Validation of an automated system for detecting ineffective triggering asynchronies during mechanical ventilation: a retrospective study

We compare the sensitivity and specificity of clinician visual waveform analysis against an automated system’s waveform analysis in detecting ineffective triggering in mechanically ventilated intensive care unit patients when compared against a reference label set based upon analysis of respiratory...

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Bibliographic Details
Published in:Journal of clinical monitoring and computing 2020-12, Vol.34 (6), p.1233-1237
Main Authors: Phan, Timothy S., Costa, Roberta, Haddad, Wassim M., Mullis, Jerry C., Price, Levi T., Cason, Andrew D., Bailey, James M., Gholami, Behnood
Format: Article
Language:English
Subjects:
Anesthesiology
Brief Communication
Critical Care Medicine
Health Sciences
Intensive
Medicine
Medicine & Public Health
Statistics for Life Sciences
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Summary:We compare the sensitivity and specificity of clinician visual waveform analysis against an automated system’s waveform analysis in detecting ineffective triggering in mechanically ventilated intensive care unit patients when compared against a reference label set based upon analysis of respiratory muscle activity. Electrical activity of the diaphragm or esophageal/transdiaphragmatic pressure waveforms were available to a single clinician for the generation of a reference label set indicating the ground truth, that is, presence or absence of ineffective triggering, on a breath-by-breath basis. Pressure and flow versus time tracings were made available to (i) a group of three clinicians; and (ii) the automated Syncron-E™ system capable of detecting patient-ventilator asynchrony in real-time, in order to obtain breath-by-breath labels indicating the presence or absence of ineffective triggering. The clinicians and the automated system did not have access to other waveforms such as electrical activity of the diaphragm or esophageal/transdiaphragmatic pressure. In total, 926 breaths were analyzed across the seven patients. Specificity for clinicians and the automated system were high (99.3% for clinician and 98.5% for the automated system). The automated system had a significantly higher sensitivity (83.2%) compared to clinicians (41.1%). Ineffective triggering detected by the automated system, which has access only to airway pressure and flow versus time tracings, is in substantial agreement with a reference detection derived from analysis of invasively measured patient effort waveforms.
ISSN:1387-1307
1573-2614
DOI:10.1007/s10877-019-00442-5