Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Blood Transfusion and Agglutination02:45

Blood Transfusion and Agglutination

Blood transfusion is a therapeutic measure to restore the blood volume after extensive blood loss due to an accident or a medical procedure. Blood transfusion involves drawing a certain amount of blood from a suitable donor and infusing it into the recipient.
History
The history of blood transfusion dates back to the 17th century, when early attempts were made in animals. In 1818 James Blundell, a British doctor, performed the first successful human blood transfusion. Later in 1900, Karl...
Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

How plaque morphology and stenosis severity govern stent-artery interaction and deployment outcomes: a computational study.

Medical & biological engineering & computing·2026
Same author

A physics-informed multi-modal transformer framework for predictive maintenance and remaining useful life estimation of electrical submersible pumps.

Scientific reports·2026
Same author

Promoting a healthy lifestyle during pregnancy in Iran: a best practice implementation project.

JBI evidence implementation·2026
Same author

Effects of binaural beats on acute stress recovery and autonomic regulation in multiple sclerosis: a pilot double-blind randomized controlled trial.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology·2026
Same author

A rare case of heterotopic ossification after an ankle sprain.

Trauma case reports·2026
Same author

Acute and chronic kidney injury following COVID-19 infection and vaccination: a narrative review.

European journal of translational myology·2026

Related Experiment Video

Updated: Jul 3, 2026

Visualization and Analysis of Blood Flow and Oxygen Consumption in Hepatic Microcirculation: Application to an Acute Hepatitis Model
10:40

Visualization and Analysis of Blood Flow and Oxygen Consumption in Hepatic Microcirculation: Application to an Acute Hepatitis Model

Published on: August 4, 2012

12.7K

Surveying haemoperfusion impact on COVID-19 from machine learning using Shapley values.

Behzad Einollahi1, Mohammad Javanbakht2, Mehrdad Ebrahimi2

  • 1Nephrology and Urology Research Center, Clinical Science Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran. behzad.einollahi@gmail.com.

Inflammopharmacology
|May 19, 2024
PubMed
Summary

Haemoperfusion (HP) significantly improved outcomes for severe COVID-19 patients by reducing ventilation needs and mortality. This extracorporeal therapy effectively filters blood, showing a positive impact on patient survival and prognosis.

Keywords:
CorticosteroidHaemoperfusionMortalityShapley valuesVentilation

More Related Videos

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.2K
A Data-Driven Approach to Quantifying Immune States in Sepsis
07:42

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

167

Related Experiment Videos

Last Updated: Jul 3, 2026

Visualization and Analysis of Blood Flow and Oxygen Consumption in Hepatic Microcirculation: Application to an Acute Hepatitis Model
10:40

Visualization and Analysis of Blood Flow and Oxygen Consumption in Hepatic Microcirculation: Application to an Acute Hepatitis Model

Published on: August 4, 2012

12.7K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.2K
A Data-Driven Approach to Quantifying Immune States in Sepsis
07:42

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

167

Area of Science:

  • Extracorporeal therapies
  • Critical care medicine
  • Immunomodulation

Background:

  • Severe COVID-19 is characterized by a cytokine storm, leading to organ damage.
  • Haemoperfusion (HP) is an extracorporeal therapy designed to remove inflammatory mediators from the blood.
  • Assessing the clinical efficacy of HP in severe COVID-19 is crucial for improving patient outcomes.

Purpose of the Study:

  • To evaluate the clinical benefits of haemoperfusion (HP) in patients with severe COVID-19.
  • To compare the outcomes of patients treated with standard care versus standard care plus HP.
  • To utilize machine learning, specifically Shapley values, to understand the contribution of HP to patient prognosis.

Main Methods:

  • A retrospective cohort study of 578 inpatients with severe COVID-19.
  • Control group received standard corticosteroid treatment (Regimen I).
  • HP group received standard corticosteroid treatment plus haemoperfusion using Cytosorb H300 (Regimen II), with session frequency based on chest CT findings. Machine learning models incorporated patient characteristics, medications, and clinical conditions to calculate Shapley values.

Main Results:

  • Haemoperfusion (HP) group showed a favorable clinical response compared to the control group.
  • One to three HP sessions reduced ventilation requirements and mortality rates in severe COVID-19 patients.
  • HP was associated with significant reductions in inflammation markers (ferritin), creatinine, D-dimer, and WBC levels compared to the control group. Significant differences were observed in the use of various medications between groups (P < 0.05).

Conclusions:

  • Haemoperfusion is a significant factor in predicting patient survival in severe COVID-19.
  • HP demonstrated a positive impact on reducing inflammation and improving renal function markers.
  • The study highlights the crucial role of HP as a therapeutic option for severe COVID-19 cases, influencing patient prognosis.