AIMC Topic: Acute Kidney Injury

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GenAI exceeds clinical experts in predicting acute kidney injury following paediatric cardiopulmonary bypass.

Scientific reports Jul 1, 2025
The emergence of large language models (LLMs) opens new horizons to leverage, often unused, information in clinical text. Our study aims to capitalise on this new potential. Specifically, we examine the utility of text embeddings generated by LLMs in...
Child Cardiopulmonary Bypass Acute Kidney Injury Electronic Health Records Female Male Postoperative Complications Infant Child, Preschool Humans Algorithms
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Usability of machine learning algorithms based on electronic health records for the prediction of acute kidney injury and transition to acute kidney disease: A proof of concept study.

PloS one Jul 1, 2025
BACKGROUND: Acute kidney injury (AKI) and acute kidney disease (AKD) are frequent complications of hospitalization, resulting in reduced outcomes and increased cost burden. However, these conditions are only sometimes recognized and promptly treated....
Machine Learning Algorithms Retrospective Studies Acute Kidney Injury Humans Adult Male Middle Aged Proof of Concept Study Electronic Health Records Female Hospitalization Aged
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Renal Dysfunction Across the Spectrum of Cardiogenic Shock: Mechanisms, Clinical Implications, and Therapeutic Strategies.

Current heart failure reports Jun 25, 2025
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 ...
Humans Risk Factors Shock, Cardiogenic Prognosis Renal Replacement Therapy Acute Kidney Injury
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Machine learning model for the prediction of postoperative acute kidney injury (AKI) in neonates undergoing digestive surgery.

Pediatric surgery international Jun 24, 2025
OBJECTIVE: The aim of our study is to determine the main predictors of postoperative AKI in neonates using machine learning models compared with the logistic regression model.
Retrospective Studies Acute Kidney Injury Female Infant, Newborn Humans Machine Learning Logistic Models Predictive Value of Tests Digestive System Surgical Procedures Risk Factors Male Postoperative Complications Incidence
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Exploring the molecular mechanisms of lactylation-related biological functions and immune regulation in sepsis-associated acute kidney injury.

Clinical and experimental medicine Jun 12, 2025
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...
Protein Processing, Post-Translational Humans Acute Kidney Injury Gene Expression Profiling Transcriptome Sepsis Gene Regulatory Networks
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Development and validation of a cardiac surgery-associated acute kidney injury prediction model using the MIMIC-IV database.

PloS one Jun 12, 2025
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...
Cardiac Surgical Procedures Middle Aged Postoperative Complications ROC Curve Logistic Models Humans Risk Factors Algorithms Aged Databases, Factual Male Retrospective Studies Acute Kidney Injury Intensive Care Units Female
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Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Scientific reports Jun 4, 2025
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...
Cardiomyopathies Male Middle Aged Sepsis ROC Curve Intensive Care Units Humans Female Machine Learning Aged Retrospective Studies Acute Kidney Injury
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A machine learning-based prediction model for sepsis-associated delirium in intensive care unit patients with sepsis-associated acute kidney injury.

Renal failure Jun 2, 2025
Sepsis-associated acute kidney injury (SA-AKI) patients in the ICU often suffer from sepsis-associated delirium (SAD), which is linked to unfavorable outcomes. This research aimed to develop a machine learning-based model for early SAD prediction in ...
Humans Machine Learning Acute Kidney Injury Intensive Care Units Delirium ROC Curve Female Male Aged Logistic Models Middle Aged Sepsis Decision Trees Bayes Theorem
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A deep-learning algorithm using real-time collected intraoperative vital sign signals for predicting acute kidney injury after major non-cardiac surgeries: A modelling study.

PLoS medicine Apr 29, 2025
BACKGROUND: Postoperative acute kidney injury (PO-AKI) prediction models for non-cardiac major surgeries typically rely solely on preoperative clinical characteristics.
Middle Aged Risk Assessment Female Deep Learning Risk Factors Postoperative Complications Humans Predictive Value of Tests Aged Algorithms Vital Signs Male Acute Kidney Injury
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Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study.

Journal of medical Internet research Apr 28, 2025
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.
Retrospective Studies Acute Kidney Injury Aged Machine Learning Intensive Care Units Humans Male Female Prospective Studies Middle Aged Biomarkers Sepsis
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