease

X Zhang, S Chen, K Lai, Z Chen, J Wan, Y Xu - Renal Failure, 2022 - Taylor & Francis
Purpose Acute kidney injury (AKI) is a common complication and associated with a poor
clinical outcome. In this study, we developed and validated a model for predicting the risk of …

Nomogram to predict the risk of septic acute kidney injury in the first 24 h of admission: an analysis of intensive care unit data

F Deng, M Peng, J Li, Y Chen, B Zhang, S Zhao - Renal Failure, 2020 - Taylor & Francis
Background Acute kidney injury (AKI) is a significant cause of morbidity and mortality,
especially in sepsis patients. Early prediction of AKI can help physicians determine the …

[HTML][HTML] Risk factors and prognosis assessment for acute kidney injury: The 2020 consensus of the Taiwan AKI Task Force

JJ Chen, G Kuo, CC Hung, YF Lin, YC Chen… - Journal of the Formosan …, 2021 - Elsevier
Risk and prognostic factors for acute kidney injury (AKI) have been published in various
studies across various populations. We aimed to explore recent advancements in and …

Artificial intelligence and machine learning for predicting acute kidney injury in severely burned patients: a proof of concept

NK Tran, S Sen, TL Palmieri, K Lima, S Falwell… - Burns, 2019 - Elsevier
Background Burn critical care represents a high impact population that may benefit from
artificial intelligence and machine learning (ML). Acute kidney injury (AKI) recognition in …