Detecting ineffective triggering in the expiratory phase in mechanically ventilated patients based on airway flow and pressure deflection: Feasibility of using a computer algorithm*

Abstract

We conclude that accurately detecting and quantifying ITEs is feasible using a computerized algorithm based on F(def) and P(def). Such a computerized estimation of patient-ventilator interaction might be helpful for adjusting ventilator settings in an intensive care unit.

Nurses' Detection of Ineffective Inspiratory Efforts During Mechanical Ventilation

“…[1][2][3] This is an issue of concern because PVD may influence outcome. Thille et al 1 studied 62 patients receiving mechanical ventilation for more than 24 hours who were able to trigger all the ventilator's breaths during assisted-control ventilation.…”

“…We selected the first 32 breaths in each deviation category from each of the 8 patients, and this yielded a data base of 1024 breaths for the study. A random-P atient-ventilator dyssynchrony (PVD) is highly prevalent in patients receiving mechanical ventilation, [1][2][3] and it may influence their outcome. PVD increases the duration of mechanical ventilation and consequently the tracheostomy rate.…”

Asynchrony and DyspneaDiscussion

“…They demonstrated a sensitivity and specificity of Ͼ 90% for detecting missed triggers. 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.…”

“…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.…”

Ineffective efforts during mechanical ventilation: the brain wants, the machine declines

“…Therefore, automatic detection and recording of IE using noninvasive methods that do not interfere with patients' management and preferably are not affected by noise (i.e., secretions, body movements) are welcome. In recent years several methods of automatic detection of IE during invasive or noninvasive mechanical ventilation have been published [14,[22][23][24]. In this issue of Intensive Care Medicine Blanch et al [25] present one such method validated in a small number of intubated patients.…”