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Acute Kidney Injury

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Calprotectin and Neutrophil Gelatinase-Associated Lipocalin As Biomarkers of Acute Kidney Injury in Acute Coronary Syndrome.

The American journal of the medical sciences
BACKGROUND: Acute kidney injury (AKI) is increasingly being seen in patients with acute coronary syndromes (ACS) and it is associated with higher short-term and long-term morbidity and mortality. Therefore, it is of paramount importance to identify t...

Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records.

Utilizing imbalanced electronic health records to predict acute kidney injury by ensemble learning and time series model.

BMC medical informatics and decision making
BACKGROUND: Acute Kidney Injury (AKI) is a shared complication among Intensive Care Unit (ICU), marked by high cost, high morbidity and high mortality. As the early prediction of AKI is critical for patients' outcomes and data mining is such a powerf...

Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Community-acquired acute kidney injury (CA-AKI)-associated hospitalizations impose significant health care needs and contribute to in-hospital mortality. However, most risk prediction models developed to date have focused on AKI in a spec...

Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury.

JAMA network open
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 few prediction models have been externally validated.

Explainable artificial intelligence model to predict acute critical illness from electronic health records.

Nature communications
Acute critical illness is often preceded by deterioration of routinely measured clinical parameters, e.g., blood pressure and heart rate. Early clinical prediction is typically based on manually calculated screening metrics that simply weigh these pa...

Prediction of the development of acute kidney injury following cardiac surgery by machine learning.

Critical care (London, England)
BACKGROUND: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication that results in increased morbidity and mortality after cardiac surgery. Most established prediction models are limited to the analysis of nonlinear relation...

Early Prediction of Acute Kidney Injury in the Emergency Department With Machine-Learning Methods Applied to Electronic Health Record Data.

Annals of emergency medicine
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 acute kidney injury treatment can improve outcomes. However, current dec...

Acute kidney injury and its impact on renal prognosis after robot-assisted laparoscopic radical prostatectomy.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: This study assessed the incidence and impact of acute kidney injury (AKI) on renal prognosis in patients who underwent robot-assisted laparoscopic radical prostatectomy (RARP).