2007
DOI: 10.1007/s00134-007-0767-z
|View full text |Cite
|
Sign up to set email alerts
|

Automatic detection of ineffective triggering and double triggering during mechanical ventilation

Abstract: We have demonstrated the feasibility and efficacy of a new algorithm to detect the occurrence of impaired patient-ventilator interaction during mechanical ventilation in real time. This software may help the clinician in the identification of this problem, which has been shown to have important clinical consequences.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

2
72
0
1

Year Published

2008
2008
2022
2022

Publication Types

Select...
5
4

Relationship

0
9

Authors

Journals

citations
Cited by 87 publications
(78 citation statements)
references
References 11 publications
2
72
0
1
Order By: Relevance
“…While home ventilators can adequately compensate large gas leaks, ICU ventilators are not able to cope with large leaks and need to titrate trigger sensitivity to avoid auto-triggering and asynchrony between patient and ventilator [135][136][137]. Indeed, the presence of asynchrony represents one of the main problems with NPPV both during ARF episodes [138] and in long-term ventilation for chronic respiratory insufficiency [139]. In this regard, the recording of breathing frequency using the ventilator monitor may be misleading.…”
Section: Leaks and Ventilators: Icu Versus Homementioning
confidence: 99%
“…While home ventilators can adequately compensate large gas leaks, ICU ventilators are not able to cope with large leaks and need to titrate trigger sensitivity to avoid auto-triggering and asynchrony between patient and ventilator [135][136][137]. Indeed, the presence of asynchrony represents one of the main problems with NPPV both during ARF episodes [138] and in long-term ventilation for chronic respiratory insufficiency [139]. In this regard, the recording of breathing frequency using the ventilator monitor may be misleading.…”
Section: Leaks and Ventilators: Icu Versus Homementioning
confidence: 99%
“…Recently, a parallel approach was developed by Mulqueeny et al [18]. They built an algorithm that was able to detect ineffective triggering efforts based on significant alterations of the expiratory flow signal.…”
Section: Discussionmentioning
confidence: 99%
“…More recently, several investigators have explored the use of machine learning and pattern recognition to automatically detect asynchrony. [63][64][65][66][67] In most instances these systems specifically address the issue of missed triggers. Chen et al used measurements of flow and pressure deflections to detect missed triggers in 14 mechanically ventilated patients.…”
Section: Automated Detection Of Asynchronymentioning
confidence: 99%
“…63 Mulqueeney and others have shown that pattern recognition software can detect missed triggers during the expiratory phase with an overall accuracy of near 95%. 64,65 More recently, Blanch and colleagues have evaluated the Better Care system for detection of missed triggers during invasive ventilation. 66 The Better Care software calculates a theoretical mono-exponential expiratory flow curve and compares it to the actual expiratory flow curve by evaluating the percentage deviation.…”
Section: Automated Detection Of Asynchronymentioning
confidence: 99%