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Automatic Detection of Ventilations During Mechanical Cardiopulmonary Resuscitation.

ABSTRACT: Feedback on chest compressions and ventilations during cardiopulmonary resuscitation (CPR) is important to improve survival from out-of-hospital cardiac arrest (OHCA). The thoracic impedance signal acquired by monitor-defibrillators during treatment can be used to provide feedback on ventilations, but chest compression components prevent accurate detection of ventilations. This study introduces the first method for accurate ventilation detection using the impedance while chest compressions are concurrently delivered by a mechanical CPR device. A total of 423 OHCA patients treated with mechanical CPR were included, 761 analysis intervals were selected which in total comprised 5 884 minutes and contained 34 864 ventilations. Ground truth ventilations were determined using the expired CO 2 channel. The method uses adaptive signal processing to obtain the impedance ventilation waveform. Then, 14 features were calculated from the ventilation waveform and fed to a random forest (RF) classifier to discriminate false positive detections from actual ventilations. The RF feature importance was used to determine the best feature subset for the classifier. The method was trained and tested using stratified 10-fold cross validation (CV) partitions. The training/test process was repeated 20 times to statistically characterize the results. The best ventilation detector had a median (interdecile range, IDR) F 1-score of 96.32 (96.26-96.37). When used to provide feedback in 1-min intervals, the median (IDR) error and relative error in ventilation rate were 0.002 (-0.334-0.572) min-1 and 0.05 (-3.71-9.08)%, respectively. An accurate ventilation detector during mechanical CPR was demonstrated. The algorithm could be introduced in current equipment for feedback on ventilation rate and quality, and it could contribute to improve OHCA survival rates.

SUBMITTER: Jaureguibeitia X

PROVIDER: S-EPMC7537815 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Automatic Detection of Ventilations During Mechanical Cardiopulmonary Resuscitation.

Jaureguibeitia Xabier X Irusta Unai U Aramendi Elisabete E Owens Pamela C PC Wang Henry E HE Idris Ahamed H AH

IEEE journal of biomedical and health informatics 20200117 9

Feedback on chest compressions and ventilations during cardiopulmonary resuscitation (CPR) is important to improve survival from out-of-hospital cardiac arrest (OHCA). The thoracic impedance signal acquired by monitor-defibrillators during treatment can be used to provide feedback on ventilations, but chest compression components prevent accurate detection of ventilations. This study introduces the first method for accurate ventilation detection using the impedance while chest compressions are c ...[more]

PMID: 31976918

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Project description:Prolonged cardiac arrest (CA) causes microvascular thrombosis which is a potential barrier to organ reperfusion during extracorporeal cardiopulmonary resuscitation (ECPR). The aim of this study was to test the hypothesis that early intra-arrest anticoagulation during cardiopulmonary resuscitation (CPR) and thrombolytic therapy during ECPR improve recovery of brain and heart function in a porcine model of prolonged out-of-hospital CA.DesignRandomized interventional trial.SettingUniversity laboratory.SubjectsSwine.InterventionsIn a blinded study, 48 swine were subjected to 8 minutes of ventricular fibrillation CA followed by 30 minutes of goal-directed CPR and 8 hours of ECPR. Animals were randomized into four groups (n = 12) and given either placebo (P) or argatroban (ARG; 350 mg/kg) at minute 12 of CA and either placebo (P) or streptokinase (STK, 1.5 MU) at the onset of ECPR.Measurements and main resultsPrimary outcomes included recovery of cardiac function measured by cardiac resuscitability score (CRS: range 0-6) and recovery of brain function measured by the recovery of somatosensory-evoked potential (SSEP) cortical response amplitude. There were no significant differences in recovery of cardiac function as measured by CRS between groups (p = 0.16): P + P 2.3 (1.0); ARG + P = 3.4 (2.1); P + STK = 1.6 (2.0); ARG + STK = 2.9 (2.1). There were no significant differences in the maximum recovery of SSEP cortical response relative to baseline between groups (p = 0.73): P + P = 23% (13%); ARG + P = 20% (13%); P + STK = 25% (14%); ARG + STK = 26% (13%). Histologic analysis demonstrated reduced myocardial necrosis and neurodegeneration in the ARG + STK group relative to the P + P group.ConclusionsIn this swine model of prolonged CA treated with ECPR, early intra-arrest anticoagulation during goal-directed CPR and thrombolytic therapy during ECPR did not improve initial recovery of heart and brain function but did reduce histologic evidence of ischemic injury. The impact of this therapeutic strategy on the long-term recovery of cardiovascular and neurological function requires further investigation.

Project description:It is unclear if cardiopulmonary resuscitation is an aerosol-generating procedure and whether this poses a risk of airborne disease transmission to healthcare workers and bystanders. Use of airborne transmission precautions during cardiopulmonary resuscitation may confer rescuer protection but risks patient harm due to delays in commencing treatment. To quantify the risk of respiratory aerosol generation during cardiopulmonary resuscitation in humans, we conducted an aerosol monitoring study during out-of-hospital cardiac arrests. Exhaled aerosol was recorded using an optical particle sizer spectrometer connected to the breathing system. Aerosol produced during resuscitation was compared with that produced by control participants under general anaesthesia ventilated with an equivalent respiratory pattern to cardiopulmonary resuscitation. A porcine cardiac arrest model was used to determine the independent contributions of ventilatory breaths, chest compressions and external cardiac defibrillation to aerosol generation. Time-series analysis of participants with cardiac arrest (n = 18) demonstrated a repeating waveform of respiratory aerosol that mapped to specific components of resuscitation. Very high peak aerosol concentrations were generated during ventilation of participants with cardiac arrest with median (IQR [range]) 17,926 (5546-59,209 [1523-242,648]) particles.l-1 , which were 24-fold greater than in control participants under general anaesthesia (744 (309-2106 [23-9099]) particles.l-1 , p < 0.001, n = 16). A substantial rise in aerosol also occurred with cardiac defibrillation and chest compressions. In a complimentary porcine model of cardiac arrest, aerosol recordings showed a strikingly similar profile to the human data. Time-averaged aerosol concentrations during ventilation were approximately 270-fold higher than before cardiac arrest (19,410 (2307-41,017 [104-136,025]) vs. 72 (41-136 [23-268]) particles.l-1 , p = 0.008). The porcine model also confirmed that both defibrillation and chest compressions generate high concentrations of aerosol independent of, but synergistic with, ventilation. In conclusion, multiple components of cardiopulmonary resuscitation generate high concentrations of respiratory aerosol. We recommend that airborne transmission precautions are warranted in the setting of high-risk pathogens, until the airway is secured with an airway device and breathing system with a filter.

Dataset Information

Automatic Detection of Ventilations During Mechanical Cardiopulmonary Resuscitation.

Publications

Automatic Detection of Ventilations During Mechanical Cardiopulmonary Resuscitation.

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