Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup
Acute kidney injury (AKI), which is a common complication of acute illnesses, affects the
health of individuals in community, acute care and post-acute care settings. Although the …
health of individuals in community, acute care and post-acute care settings. Although the …
Artificial intelligence in acute kidney injury risk prediction
J Gameiro, T Branco, JA Lopes - Journal of clinical medicine, 2020 - mdpi.com
Acute kidney injury (AKI) is a frequent complication in hospitalized patients, which is
associated with worse short and long-term outcomes. It is crucial to develop methods to …
associated with worse short and long-term outcomes. It is crucial to develop methods to …
Cross-site transportability of an explainable artificial intelligence model for acute kidney injury prediction
Artificial intelligence (AI) has demonstrated promise in predicting acute kidney injury (AKI),
however, clinical adoption of these models requires interpretability and transportability. Non …
however, clinical adoption of these models requires interpretability and transportability. Non …
Internal and external validation of a machine learning risk score for acute kidney injury
Importance Acute kidney injury (AKI) is associated with increased morbidity and mortality in
hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and …
hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and …
Continuous and early prediction of future moderate and severe Acute Kidney Injury in critically ill patients: development and multi-centric, multi-national external …
Background Acute Kidney Injury (AKI) is a major complication in patients admitted to
Intensive Care Units (ICU), causing both clinical and economic burden on the healthcare …
Intensive Care Units (ICU), causing both clinical and economic burden on the healthcare …
A simple real-time model for predicting acute kidney injury in hospitalized patients in the US: a descriptive modeling study
M Simonov, U Ugwuowo, E Moreira, Y Yamamoto… - PLoS …, 2019 - journals.plos.org
Background Acute kidney injury (AKI) is an adverse event that carries significant morbidity.
Given that interventions after AKI occurrence have poor performance, there is substantial …
Given that interventions after AKI occurrence have poor performance, there is substantial …
Electronic alert systems for patients with acute kidney injury: a systematic review and meta-analysis
JJ Chen, TH Lee, MJ Chan, TY Tsai, PC Fan… - JAMA network …, 2024 - jamanetwork.com
Importance The acute kidney injury (AKI) electronic alert (e-alert) system was hypothesized
to improve the outcomes of AKI. However, its association with different patient outcomes and …
to improve the outcomes of AKI. However, its association with different patient outcomes and …
Optimizing the design and analysis of future AKI trials
AKI is a complex clinical syndrome associated with an increased risk of morbidity and
mortality, particularly in critically ill and perioperative patient populations. Most AKI clinical …
mortality, particularly in critically ill and perioperative patient populations. Most AKI clinical …
Performance of a standardized clinical assay for urinary C–C motif chemokine ligand 14 (CCL14) FOR persistent severe acute kidney injury
Background Clinical use of biomarkers requires the development of standardized assays
and establishment of cutoffs. Urinary CC motif chemokine ligand 14 (CCL14) has been …
and establishment of cutoffs. Urinary CC motif chemokine ligand 14 (CCL14) has been …
Early prediction of acute kidney injury in the emergency department with machine-learning methods applied to electronic health record data
Study objective Acute kidney injury occurs commonly and is a leading cause of prolonged
hospitalization, development and progression of chronic kidney disease, and death. Early …
hospitalization, development and progression of chronic kidney disease, and death. Early …