Multiplying flow and pressure: detecting respiratory phases in intra-arrest ventilation.

Abstract

PURPOSE: To develop a method for detecting respiratory phases and their onset during intra-arrest ventilation with ongoing chest compressions based on explicit definitions for respiratory phase onsets, enabling automated processing at scale. METHODS: An algorithm was developed that uses the product of airflow and airway pressure, and the product of flow and airway pressure slope. For experimental validation of the algorithm, ventilatory recordings from 13 pigs with mechanical ventilation were used. For each animal, 20 ventilations before induction of cardiac arrest (regular ventilation) and 20 ventilations during ongoing chest compressions with asynchronous ventilation (intra-arrest ventilation) were selected. Algorithm performance was analysed against investigator-validated annotations of respiratory phase onsets. RESULTS: The proposed algorithm yielded perfect classification of inspiratory and expiratory phases during regular and intra-arrest ventilation. For the determination of the exact timestamp of respiratory phase onsets, the algorithm had an F1-score of 1 in regular ventilation and 0.971 during intra-arrest ventilation. CONCLUSIONS: We propose an algorithm to detect respiratory phases and their exact onsets robust to chest compressions, which exhibits excellent results on a validation dataset. The concept incorporates the inherent relationship of airflow and airway pressure to differentiate between airflow due to artificial ventilations and airflow due to chest compressions.