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Related Concept Videos

Chronic Kidney Disease III: Interprofessional Care01:28

Chronic Kidney Disease III: Interprofessional Care

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Chronic kidney disease (CKD) requires collaborative and comprehensive management. CKD progresses through stages and can lead to end-stage kidney disease (ESKD) if untreated. Interprofessional collaboration and patient education are crucial, enabling patients to manage their health and improve their quality of life.Diagnostic approach for chronic kidney diseaseThe diagnosis of CKD primarily focuses on the glomerular filtration rate (GFR), which assesses kidney function by measuring how well...
82
Chronic Kidney Disease I: Introduction01:25

Chronic Kidney Disease I: Introduction

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Chronic Kidney Disease (CKD) arises when the kidneys progressively lose their ability to function, ultimately leading to end-stage renal disease. At this advanced stage, the kidneys can no longer filter waste or maintain essential body functions, requiring renal replacement therapy (RRT) through dialysis or a kidney transplant for survival.Early-stage chronic kidney disease and detection challengesIn CKD's early stages, symptoms often remain absent because healthy nephrons compensate for...
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Chronic Kidney Disease IV: Nursing Management01:18

Chronic Kidney Disease IV: Nursing Management

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Nursing management is essential for preventing complications, maintaining stability, and improving patients' quality of life in chronic kidney disease (CKD). By using a structured approach, nurses help slow CKD progression and support effective patient care​.1. Comprehensive patient assessmentEffective management begins with nurses reviewing the patient’s medical history, and identifying key risk factors like diabetes, hypertension, and nephrotoxic drug use. Nurses assess signs of...
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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 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 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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Updated: Sep 17, 2025

5/6 Nephrectomy Using Sharp Bipolectomy Via Midline Laparotomy in Rats
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Predicting Hospitalization and Related Outcomes in Advanced Chronic Kidney Disease: A Systematic Review, External

Roemer J Janse1, Jet Milders1, Joris I Rotmans2

  • 1Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

Kidney Medicine
|July 4, 2025
PubMed
Summary

Predicting hospitalizations for advanced chronic kidney disease (CKD) patients is challenging. Current models show poor performance, necessitating development of new, more specific prediction tools for better patient care.

Keywords:
Algorithmchronic kidney diseasedialysishospital admissionhospitalizationlength of staypredictionreadmissionrisk score

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Area of Science:

  • Nephrology
  • Clinical Epidemiology
  • Biostatistics

Background:

  • Hospitalization is frequent in advanced chronic kidney disease (CKD).
  • Predictive models for hospitalization, length of stay, and readmission are valuable for patient management and healthcare planning.
  • Existing models require external validation and potential development of new tools.

Purpose of the Study:

  • To review and externally validate existing prediction models for hospitalization, length of stay, and readmission in advanced CKD patients.
  • To develop a new prediction model if current models prove inadequate.

Main Methods:

  • Systematic literature search for prediction models in adults with CKD.
  • Risk of bias assessment using PROBAST.
  • External validation of identified models for discrimination (C-statistic) and calibration.
  • Development of a Fine-Gray model for 1-year hospitalization risk in hemodialysis patients.

Main Results:

  • 45 models from 8 studies were identified, mostly of low quality with high risk of bias.
  • Only 3 models were validated due to underreporting and population-specific predictors; these showed poor calibration and discrimination.
  • Development of an adequate new model was not feasible with available data and strategies.

Conclusions:

  • Predicting hospitalization in advanced CKD is difficult due to outcome heterogeneity and limited predictors.
  • Future models should focus on more specific outcomes (e.g., cardiovascular hospitalizations) and incorporate patient-reported outcome measures for improved accuracy.