AIMC Topic: Acute Kidney Injury

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Renal Dysfunction Across the Spectrum of Cardiogenic Shock: Mechanisms, Clinical Implications, and Therapeutic Strategies.

Current heart failure reports
PURPOSE OF REVIEW: This review aims to elucidate the complex interplay between cardiogenic shock (CS) and renal function, detailing the mechanisms of kidney injury, identifying risk factors, and providing a framework for the diagnosis and management ...

Moving beyond the syndrome: how can acute kidney injury phenotypes help?

Current opinion in nephrology and hypertension
PURPOSE OF REVIEW: The purpose of this review is to describe recent and important updates in acute kidney injury (AKI) phenotyping that help us to move beyond the clinical syndrome of AKI.

Exploring the molecular mechanisms of lactylation-related biological functions and immune regulation in sepsis-associated acute kidney injury.

Clinical and experimental medicine
Lactylation, a novel post-translational modification, has been implicated in various pathophysiological processes; however, its role in sepsis-associated acute kidney injury (SA-AKI) remains unclear. This study aimed to investigate the expression pat...

Development and validation of a cardiac surgery-associated acute kidney injury prediction model using the MIMIC-IV database.

PloS one
OBJECTIVE: This study aimed to develop an innovative early prediction model for acute kidney injury (AKI) following cardiac surgery in intensive care unit (ICU) settings, leveraging preoperative and postoperative clinical variables, and to identify k...

Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Scientific reports
Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis-induced myocardial injury (SIMI). Prompt and early prediction of sAKI has an important role in timely intervention, ultimately improving the patients...

DEVELOPMENT AND VALIDATION OF A PREDICTION MODEL FOR SEPTIC SHOCK-ASSOCIATED ACUTE KIDNEY INJURY: A MULTICENTER STUDY USING NOMOGRAM MODELING.

Shock (Augusta, Ga.)
Background: Septic shock-associated acute kidney injury (SS-AKI) is a severe complication with high mortality. This study aimed to investigate the risk factors associated with AKI in patients with septic shock and establish a nomogram to predict its ...

Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Persistent sepsis-associated acute kidney injury (SA-AKI) shows poor clinical outcomes and remains a therapeutic challenge for clinicians. Early identification and prediction of persistent SA-AKI are crucial.

Prediction of acute and chronic kidney diseases during the post-covid-19 pandemic with machine learning models: utilizing national electronic health records in the US.

EBioMedicine
BACKGROUND: COVID-19 has been linked to acute kidney injury (AKI) and chronic kidney disease (CKD), but machine learning (ML) models predicting these risks post-pandemic have been absent. We aimed to use large electronic health records (EHR) and ML a...