Deep Neural Networks for ECG-Based Pulse Detection during Out-of-Hospital Cardiac Arrest

The automatic detection of pulse during out-of-hospital cardiac arrest (OHCA) is necessary for the early recognition of the arrest and the detection of return of spontaneous circulation (end of the arrest). The only signal available in every single defibrillator and valid for the detection of pulse is the electrocardiogram (ECG). In this study we propose two deep neural network (DNN) architectures to detect pulse using short ECG segments (5 s), i.e., to classify the rhythm into pulseless electrical activity (PEA) or pulse-generating rhythm (PR). A total of 3914 5-s ECG segments, 2372 PR and 1542 PEA, were extracted from 279 OHCA episodes. Data were partitioned patient-wise into training (80%) and test (20%) sets. The first DNN architecture was a fully convolutional neural network, and the second architecture added a recurrent layer to learn temporal dependencies. Both DNN architectures were tuned using Bayesian optimization, and the results for the test set were compared to state-of-the art PR/PEA discrimination algorithms based on machine learning and hand crafted features. The PR/PEA classifiers were evaluated in terms of sensitivity (Se) for PR, specificity (Sp) for PEA, and the balanced accuracy (BAC), the average of Se and Sp. The Se/Sp/BAC of the DNN architectures were 94.1%/92.9%/93.5% for the first one, and 95.5%/91.6%/93.5% for the second one. Both architectures improved the performance of state of the art methods by more than 1.5 points in BAC.This work was supported by: The Spanish Ministerio de Economía y Competitividad, TEC2015-64678-R, jointly with the Fondo Europeo de Desarrollo Regional (FEDER), UPV/EHU via GIU17/031 and the Basque Government through the grant PRE_2018_2_0260

Applications of the Transthoracic Impedance Signal during Resuscitation

Defibrillators acquire both the ECG and the transthoracic impedance (TI) signal through defibrillation pads. TI represents the resistance of the thorax to current flow, and is measured by defibrillators to check that defibrillation pads are correctly attached to the chest of the patient. Additionally, some defibrillators use the TI measurement to adjust the energy of the defibrillation pulse. Changes in tissue composition due to redistribution and movement of fluids induce fluctuations in the TI. Blood flow during the cardiac cycle generates small fluctuations synchronized to each heartbeat. Respiration (or assisted ventilation) also causes changes in the TI. Additionally, during cardiopulmonary resuscitation (CPR), chest compressions cause a disturbance in the electrode-skin interface, inducing artifacts in the TI signal. These fluctuations may provide useful information regarding CPR quality, length of pauses in chest compressions (no flow time), presence of circulation, etc. This chapter explores the new applications of the transthoracic impedance signal acquired through defibrillation pads during resuscitative attempts

Cardiac rhythm analysis during ongoing cardiopulmonary resuscitation using the Analysis During Compressions with Fast reconfirmation technology

BACKGROUND Pauses in chest compressions (CCs) have a negative association with survival from cardiac arrest. Electrocardiographic (ECG) rhythm analysis and defibrillator charging are significant contributors to CC pauses. OBJECTIVE Accuracy of the Analysis During Compressions with Fast Reconfirmation (ADC-FR) algorithm, which features automated rhythm analysis and charging during CCs to reduce CC pauses, was retrospectively determined in a large database of ECGs from 2701 patients with out-of-hospital cardiac arrest. METHODS The ADC-FR algorithm generated a total of 7264 advisories, of which 3575 were randomly assigned to a development data set and 3689 to a test data set. With ADC-FR, a high-pass digital filter is used to remove CC artifacts, while the underlying ECG rhythm is automatically interpreted. When CCs are paused at the end of the 2-minute cardiopulmonary resuscitation interval, a 3-second reconfirmation analysis is performed using the artifact-free ECG to confirm the shock/no-shock advisory. The sensitivity and specificity of the ADC-FR algorithm in correctly identifying shockable/nonshockable rhythms during CCs were calculated. RESULTS In both data sets, the accuracy of the ADC-FR algorithm for each ECG rhythm exceeded the recommended performance goals, which apply to a standard artifact-free ECG analysis. Sensitivity and specificity were 97% and 99%, respectively, for the development data set and 95% and 99% for the test data set. CONCLUSION The ADC-FR algorithm is highly accurate in discriminating shockable and nonshockable rhythms and can be used to reduce CC pauses

Feasibility of waveform capnography as a non-invasive monitoring tool during cardiopulmonary resuscitation

178 p.Sudden cardiac arrest (SCA) is one of the leading causes of death in the industrialized world and it includes the sudden cessation of circulation and consciousness, confirmed by the absence of pulse and breathing. Cardiopulmonary resuscitation (CPR) is one of the key interventions for patient survival after SCA, a life-saving procedure that combines chest compressions and ventilations to maintain a minimal oxygenated blood flow.To deliver oxygen, an adequate blood flow must be generated, by effective CPR, during the majority of the cardiac arrest time. Although monitoring the quality of CPR performed by rescuers during cardiac arrest has been a huge step forward in resuscitation science, in 2013, a consensus statement from the American Heart Association prioritized a new type of CPR quality monitoring focused on the physiological response of the patient instead of how the rescuer is doing.To that end, current resuscitation guidelines emphasize the use of waveform capnography during CPR for patient monitoring. Among several advantages such as ensure correct tube placement, one of its most important roles is to monitor ventilation rate, helping to avoid potentially harmful over-ventilation. In addition, waveform capnography would enable monitoring CPR quality, early detection of ROSC and determining patient prognosis. However, several studies have reported the appearance of fast oscillations superimposed on the capnogram, hereinafter CC-artifact, which may hinder a feasible use of waveform capnography during CPR. In addition to the possible lack of reliability, several factors need to be taken into account when interpreting ETCO2 measurements. Chest compressions and ventilation have opposing effects on ETCO2 levels. Chest compressions increase CO2 concentration, delivering CO2 from the tissues to the lungs, whilst ventilations remove CO2 from the lungs, decreasing ETCO2. Thus, ventilation rate acts as a significant confounding factor.This thesis analyzes the feasibility of waveform capnography as non-invasive monitoring tool of the physiological response of the patient to resuscitation efforts. A set of four intermediate goals was defined.First, we analyzed the incidence and morphology of the CC-artifact and assessed its negative influence in the detection of ventilations and in ventilation rate and ETCO2 measurement. Second, several artifact suppression techniques were used to improve ventilation detection and to enhance capnography waveform. Third, we applied a novel strategy to model the impact of ventilations and ventilation rate on the exhaled CO2 measured in out-of-hospital cardiac arrest capnograms, which could allow to measure the change in ETCO2 attributable to chest compressions by removing the influence of concurrent ventilations. Finally, we studied if the assessment of the ETCO2 trends during chest compressions pauses could allow to detect return of spontaneous circulation, a metric that could be useful as an adjunct to other decision tool

Impact of Transitory ROSC Events on Neurological Outcome in Patients with Out-of-Hospital Cardiac Arrest

In out-of-hospital cardiac arrest (OHCA), the occurrence of temporary periods of return to spontaneous circulation (t-ROSC) has been found to be predictive of survival to hospital discharge. The relationship between the duration of t-ROSCs and OHCA outcome has not been explored yet. The aim of this prospective observational study was to analyze the duration of t-ROSCs during OHCA and its impact on outcome. Defibrillator-recorded OHCA events were analyzed via dedicated software. The number of t-ROSC episodes and their overall durations were recorded. The study endpoint was the good neurologic outcome at hospital discharge. Among 285 patients included in the study, 45 (15.8%) had one or more t-ROSCs. The likelihood of t-ROSC occurrence was higher in patients with a shockable rhythm (p = 0.009). The cumulative length of t-ROSC episodes was significantly higher for patients who achieved sustained ROSC (p < 0.001). The adjusted cumulative t-ROSC length was an independent predictor for good neurological outcome at hospital discharge (OR 1.588, 95% CI 1.017 to 2.481; p = 0.042). According to our findings and data from previous studies, t-ROSC episodes during OHCA should be considered as a favorable prognostic factor, encouraging continuing resuscitative efforts

Effects of a First Responders Automatic External Defibrillator (AED) program on patient Outcomes in a Rural Emergency Medical Service System

Background For patients in cardiac arrest the most important variable in survival is rapid activation of emergency medical services to provide early defibrillation. Previous studies have indicated that for the greatest chance of survival the patient must be defibrillated within six minutes of collapse. In September of 2002 the Fairmont police department placed AED\u27s in the medical kits of their officers in an effort to improve the chances of survival for the cardiac arrest patients in the city. This study is an attempt to gauge the success of this AED program by Iooking at multiple variables in the care of cardiac arrest patients. Methods A retrospective chart review study was undertaken and data was captured from patient care documents. An equal number of cardiac arrests (18) were taken from before and after the AED program was initiated for a total of 36 patients in the study. Results Statistical significant was found in the time from 911 dispatch to defibrillator placement and analysis,3.4 min in the pre-AED group vs. 5.2 min in the post AED group (P=0.03). No significance was found in patient outcomes in comparison to the pre-AED period Discussion Although there was no change in the patient outcomes after the AED program was initiated, a closer look at the data shows that a decrease in the amount of time it took to get to the patients side was accomplished, given more time and data points, it is possible that an increase in patient survival might be seen. Focus for the next study would be an attempt to decrease the time from collapse to patient defibrillation

Out-of-hospital cardiac arrest in the Algarve region of Portugal: a retrospective registry trial with outcome data

Background and importanceOut-of-hospital cardiac arrest is a leading cause of death in Europe. An understanding of region-specific factors is essential for informing strategies to improve survival. DesignThis retrospective observational study included all out-of-hospital cardiac arrest patients attended by the Emergency Medical Service of the Algarve in 2019. Outcome data were derived from hospital records. Main resultsIn 2019, there were 850 out-of-hospital cardiac arrests treated with cardiopulmonary resuscitation in the Algarve, representing a population incidence of 189/100 000. Return of spontaneous circulation occurred in 83 patients (9.8%), of whom 17 (2.0%) had survival to hospital discharge and 15 (1.8%) had survival with good neurologic outcome. Among patients in the Utstein comparator group, survival to hospital discharge was 21.4%. Predictors of return of spontaneous circulation were age, witnessed arrest, initial shockable rhythm, time of year, time to cardiopulmonary resuscitation, and time to advanced life support. Predictors of survival to hospital discharge were age, initial shockable rhythm, time to rhythm analysis, and time to advanced life support. Predictors of survival with good neurologic outcome were age, initial shockable rhythm, and time to return of spontaneous circulation. ConclusionsThe incidence of out-of-hospital cardiac arrest with cardiopulmonary resuscitation in the Algarve was higher than in other jurisdictions while return of spontaneous circulation, survival to hospital discharge, and survival with good neurologic outcome were comparatively low. An aging population, a geographically diverse region, and a low incidence of bystander cardiopulmonary resuscitation may have contributed to these outcomes. These results confirm the importance of early cardiopulmonary resuscitation, early rhythm assessment, and early advanced life support, all of which are potentially modifiable through public education, broadening of the defibrillator network and increased availability of advanced life support teams.info:eu-repo/semantics/publishedVersio

Noninvasive Monitoring of Manual Ventilation during Out-of- Hospital Cardiopulmonary Resuscitation

Cardiopulmonary resuscitation (CPR) consisting of chest compressions and assisted ventilation is crucial to treat out-of-hospital cardiac arrest (OHCA). It is well reported that quality of manual ventilations, in terms of rate and volume, is suboptimal, with a high incidence of hyperventilation, which is linked to poor outcomes. The lack of a noninvasive technology to monitor ventilations during out-of-hospital CPR precludes feedback on ventilations to the rescuer, and it handicaps the evaluation of the effect of ventilations on the outcome of the patient. This chapter addresses the possibilities and challenges of monitoring the quality of manual ventilations in current defibrillators. Methods are proposed to monitor ventilations based on the thoracic impedance and the capnogram. These methods can be integrated in defibrillators used in both basic and advanced life support. The algorithms are described, and the accuracy of the methods to monitor the ventilation rate and the quality metrics of the ventilations is reported using real OHCA episodes. The accuracy and limitations of the methods as well as the implications of integrating them in the treatment of patients in cardiac arrest are discussed

Feasibility of waveform capnography as a non-invasive monitoring tool during cardiopulmonary resuscitation

178 p.Sudden cardiac arrest (SCA) is one of the leading causes of death in the industrialized world and it includes the sudden cessation of circulation and consciousness, confirmed by the absence of pulse and breathing. Cardiopulmonary resuscitation (CPR) is one of the key interventions for patient survival after SCA, a life-saving procedure that combines chest compressions and ventilations to maintain a minimal oxygenated blood flow.To deliver oxygen, an adequate blood flow must be generated, by effective CPR, during the majority of the cardiac arrest time. Although monitoring the quality of CPR performed by rescuers during cardiac arrest has been a huge step forward in resuscitation science, in 2013, a consensus statement from the American Heart Association prioritized a new type of CPR quality monitoring focused on the physiological response of the patient instead of how the rescuer is doing.To that end, current resuscitation guidelines emphasize the use of waveform capnography during CPR for patient monitoring. Among several advantages such as ensure correct tube placement, one of its most important roles is to monitor ventilation rate, helping to avoid potentially harmful over-ventilation. In addition, waveform capnography would enable monitoring CPR quality, early detection of ROSC and determining patient prognosis. However, several studies have reported the appearance of fast oscillations superimposed on the capnogram, hereinafter CC-artifact, which may hinder a feasible use of waveform capnography during CPR. In addition to the possible lack of reliability, several factors need to be taken into account when interpreting ETCO2 measurements. Chest compressions and ventilation have opposing effects on ETCO2 levels. Chest compressions increase CO2 concentration, delivering CO2 from the tissues to the lungs, whilst ventilations remove CO2 from the lungs, decreasing ETCO2. Thus, ventilation rate acts as a significant confounding factor.This thesis analyzes the feasibility of waveform capnography as non-invasive monitoring tool of the physiological response of the patient to resuscitation efforts. A set of four intermediate goals was defined.First, we analyzed the incidence and morphology of the CC-artifact and assessed its negative influence in the detection of ventilations and in ventilation rate and ETCO2 measurement. Second, several artifact suppression techniques were used to improve ventilation detection and to enhance capnography waveform. Third, we applied a novel strategy to model the impact of ventilations and ventilation rate on the exhaled CO2 measured in out-of-hospital cardiac arrest capnograms, which could allow to measure the change in ETCO2 attributable to chest compressions by removing the influence of concurrent ventilations. Finally, we studied if the assessment of the ETCO2 trends during chest compressions pauses could allow to detect return of spontaneous circulation, a metric that could be useful as an adjunct to other decision tool