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Acute Kidney Injury IV: Diagnostic Studies and Prevention01:30

Acute Kidney Injury IV: Diagnostic Studies and Prevention

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Accurate diagnosis and effective prevention are critical in managing Acute Kidney Injury (AKI), which is linked to high mortality rates ranging from 10% to 80%. Timely recognition of at-risk patients and careful monitoring can significantly reduce the likelihood of kidney damage.Diagnostic Assessments:The diagnostic process starts with a comprehensive medical history to identify prerenal, intrarenal, and postrenal causes.Prerenal causes, such as dehydration, hypotension, or blood loss, should...
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Acute Kidney Injury II: Pathophysiology01:29

Acute Kidney Injury II: Pathophysiology

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Acute kidney injury (AKI) causes are categorized into three primary categories based on the location of the injury: prerenal, intrarenal (or intrinsic), and postrenal causes. This classification guides clinical management and illustrates how different pathways can impair kidney function.Etiology and Pathophysiology of Acute Kidney Injury1. Prerenal causesEtiology: Prerenal Acute Kidney Injury, the most common type, occurs when reduced blood flow to the kidneys decreases filtration capacity...
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Acute Kidney Injury I: Introduction01:22

Acute Kidney Injury I: Introduction

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Introduction:Acute Kidney Injury (AKI) describes a swift decrease in kidney function occurring over hours to days, characterized by the kidneys' failure to remove waste products from the bloodstream. This leads to dangerous complications like metabolic acidosis, fluid overload, and electrolyte imbalances, such as hyperkalemia, which can cause life-threatening arrhythmias. AKI is common in both hospital and outpatient settings, often triggered by dehydration, sepsis, or exposure to nephrotoxic...
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Acute Kidney Injury III: Clinical Manifestations01:29

Acute Kidney Injury III: Clinical Manifestations

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Acute Kidney Injury (AKI) progresses through distinct clinical phases: the oliguric, diuretic, and recovery phases, each marked by unique manifestations and challenges.Oliguric Phase:The oliguric phase is the initial stage of AKI, typically lasting 10 to 14 days. This phase is marked by a significant reduction in urine output, usually less than 400 mL per day, indicating decreased kidney function. Fluid retention is a prominent feature, leading to symptoms such as edema, hypertension, and...
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Acute Kidney Injury V: Interprofessional Care01:20

Acute Kidney Injury V: Interprofessional Care

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Acute Kidney Injury (AKI) requires a collaborative healthcare approach to restore renal function and prevent complications. Essential management strategies involve monitoring fluid and electrolyte balance, adjusting medications, initiating dialysis when necessary, and providing nutritional support.Fluid and Electrolyte ManagementFluid Monitoring: Regularly monitoring body weight, central venous pressure, and urine output helps detect fluid imbalances early. Patient intake and output are...
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Acute Kidney Injury VI: Nursing Management01:22

Acute Kidney Injury VI: Nursing Management

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Acute Kidney Injury (AKI) results in an inability to maintain fluid, electrolyte, and acid-base balance. Effective nursing management is critical in improving patient outcomes and includes comprehensive patient assessment and targeted interventions.Comprehensive Patient AssessmentA detailed history collection is essential, focusing on any recent infections, nephrotoxic medication use, or chronic conditions such as hypertension and diabetes that may contribute to AKI. During the physical...
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Updated: Jan 16, 2026

Standardized Colon Ascendens Stent Peritonitis in Rats - a Simple, Feasible Animal Model to Induce Septic Acute Kidney Injury
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Prediction of Moderate-to-Severe Sepsis-Associated Acute Kidney Injury Using a Dual-Timepoint Machine Learning Model:

Xinbo Ge1,2, Weiwei Chen1,3, Jianshan Shi4

  • 1Department of Critical Care Medicine, The First Affiliated Hospital of Hainan Medical University, Haikou, China.

Journal of Medical Internet Research
|September 30, 2025
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Summary

This study developed a machine learning model to predict sepsis-associated acute kidney injury (SA-AKI) risk at critical time points. The validated tool offers stage-specific predictions for better clinical decision-making.

Keywords:
SHAPShapley additive explanationacute kidney injuryclinical decision supportmachine learningmulticenter validationpredictive modelsepsis

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Area of Science:

  • Critical care medicine
  • Nephrology
  • Data science in healthcare

Background:

  • Sepsis-associated acute kidney injury (SA-AKI) is a major ICU complication with high mortality.
  • Current prediction models lack severity stratification, limiting clinical utility.

Purpose of the Study:

  • Identify critical time points for SA-AKI progression.
  • Develop and validate dynamic, stratified machine learning models for moderate-to-severe SA-AKI.
  • Deploy models as accessible, interpretable clinical decision support tools.

Main Methods:

  • Utilized three independent ICU databases for model development and validation.
  • Identified 48-hour and 7-day critical time points.
  • Employed LightGBM and SHAP for feature selection and model interpretation, validated across multiple centers and regions.

Main Results:

  • The LightGBM model showed robust predictive performance with AUCs ranging from 0.720 to 0.839 across prediction tasks and cohorts.
  • Key predictors included urine output, mechanical ventilation, SOFA score, creatinine, GCS, and nephrotoxic drug use.
  • Model performance was consistent across various subgroups and validated through decision curve analysis.

Conclusions:

  • Developed and validated a dynamic, stratified prediction system for moderate-to-severe SA-AKI.
  • The system provides stage-specific risk assessment and has been translated into an interpretable clinical decision support tool.
  • Offers a scientific foundation for precision management of SA-AKI.