Methods We selected AKI patients from the US-based critical care database (Medical
Information Mart for Intensive Care, MIMIC-IV2. 2) who had urine output< 0.5 ml/kg/h in the …

This retrospective cohort study aimed to develop and evaluate a machine-learning algorithm
for predicting oliguria, a sign of acute kidney injury (AKI). To this end, electronic health …

Background and objectives Excess fluid balance in acute kidney injury (AKI) may be
harmful, and conversely, some patients may respond to fluid challenges. This study aimed to …

Objectives: The Kidney Disease: Improving Global Outcomes urine output criteria for acute
kidney injury lack specificity for identifying patients at risk of adverse renal outcomes. The …

Objectives The purpose of this study was to externally validate algorithms (previously
developed and trained in two United States populations) aimed at early detection of severe …

Methods We conducted a secondary analysis of the Crystalloid versus Hydroxyethyl Starch
Trial (CHEST) trial, a blinded randomized controlled trial that enrolled ICU patients who …

In critically ill patients, both increased and decreased renal clearance are highly prevalent
and may vary during the course of critical illness. Acute kidney injury is a type of organ …

Background and objective To develop a machine learning model to predict urine output
(UO) in sepsis patients after fluid resuscitation. Methods We identified sepsis patients in the …

Background: The relationship between urine output (UO) and severe-stage progression in
the early phase of acute kidney injury (AKI) remains unclear. This study aimed to investigate …

Methods: This retrospective observational study analyzed data from 30 adult patients
undergoing cardiac surgery with cardiopulmonary bypass (CPB). Demographics, vital signs …