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Related Concept Videos

Acute Kidney Injury I: Introduction01:22

Acute Kidney Injury I: Introduction

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...
Acute Kidney Injury IV: Diagnostic Studies and Prevention01:30

Acute Kidney Injury IV: Diagnostic Studies and Prevention

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...
Acute Kidney Injury V: Interprofessional Care01:20

Acute Kidney Injury V: Interprofessional Care

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...
Acute Kidney Injury II: Pathophysiology01:29

Acute Kidney Injury II: Pathophysiology

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...
Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration01:28

Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration

Glomerular filtration rate (GFR) can be estimated from serum creatinine using the modification of diet in renal disease (MDRD) formula or the chronic kidney disease–epidemiology collaboration (CKD–EPI) equation. Both methods are widely used in clinical practice to assess kidney function and guide treatment decisions.The MDRD equation does not require weight or height measurements and is normalized to the body surface area of 1.73 m², considered the average adult surface area. This equation is...
Acute Kidney Injury III: Clinical Manifestations01:29

Acute Kidney Injury III: Clinical Manifestations

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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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

Computer-Interpretable Domain Knowledge for Drug-Induced Acute Kidney Injury: a Knowledge Graph Approach.

Romy Vos1, Iacopo Vagliano2,3, Cornelis Boersma4,5,6

  • 1Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. r.m.p.vos@student.vu.nl.

Scientific Data
|June 10, 2026
PubMed
Summary
This summary is machine-generated.

A new Knowledge Graph (KG) for Drug-Induced Acute Kidney Injury (DAKI) organizes drug information to aid in identifying kidney risks. This DAKI KG supports clinical decision-making and machine learning for better patient outcomes.

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

  • Pharmacology
  • Biomedical Informatics
  • Nephrology

Background:

  • Drug-induced acute kidney injury (AKI) poses a significant clinical challenge.
  • Existing knowledge on DAKI is often fragmented across various sources.
  • Standardized data representation is crucial for effective analysis and clinical support.

Purpose of the Study:

  • To develop a comprehensive Knowledge Graph (KG) for Drug-Induced Acute Kidney Injury (DAKI).
  • To integrate and standardize knowledge from diverse, credible sources.
  • To demonstrate the KG's utility in clinical decision support and research.

Main Methods:

  • Integrated data from multiple domain-specific sources.
  • Standardized information to international vocabularies.
  • Validated the DAKI KG using competency questions and expert evaluation.

Main Results:

  • The DAKI KG successfully integrates and standardizes information on drugs causing AKI.
  • Demonstrated applicability through competency questions and expert reviews.
  • Identified potential for decision support tools and machine learning model inputs.

Conclusions:

  • The developed DAKI KG provides a structured knowledge base for drug-induced kidney injury.
  • The KG shows promise for identifying side effects, drug-drug interactions, and aiding research.
  • Further refinement is necessary for direct clinical application, but it is valuable for confounder identification and QA systems.