AIMC Topic: Continuous Renal Replacement Therapy

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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
BACKGROUND: To construct and evaluate a predictive model for in-hospital mortality among critically ill patients with acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT), based on nine machine learning (ML) algorithm.

Coagulation Risk Predicting in Anticoagulant-Free Continuous Renal Replacement Therapy.

Blood purification
INTRODUCTION: Continuous renal replacement therapy (CRRT) is a prolonged continuous extracorporeal blood purification therapy to replace impaired renal function. Typically, CRRT therapy requires routine anticoagulation, but for patients at risk of bl...

Using machine learning to predict the risk of short-term and long-term death in acute kidney injury patients after commencing CRRT.

BMC nephrology
BACKGROUND: The mortality rate and prognosis of short-term and long-term acute kidney injury (AKI) patients who undergo continuous renal replacement therapy (CRRT) are different. Setting up risk stratification tools for both short-term and long-term ...

Data-driven prediction of continuous renal replacement therapy survival.

Nature communications
Continuous renal replacement therapy (CRRT) is a form of dialysis prescribed to severely ill patients who cannot tolerate regular hemodialysis. However, as the patients are typically very ill to begin with, there is always uncertainty whether they wi...

Machine Learning-Aided Decision-Making Model for the Discontinuation of Continuous Renal Replacement Therapy.

Blood purification
INTRODUCTION: Continuous renal replacement therapy (CRRT) is a primary form of renal support for patients with acute kidney injury in an intensive care unit. Making an accurate decision of discontinuation is crucial for the prognosis of patients. Pre...

Machine learning in risk prediction of continuous renal replacement therapy after coronary artery bypass grafting surgery in patients.

Clinical and experimental nephrology
OBJECTIVES: This study aimed to develop machine learning models for risk prediction of continuous renal replacement therapy (CRRT) following coronary artery bypass grafting (CABG) surgery in intensive care unit (ICU) patients.

Predicting outcomes of continuous renal replacement therapy using body composition monitoring: a deep-learning approach.

Scientific reports
Fluid balance is a critical prognostic factor for patients with severe acute kidney injury (AKI) requiring continuous renal replacement therapy (CRRT). This study evaluated whether repeated fluid balance monitoring could improve prognosis in this cli...

Machine learning model to predict hypotension after starting continuous renal replacement therapy.

Scientific reports
Hypotension after starting continuous renal replacement therapy (CRRT) is associated with worse outcomes compared with normotension, but it is difficult to predict because several factors have interactive and complex effects on the risk. The present ...

Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.

Critical care (London, England)
BACKGROUND: Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing co...