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

Mechanical Ventilation II: Invasive Ventilation01:23

Mechanical Ventilation II: Invasive Ventilation

154
Ventilators are essential medical equipment used to aid patients with respiratory difficulties. Their primary function is to assist or replace spontaneous breathing by providing mechanical ventilation. There are two general classes of mechanical ventilators: negative-pressure and positive-pressure ventilators.
Negative-Pressure Ventilators
Negative-pressure ventilators create a vacuum around the chest or body to draw air into the lungs, simulating breathing. This method does not require an...
154
Mechanical Ventilation III: Noninvasive Ventilation01:23

Mechanical Ventilation III: Noninvasive Ventilation

125
Noninvasive positive-pressure ventilation (NIPPV), continuous positive airway pressure (CPAP), and bilevel positive airway pressure (BiPAP) are essential methods in respiratory care. These ventilation techniques offer unique benefits for patients with various respiratory conditions, providing adequate support without requiring intubation. Let's explore how each method is crucial in improving patient outcomes and enhancing respiratory therapy.
Noninvasive Positive-Pressure Ventilation...
125
Ventilatory Modes01:14

Ventilatory Modes

175
Mechanical ventilators are life-saving devices that support or replace spontaneous breathing. They deliver breaths to patients through varying methods known as ventilator modes. Understanding these modes is critical for healthcare providers managing patients with respiratory failure.
There are three ventilatory modes: full support, partial support, and spontaneous. These are described below.
Full Support Modes
Full support modes include controlled mechanical ventilation, continuous mandatory...
175
Tracheostomy Decannulation01:21

Tracheostomy Decannulation

195
Tracheostomy decannulation is a significant milestone in the liberation of mechanically ventilated patients. Despite its importance, there is no universally accepted protocol for this procedure. This demands an evidence-based, individualized approach.
Description of the Procedure
Decannulation refers to the permanent removal of the tracheostomy tube, signaling the resolution of the condition that initially necessitated the tracheostomy. The process requires a well-coordinated interplay between...
195

You might also read

Related Articles

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

Sort by
Same author

ICU-acquired infections and thrombo-embolic events in critically ill patients receiving platelet transfusion: a prospective multicenter observational study.

Blood transfusion = Trasfusione del sangue·2026
Same author

Diuresis increase after positive end-expiratory pressure weaning during acute respiratory distress syndrome.

Scientific reports·2025
Same author

Volatile sedation in critically ills adults undergoing mechanical ventilation: not all inhaled sedatives are equivalent!

Critical care (London, England)·2025
Same author

Characteristics and outcomes of ICU patients with sepsis transmitted by cats and dogs: the PETSEPSIS multicentre retrospective observational cohort study.

Critical care (London, England)·2025
Same author

Potential association of TGFβ1 plasma levels and fibrinolysis parameters with the risk of recurrence and vascular obstruction after a first unprovoked pulmonary embolism episode.

Journal of thrombosis and thrombolysis·2025
Same author

The continued industrial use of ethylene oxide despite health risks: An interventional radiology perspective on a broader medical challenge of balancing sterility, safety, and sustainability.

Diagnostic and interventional imaging·2025

Related Experiment Video

Updated: Jul 10, 2025

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.8K

Defining predictors for successful mechanical ventilation weaning, using a data-mining process and artificial

Juliette Menguy1, Kahaia De Longeaux1,2, Laetitia Bodenes1

  • 1Medical Intensive Care Unit, CHRU de la Cavale Blanche, Bvd Tanguy-Prigent, 29609, Brest Cedex, France.

Scientific Reports
|November 22, 2023
PubMed
Summary

Predicting extubation success in intensive care units (ICU) is vital. This study identified key physiological parameters and developed an AI model to accurately forecast successful mechanical ventilation weaning, reducing adverse events.

More Related Videos

Use of an Integrated Low-Flow Anesthetic Vaporizer, Ventilator, and Physiological Monitoring System for Rodents
06:57

Use of an Integrated Low-Flow Anesthetic Vaporizer, Ventilator, and Physiological Monitoring System for Rodents

Published on: July 9, 2020

6.0K
Ex Vivo Porcine Experimental Model for Studying and Teaching Lung Mechanics
12:09

Ex Vivo Porcine Experimental Model for Studying and Teaching Lung Mechanics

Published on: April 19, 2024

1.5K

Related Experiment Videos

Last Updated: Jul 10, 2025

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.8K
Use of an Integrated Low-Flow Anesthetic Vaporizer, Ventilator, and Physiological Monitoring System for Rodents
06:57

Use of an Integrated Low-Flow Anesthetic Vaporizer, Ventilator, and Physiological Monitoring System for Rodents

Published on: July 9, 2020

6.0K
Ex Vivo Porcine Experimental Model for Studying and Teaching Lung Mechanics
12:09

Ex Vivo Porcine Experimental Model for Studying and Teaching Lung Mechanics

Published on: April 19, 2024

1.5K

Area of Science:

  • Critical Care Medicine
  • Biomedical Engineering
  • Data Science

Background:

  • Mechanical ventilation weaning is complex, with failed extubation leading to increased morbidity and mortality.
  • Identifying predictors of extubation success is crucial for optimizing patient outcomes in intensive care units (ICUs).

Purpose of the Study:

  • To identify predictive factors for extubation success using data-mining and artificial intelligence.
  • To develop a dynamic predictive model for forecasting successful weaning from mechanical ventilation.

Main Methods:

  • Prospective data collection of physiological and biomedical signals from adult patients undergoing mechanical ventilation weaning.
  • Analysis of hemodynamic and respiratory parameters during spontaneous breathing trials (SBTs).
  • Development of a predictive model incorporating parameters like Early-Warning Score Oxygen (EWSO2), mean arterial pressure, heart-rate variability, body-mass index (BMI), occlusion pressure (P0.1), and LF/HF ratio.

Main Results:

  • The Early-Warning Score Oxygen (EWSO2) effectively discriminated between patients likely to succeed extubation at 72 hours and 7 days (AUC=0.80).
  • Key predictors identified include BMI, P0.1, LF/HF ratio (pre-SBT), and heart rate during SBT.
  • The developed AI model demonstrated a global performance of 62% and 83% for predicting extubation success.

Conclusions:

  • Data-mining and artificial intelligence can identify independent predictors of extubation success.
  • A dynamic predictive model using AI can assist clinicians in better discriminating patients for successful extubation.
  • Improved prediction of extubation success can lead to enhanced clinical performance and reduced adverse events in ICUs.