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Development and validation of a sample entropy-based method to identify complex patient-ventilator interactions during mechanical ventilation
2020
Scientific Reports
Patient-ventilator asynchronies can be detected by close monitoring of ventilator screens by clinicians or through automated algorithms. However, detecting complex patient-ventilator interactions (CP-VI), consisting of changes in the respiratory rate and/or clusters of asynchronies, is a challenge. Sample Entropy (SE) of airway flow (SE-Flow) and airway pressure (SE-Paw) waveforms obtained from 27 critically ill patients was used to develop and validate an automated algorithm for detecting
doi:10.1038/s41598-020-70814-4
pmid:32807815
fatcat:ljoeqpukubgtrb56jvtehw4bve