AIMC Topic: Acute Kidney Injury

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Global research trends and collaborations in acute kidney injury (AKI) and sepsis: a bibliometric analysis (2004-2024).

Renal failure
BACKGROUND: Acute kidney injury (AKI) and sepsis are critical clinical conditions associated with high morbidity and mortality. Despite growing research interest, there remains a need for a comprehensive analysis of global research trends in this fie...

Timing of kidney replacement therapy in critically ill patients: A call to shift the paradigm in the era of artificial intelligence.

Science progress
Acute kidney injury (AKI) is a common condition in intensive care units (ICUs) and is associated with high mortality rates, particularly when kidney replacement therapy (KRT) becomes necessary. The optimal timing for initiating KRT remains a subject ...

Association of acute kidney injury with 1-year mortality in granulomatosis with polyangiitis patients: a cohort study using mediation analyses and machine learning.

Rheumatology international
To investigate the correlation between acute kidney injury (AKI) and 1-year mortality in patients with granulomatosis with polyangiitis (GPA). Clinical data for GPA patients were extracted from the MIMIC-IV (version 3.0) database. Logistic and Cox re...

A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: Postoperative acute kidney injury (AKI) is a significant risk associated with surgeries under general anesthesia, often leading to increased mortality and morbidity. Existing predictive models for postoperative AKI are usually limited to ...

Machine learning for risk prediction of acute kidney injury in patients with diabetes mellitus combined with heart failure during hospitalization.

Scientific reports
This study aimed to develop a machine learning (ML) model for predicting the risk of acute kidney injury (AKI) in diabetic patients with heart failure (HF) during hospitalization. Using data from 1,457 patients in the MIMIC-IV database, the study ide...

Validation of a cancer population derived AKI machine learning algorithm in a general critical care scenario.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PURPOSE: Acute Kidney Injury (AKI) is the sudden onset of kidney damage. This damage usually comes without warning and can lead to increased mortality and inpatient costs and is of particular significance to patients undergoing cancer treatment. In p...

Construction of a machine learning-based interpretable prediction model for acute kidney injury in hospitalized patients.

Scientific reports
In this observational study, we used data from 59,936 hospitalized adults to construct a model. For the models constructed with all 53 variables, all five models achieved acceptable performance with the validation cohort, with the extreme gradient bo...

Machine Learning to Assist in Managing Acute Kidney Injury in General Wards: Multicenter Retrospective Study.

Journal of medical Internet research
BACKGROUND: Most artificial intelligence-based research on acute kidney injury (AKI) prediction has focused on intensive care unit settings, limiting their generalizability to general wards. The lack of standardized AKI definitions and reliance on in...