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Related Concept Videos

Tracheostomy Decannulation01:21

Tracheostomy Decannulation

63
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...
63
Oxygen Delivering System III: Tracheostomy and T-piece01:23

Oxygen Delivering System III: Tracheostomy and T-piece

268
Oxygen delivery is critical in clinical care, especially for patients with respiratory disorders or those undergoing surgical procedures. Various systems, such as tracheostomy and the T-piece, deliver oxygen to the lungs, ensuring adequate arterial oxygenation.
Tracheostomy
A tracheostomy is a surgically created opening (stoma) in the anterior part of the trachea. It is used to establish a patient airway, bypass an upper airway obstruction, simplify the removal of secretions, permit long-term...
268
Oxygen Delivering System II: Venturi Mask and Transtracheal Oxygen01:16

Oxygen Delivering System II: Venturi Mask and Transtracheal Oxygen

213
Oxygen therapy is a pivotal aspect of medical care, particularly for patients with respiratory ailments. Two prominent oxygen-delivering systems include the Venturi mask and the transtracheal oxygen catheter.
Venturi Mask
The Venturi mask, named after the Venturi effect, is designed to deliver precise oxygen concentrations. It consists of a large tube with an oxygen inlet that narrows down, causing a pressure drop that pulls air in through adjustable side ports. The mask is a lightweight,...
213
Tracheostomy Care I: Pre-procedural Steps01:16

Tracheostomy Care I: Pre-procedural Steps

95
A tracheostomy is a surgical technique that involves making an incision in the neck to provide access to the trachea. It is frequently used in medical conditions such as airway obstruction and prolonged mechanical ventilation. Effective nursing management is crucial for the long-term success of a tracheostomy.
Required Equipment
The equipment necessary for tracheostomy care includes:
95
Tracheostomy Care II: Procedure01:25

Tracheostomy Care II: Procedure

90
Tracheostomy care is an essential nursing skill that involves cleaning and maintaining a tracheostomy tube to prevent infection and other complications. Here's a step-by-step guide explaining each procedure with its rationale. Note that disposable gloves are to be worn at all times and changed as often as needed to maintain a sterile work environment, and to protect both patient and healthcare worker.
Step 1: Perform hand hygiene, and put on personal protective equipment: gown, gloves, mask...
90
Tracheostomy Suctioning I: Pre-Procedural Steps01:26

Tracheostomy Suctioning I: Pre-Procedural Steps

341
Tracheostomy suctioning is a critical procedure healthcare professionals perform to maintain a patent airway in patients with a tracheostomy tube. This procedure is necessary when secretions accumulate in the airway, causing respiratory distress. Here is a step-wise procedural guide for performing tracheostomy suctioning using an open system.
Equipment Required
First, gather all necessary equipment: a sterile suction catheter, a sterile disposable container, sterile gloves, a towel or...
341

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Related Experiment Video

Updated: May 16, 2025

Manufacture of a Multi-Purpose Low-Cost Animal Bench-Model for Teaching Tracheostomy
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Deployable machine learning-based decision support system for tracheostomy in acute burn patients.

Haisheng Li1, Ni Zhen1, Shixu Lin2

  • 1Institute of Burn Research, Southwest Hospital, State Key Laboratory of Trauma and Chemical Poisoning, Third Military Medical University (Army Medical University), Chongqing 400038, China.

Burns & Trauma
|May 14, 2025
PubMed
Summary
This summary is machine-generated.

This study developed a machine learning system to predict tracheostomy needs in burn patients, improving emergency airway management. The validated tool, including a nomogram and calculator, offers reliable decision support, especially in resource-limited settings.

Keywords:
Artificial intelligenceBurnsDecision support systemMachine learningTracheostomy

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Area of Science:

  • Medical Informatics
  • Emergency Medicine
  • Surgical Critical Care

Background:

  • Airway obstruction is a critical emergency in acute burns, often necessitating tracheostomy for airway patency and mechanical ventilation.
  • Indications for tracheostomy in burn patients are challenging and controversial, leading to potential delays or unnecessary procedures.
  • Developing a reliable decision support system is crucial for optimizing tracheostomy decisions in acute burn care.

Purpose of the Study:

  • To develop and validate a deployable machine learning (ML)-based decision support system for predicting the necessity of tracheostomy in acute burn patients.
  • To enhance the interpretability and clinical utility of the ML model through a nomogram, online calculator, and abbreviated scale.
  • To evaluate the generalizability and predictive performance of the developed system across different clinical settings.

Main Methods:

  • Development and feature selection using a cohort of 1011 burn patients from Southwest Hospital (2018-20).
  • Validation on an independent internal cross-temporal cohort (n=274, 2021) and an external cross-institutional cohort (n=376, 2020-21).
  • Utilized an eXtreme Gradient Boosting (XGB) classifier, constructing an ML-based nomogram, online calculator, and abbreviated scale (BETS).

Main Results:

  • The XGB model achieved high predictive performance with an AUROC of 0.973 in training and >0.95 in both validation cohorts.
  • The model demonstrated stable discriminatory ability across subgroups stratified by sex, age, burn area, and inhalation injury (AUROC 0.903-0.990).
  • The ML-based nomogram, BETS scale, and online calculator showed feasibility and reliability based on calibration and decision curve analyses.

Conclusions:

  • The developed ML-based decision support system exhibits strong predictive ability and generalizability for tracheostomy necessity in acute burn patients.
  • The nomogram, online calculator, and abbreviated scale offer comparable prediction performance and are deployable in various clinical scenarios.
  • This system provides valuable decision support, particularly in resource-limited clinical environments, to optimize emergency airway management for burn survivors.