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Related Concept Videos

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 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 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 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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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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Using Predictive Models and AI for AKI Research.

Madhumitha Rajagopal1, Lili Chan2, Girish N Nadkarni3

  • 1Samuel Bronfman Department of Medicine, The Barbara T Murphy Division of Nephrology Icahn School of Medicine at Mount Sinai, New York, NY.

Seminars in Nephrology
|October 9, 2025
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Summary
This summary is machine-generated.

Artificial intelligence (AI) aids in predicting acute kidney injury (AKI) and patient outcomes using electronic health records. Newer AI technologies show promise for AKI management, risk stratification, and addressing ethical considerations.

Keywords:
Acute kidney injurygenerative AImachine learningnatural language processingrisk-stratification

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Area of Science:

  • Nephrology
  • Medical Informatics
  • Artificial Intelligence

Background:

  • Acute kidney injury (AKI) is a frequent complication in hospitalized patients, linked to adverse outcomes.
  • Electronic health records (EHRs) have enabled the development of machine learning (ML) for AKI prediction.
  • Existing ML models can predict AKI incidence, severity, persistence, and patient outcomes.

Purpose of the Study:

  • To review the current role of artificial intelligence (AI) in managing adult patients with AKI.
  • To explore the potential of emerging AI technologies, including natural language processing and generative AI, in AKI care.
  • To discuss limitations and ethical considerations associated with AI in AKI management.

Main Methods:

  • Literature review of AI applications in AKI prediction and management.
  • Analysis of machine learning algorithms utilizing electronic health records.
  • Exploration of natural language processing and generative AI for AKI.

Main Results:

  • AI and ML algorithms can predict AKI incidence, severity, and patient outcomes like mortality.
  • AI facilitates risk stratification for early clinical management of AKI.
  • Emerging AI technologies show promise for enhancing AKI prediction and management strategies.

Conclusions:

  • AI offers significant potential in improving the prediction and management of AKI in hospitalized adults.
  • Further research and ethical considerations are crucial for the responsible integration of AI in AKI care.
  • AI tools can aid clinicians in risk-stratifying patients and optimizing treatment pathways for AKI.