analysis. 30–32 Moreover, performing waveform
analysis at the bedside is time consuming and
requires reoptimisation every time patients
change their breathing pattern or their
respiratory system resistance and/or compliance
for any reason (bronchoconstriction,
hyperinflation, increased or decreased pleural
effusion...).
In this setting, there is a real clinical need for
new technologies that can analyse ventilator
waveforms automatically in real time (breath
by breath) and continuously (24/7). The ideal
software should be able to identify any patient’s
respiratory activity, discriminating the beginning
and the end of each inspiratory act; it should be
able to work online as a trigger to command the
inspiratory valve opening and closing according
to the patient’s effort. Manufacturers have
marketed systems that have been implemented
into modern ICU ventilators. They are all
promising tools, but not yet validated and no
results are currently available to document their
performance in improving patient–ventilator
interaction.
FIGURE 6
Interdependence of asynchronies
Over-assistance
Delayed
cycling-off
Dynamic
hyperinflation
Inspiratory delay
Ineffective efforts
activity and reduces asynchronies, also allowing
a reduction in pressure support levels.
Automatic monitoring
In the last ten years, big efforts have made in
developing software able to detect patients’
respiratory activity and, by computing these data
with the ventilator output, toidentify
asynchronies. Most of these monitoring softwares
were able to work online only for brief periods,
usually from minutes to a few hours; in reality,
they mainly worked as offline asynchrony
analysers, particularly focused on major
asynchronies. 27–29 The only effective way to
monitor patient–ventilator interaction online
at the bedside is waveform analysis performed
by the expert clinician: indeed, it allows the
detection of asynchronies and concurrent
optimisation of the ventilator settings. Inevitably,
waveform analysis has specific requirements and
costs. First, specific training is required, because
general clinical expertise and experience do not
necessarily correlate with the ability of clinicians
in detecting asynchronies by waveform
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