Pulseless Electrical Activity in In-Hospital Cardiac Arrest – A crossroad for decisions

Machine learning model to predict evolution of pulseless electrical activity during in-hospital cardiac arrest

Background

During pulseless electrical activity (PEA) the cardiac mechanical and electrical functions are dissociated, a phenomenon occurring in 25-42% of in-hospital cardiac arrest (IHCA) cases. Accurate evaluation of the likelihood of a PEA patient transitioning to return of spontaneous circulation (ROSC) may be vital for the successful resuscitation.

The aim

We sought to develop a model to automatically discriminate between PEA rhythms with favorable and unfavorable evolution to ROSC.

Methods

A dataset of 190 patients, 120 with ROSC, were acquired with defibrillators from different vendors in three hospitals. The ECG and the transthoracic impedance (TTI) signal were processed to compute 16 waveform features. Logistic regression models where designed integrating both automated features and characteristics annotated in the QRS to identify PEAs with better prognosis leading to ROSC. Cross validation techniques were applied, both patient-specific and stratified, to evaluate the performance of the algorithm.

Results

The best model consisted in a three feature algorithm that exhibited median (interquartile range) Area Under the Curve/Balanced accuracy/Sensitivity/Specificity of 80.3(9.9)/75.6(8.0)/ 77.4(15.2)/72.3(16.4) %, respectively.

Conclusions

Information hidden in the waveforms of the ECG and TTI signals, along with QRS complex features, can predict the progression of PEA. Automated methods as the one proposed in this study, could contribute to assist in the targeted treatment of PEA in IHCA.

Non-shockable rhythms: A parametric model for the immediate probability of return of spontaneous circulation

BACKGROUND

Cardiac arrest can present with asystole, Pulseless Electrical Activity (PEA), or Ventricular Fibrillation/Tachycardia (VF/VT). We investigated the transition intensity of Return of spontaneous circulation (ROSC) from PEA and asystole during in-hospital resuscitation.

MATERIALS AND METHODS

We included 770 episodes of cardiac arrest. PEA was defined as ECG with >12 QRS complexes per min, asystole by an isoelectric signal >5 seconds. The observed times of PEA to ROSC transitions were fitted to five different parametric time-to-event models. At values ≤0.1, transition intensities roughly represent next-minute probabilities allowing for direct interpretation. Different entities of PEA and asystole, dependent on whether it was the primary or a secondary rhythm, were included as covariates.

RESULTS

The transition intensities to ROSC from primary PEA and PEA after asystole were unimodal with peaks of 0.12 at 3 min and 0.09 at 6 min, respectively. Transition intensities to ROSC from PEA after VF/VT, or following transient ROSC, exhibited high initial values of 0.32 and 0.26 at 3 minutes, respectively, but decreased. The transition intensity to ROSC from initial asystole and asystole after PEA were both about 0.01 and 0.02; while asystole after VF/VT had an intensity to ROSC of 0.15 initially which decreased. The transition intensity from asystole after temporary ROSC was constant at 0.08.

CONCLUSION

The immediate probability of ROSC develops differently in PEA and asystole depending on the preceding rhythm and the duration of the resuscitation attempt. This knowledge may aid simple bedside prognostication and electronic resuscitation algorithms for monitors/defibrillators.

Dynamic Course of Clinical State Transitions in Patients Undergoing Advanced Life Support after Out-of-Hospital Cardiac Arrest

OBJECTIVES

Studies of out-of-hospital cardiac arrest generally document the presenting (pulseless electrical activity [PEA], ventricular fibrillation/tachycardia (VF/VT), asystole), and the final states (resuming stable spontaneous circulation [s-ROSC], being declared dead). Only a few studies described the transitions between clinical states during advanced life support (ALS). The aim of this study was to describe and analyze the dynamics of state transitions during ALS.

METHODS

A retrospective analysis of 464 OHCA events was conducted. Any observed state and its corresponding changing time were documented through continuous electrocardiographic and trans-thoracic impedance recording.

RESULTS

When achieved, most s-ROSCs were obtained by 30 min, regardless of the presenting state. After this time point, the persistence of any transient state was associated with a great probability of being declared dead. The most probable change for VF/VT or PEA at any time was the transition to asystole (36.4% and 34.4%, respectively); patients in asystole at any time had a 70% probability of death. Patients achieving s-ROSC mostly came from a VF/VT state.In most cases, the presenting rhythm tended to persist over time during ALS. Asystole was the most stable state; a higher degree of instability was observed when the presenting rhythms were VF/VT or PEA. Transient ROSC episodes occurred mainly as the first transition after the presenting state, especially for initial PEA.

CONCLUSIONS

An understanding of the dynamic course of clinical state transitions during ALS may allow treatment strategies to be tailored in patients affected by OHCA.

Hands-free continuous carotid Doppler ultrasound for detection of the pulse during cardiac arrest in a porcine model

Background/Purpose

Pulse palpation is an unreliable method for diagnosing cardiac arrest. To address this limitation, continuous hemodynamic monitoring may be a viable solution. Therefore, we developed a novel, hands-free Doppler system, RescueDoppler, to detect the pulse continuously in the carotid artery.

Methods

In twelve pigs, we evaluated RescueDoppleŕs potential to measure blood flow velocity in three situations where pulse palpation of the carotid artery was insufficient: (1) systolic blood pressure below 60 mmHg, (2) ventricular fibrillation (VF) and (3) pulseless electrical activity (PEA). (1) Low blood pressure was induced using a Fogarty balloon catheter to occlude the inferior vena cava. (2) An implantable cardioverter-defibrillator induced VF. (3) Myocardial infarction after microembolization of the left coronary artery caused True-PEA. Invasive blood pressure was measured in the contralateral carotid artery. Time-averaged blood flow velocity (TAV) in the carotid artery was related to mean arterial pressure (MAP) in a linear mixed model.

Results

RescueDoppler identified pulsatile blood flow in 41/41 events with systolic blood pressure below 60 mmHg, with lowest blood pressure of 19 mmHg. In addition the absence of spontaneous circulation was identified in 21/21 VF events and true PEA in 2/2 events. The intraclass correlation coefficient within animals for TAV and MAP was 0.94 (95% CI. 0.85-0.98).

Conclusions

In a porcine model, RescueDoppler reliably identified pulsative blood flow with blood pressures below 60 mmHg. During VF and PEA, circulatory arrest was rapidly and accurately demonstrated. RescueDoppler could potentially replace unreliable pulse palpation during cardiac arrest and cardiopulmonary resuscitation.

In-Hospital Cardiac Arrest

This article reviews the epidemiology and management of in-hospital cardiac arrest.

Characteristics and neurological survival following intraoperative cardiac arrest in a Swiss University Hospital: a 7-year retrospective observational cohort study

Introduction

Little is known about intraoperative cardiac arrest during anesthesia care. In particular, data on characteristics of cardiac arrest and neurological survival are scarce.

Methods

We conducted a single-center retrospective observational study evaluating anesthetic procedures from January 2015 until December 2021. We included patients with an intraoperative cardiac arrest and excluded cardiac arrest outside of the operating room. The primary outcome was the return of spontaneous circulation (ROSC). Secondary outcomes were sustained ROSC over 20 min, 30-day survival, and favorable neurological outcome according to Clinical Performance Category (CPC) 1 and 2.

Results

We screened 228,712 anesthetic procedures, 195 of which met inclusion criteria and were analyzed. The incidence of intraoperative cardiac arrest was 90 (CI 95% 78-103) in 100,000 procedures. The median age was 70.5 [60.0; 79.4] years, and two-thirds of patients (n = 135; 69.2%) were male. Most of these patients with cardiac arrest had ASA physical status IV (n = 83; 42.6%) or V (n = 47; 24.1%). Cardiac arrest occurred more frequently (n = 104; 53.1%) during emergency procedures than elective ones (n = 92; 46.9%). Initial rhythm was pre-dominantly non-shockable with pulseless electrical activity mostly. Most patients (n = 163/195, 83.6%; CI 95 77.6-88.5%) had at least one instance of ROSC. Sustained ROSC over 20 min was achieved in most patients with ROSC (n = 147/163; 90.2%). Of the 163 patients with ROSC, 111 (68.1%, CI 95 60.4-75.2%) remained alive after 30 days, and most (n = 90/111; 84.9%) had favorable neurological survival (CPC 1 and 2).

Conclusion

Intraoperative cardiac arrest is rare but is more likely in older patients, patients with ASA physical status ≥IV, cardiac and vascular surgery, and emergency procedures. Patients often present with pulseless electrical activity as the initial rhythm. ROSC can be achieved in most patients. Over half of the patients are alive after 30 days, most with favorable neurological outcomes, if treated immediately.

Heart rate and QRS duration as biomarkers predict the immediate outcome from pulseless electrical activity

INTRODUCTION

Pulseless electrical activity (PEA) is commonly observed in in-hospital cardiac arrest (IHCA). Universally available ECG characteristics such as QRS duration (QRSd) and heart rate (HR) may develop differently in patients who obtain ROSC or not. The aim of this study was to assess prospectively how QRSd and HR as biomarkers predict the immediate outcome of patients with PEA.

METHOD

We investigated 327 episodes of IHCA in 298 patients at two US and one Norwegian hospital. We assessed the ECG in 559 segments of PEA nested within episodes, measuring QRSd and HR during pauses of compressions, and noted the clinical state that immediately followed PEA. We investigated the development of HR, QRSd, and transitions to ROSC or no-ROSC (VF/VT, asystole or death) in a joint longitudinal and competing risks statistical model.

RESULTS

Higher HR, and a rising HR, reflect a higher transition intensity ("hazard") to ROSC (p < 0.001), but HR was not associated with the transition intensity to no-ROSC. A lower QRSd and a shrinking QRSd reflect an increased transition intensity to ROSC (p = 0.023) and a reduced transition intensity to no-ROSC (p = 0.002).

CONCLUSION

HR and QRSd convey information of the immediateoutcome during resuscitation from PEA. These universally available and promising biomarkers may guide the emergency team in tailoring individual treatment.