Automated detection of proper endotracheal intubation

Description:

Software to detect proper endotracheal tube (ETT) placement using existing ventilator parameters

 

Market Need

 

Hundreds of operations necessitate endotracheal intubation each year in the US, of which there are often complications that arise from improper placement of the endotracheal tube. In a pediatric setting, where this is even more difficult due to small airway size, one study reported that the higher the number of attempts of tracheal intubation was related to increase in trauma, hypoxia, and bradycardia and an accidental extubation rate of 20%. Another multicenter study reported that the success rate for first tracheal intubation attempts range from 3-55% with different techniques. The gold standard to confirm proper placement is a chest radiography, which adds a time delay, radiation exposure, and additional cost. Thus, there is a need for a technology that would alert the clinician to improper placement of an endotracheal tube in order to prevent associated complications and a system to detect proper placement of endotracheal tube to support clinical decision support systems.

 

Technology Overview

 

The Rehman lab has created software that uses the parameters already captured from an anesthesia machine, such as respiratory rate, tidal volume, peak inspiratory pressure, and end-tidal carbon dioxide to determine proper tube placement in the trachea. By examining the trend in these parameters in a case where intubation was properly performed, they isolated a variable that showed a consistent trend across different intubation modes that could be used to base the algorithm from and used the other variables to determine the duration of intubation time and proper intubation. When they tested the software on intubation data from 600 de-identified patients, it was found to be 96% successful at detecting intubation within one minute of the recorded time independent of mechanical ventilation mode. This software, which could be adapted to anesthesia machines, could provide instantaneous feedback on ETT placement and recording of intubation time that would reduce injury related to improper ETT placement and support clinical decision support systems.

 

Advantages

•       Automatic alert system for improperly placed endotracheal tube

•       Automatic detection and recording of endotracheal intubation time for clinical decision support

•       Detection is independent of mechanical ventilation mode

Application

•       Alert system for proper endotracheal intubation

•       Training system for teaching how to properly insert an endotracheal tube

 

Stage of Development: In vivo proof of concept

  

Case ID:
0895-16-Rehman
Web Published:
2/22/2017
Patent Information:
Title Country Serial No. Patent No. File Date Issued Date
Automatic Detection of Endotracheal Intubation During the Anesthesia Procedure United States 62/412,508 N/A 10/25/2016  
Category(s):
Software
For Information, Contact:
Cassie Tran
Licensing Associate
The Children's Hospital of Philadelphia
trancm@email.chop.edu
Inventors:
Rehman Mohamed
Ali Jalali
C Nataraj
Keywords:
Algorithm