Abstract 157: Multicenter Evaluation of Etiology and Observed Transition Intensities Between Pulseless Electrical Activity and Return of Spontaneous Circulation

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_4) ◽  
Author(s):  
Eirik Unneland ◽  
Anders Norvik ◽  
Shaun K. McGovern ◽  
David G. Buckler ◽  
Unai Irusta ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Electrical Activity ◽  
Additive Model ◽  
Pulseless Electrical Activity ◽  
Spontaneous Circulation ◽  
Time To Event ◽  
Transition Intensity ◽  
Time To Event Data ◽  
Current State ◽  
Average Patient

Background: Cardiac arrest presents with one of three clinical states; Cardiac standstill (asystole), Pulseless Electrical Activity (PEA), or ventricular fibrillation/tachycardia (VF/VT). PEA results from multiple etiologies and accounts for most in-hospital cardiac arrests. We quantified the dynamic nature of transitions in and out of PEA, in terms of hospital sites and presumed etiology. Methods: We analyzed 538 episodes of cardiac arrest at one Norwegian hospital and three U.S. hospitals. ECG, chest compressions and ventilations were recorded by defibrillators during CPR. Each event was assessed using a graphical application. We quantified the transition intensity, i.e. the immediate probability of a transition given the current state, between PEA and ROSC using Aalen’s additive model for time-to-event data. Results: The overall transition intensity from PEA to ROSC was about 0.10 min -1 , so an average patient in PEA has about 10 % chance to gain ROSC the following 1 minute. The intensity peaked at 7 minutes of CPR (Figure), with some heterogeneity between hospitals (0.07 to 0.11 min -1 ). The reverse transition intensity from ROSC to PEA was rather constant at 0.10 min -1 (range 0.05-0.11). Information regarding assumed cardiac or non-cardiac etiology was available in 208 episodes (123 cardiac). Patients with a cardiac etiology had a marginally smaller (-0.03 min -1 ) chance of making the transition from PEA to ROSC (p=0.049), but etiology did not impact on the ROSC to PEA transition (p=0.39). Discussion: For transitions between PEA and ROSC we observed an overall intensity of 0.1 min -1 , with some hospital heterogeneity. This may be due to heterogeneity in the underlying patient populations. We found the probability of transitioning from PEA to ROSC to increase from the start event recording until an average peak intensity at 7 minutes. This information may increase the clinicians’ understanding of the process from PEA to ROSC.

Abstract 13102: Outcomes of Primary and Secondary Pulseless Electrical Activity During In-Hospital Cardiac Arrest

Circulation ◽  
2021 ◽  
Vol 144 (Suppl_2) ◽  
Author(s):  
Eirik Unneland ◽  
Anders Norvik ◽  
Shaun McGovern ◽  
David Buckler ◽  
Unai Irusta ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Electrical Activity ◽  
Additive Model ◽  
Pulseless Electrical Activity ◽  
Spontaneous Circulation ◽  
Clinical State ◽  
Time To Event ◽  
Time To Event Data ◽  
Average Patient ◽  
Hospital Cardiac Arrest

Background: Pulseless Electrical Activity (PEA) is common during in-hospital cardiac arrest. We investigated the development of four types of PEA: PEA as presenting clinical state (primary) and PEA secondary to transient return of spontaneous circulation (ROSC), ventricular fibrillation/tachycardia (VF/VT), or asystole (ASY). Methods: We analyzed 660 episodes of cardiac arrest at one Norwegian and three U.S. hospitals. ECG, chest compressions and ventilations were recorded by defibrillators during CPR. Clinical states were annotated using a graphical application. We quantified the transition intensities from PEA to ROSC (i.e. the immediate probability of a transition), and the observed half-lives for the four types of PEA (i.e. how quickly PEA develops into another clinical state), using Aalen’s additive model for time-to-event data. Results: The transition intensities to ROSC from primary PEA (n=386) and secondary PEA after ASY (n=226) were about 0.08 per minute, peaking at 6 and 9 min, respectively (figure, left). Thus, an average patient in these types of PEA has about 8% chance to achieve ROSC in one minute. Much higher transition intensities to ROSC of about 0.20 per min were observed for secondary PEA after transient ROSC (n=209) or VF/VT (n=225), peaking at 10 and 5 min, respectively. Half-live times for the four types of PEA (figure, right) were 8.5 min, 6.8 min, 4.6 min and 1.6 min, for primary PEA, and secondary PEA after ASY, transient ROSC and VF/VT, respectively. Discussion: The observed clinical development of PEA in terms of intensity, peak intensity and half-lives during resuscitation differs substantially between the four types of PEA. The chance of obtaining ROSC is considerably lower in primary PEA or PEA after ASY, compared to PEA following transient ROSC or after VF/VT. This may increase understanding of the nature of PEA and the process leading to ROSC; and allow for simple prognostic assessments during a resuscitation attempt.

Abstract 284: Looking Back to Glance Ahead: The Impact of Last Minute's Qrs Width & Frequency in Pulseless Electrical Activity

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_4) ◽  
Author(s):  
Anders Norvik ◽  
Eirik Unneland ◽  
Gunnar W Skjeflo ◽  
David Buckler ◽  
Unai Irusta ◽  
...  
Keyword(s):  
Heart Rate ◽  
Electrical Activity ◽  
Additive Model ◽  
Pulseless Electrical Activity ◽  
Transition Intensity ◽  
Current Time ◽  
Visual Appearance ◽  
Time To Event Data ◽  
Average Transition ◽  
The Impact

Background: Observed heart rate and QRS-width during CPR in Pulseless Electrical Activity (PEA) develop differently in patients who gain ROSC compared to those who do not. In this study we investigated the impact of heart rate and QRS width on the transition from PEA to ROSC. Method: Defibrillator data from 293 episodes of cardiac arrest at two US and one Norwegian hospital were reviewed. The files contained ECG, impedance signal and compression depth. In total 178 episodes containing PEA intervals were included. Episodes with excessive ECG noise and signs of an active pacemaker were excluded. The files were processed in a MATLAB graphical application, and the clinical states were determined based on clinical documentation and the visual appearance of the ECG. ROSC was defined as an organized rhythm lasting longer than 1 minute without ongoing compressions. During pauses in compressions, heart rate and QRS-width was automatically measured and averaged over the preceding minute until current time and controlled and corrected manually. The results were analyzed using Aalen’s additive model for time-to-event data, using R version 3.6.3. Results: The average transition intensity, corresponding to the probability of gaining ROSC in one minute, was about 0.20 per min of CPR peaking at approximately 7 min. An increase in the average heart rate by 10/min increased the transition intensity by 0.03/min (p <0.01). Narrowing of the QRS in average by 100 milliseconds (ms) increased the transition intensity by 0.14/min (p <0.01). Our figure shows QRS width and heart rate for one patient with PEA approaching ROSC (gray area), with smoothed curves overlaid. Conclusion: Higher heart rates and narrower QRS complexes during PEA are strongly and significantly associated with a transition from PEA to ROSC. These changes could indicate whether a patient responds to ongoing CPR. In addition, there is a potential for predicting the immediate outcome based on these ECG characteristics.

scholarly journals A Machine Learning Model for the Prognosis of Pulseless Electrical Activity during Out-of-Hospital Cardiac Arrest

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 847
Author(s):  
Jon Urteaga ◽  
Elisabete Aramendi ◽  
Andoni Elola ◽  
Unai Irusta ◽  
Ahamed Idris
Keyword(s):  
Machine Learning ◽  
Cardiac Arrest ◽  
Electrical Activity ◽  
Area Under The Curve ◽  
Pulseless Electrical Activity ◽  
Learning Model ◽  
Spontaneous Circulation ◽  
Machine Learning Model ◽  
Balance Accuracy ◽  
Hospital Cardiac Arrest

Pulseless electrical activity (PEA) is characterized by the disassociation of the mechanical and electrical activity of the heart and appears as the initial rhythm in 20–30% of out-of-hospital cardiac arrest (OHCA) cases. Predicting whether a patient in PEA will convert to return of spontaneous circulation (ROSC) is important because different therapeutic strategies are needed depending on the type of PEA. The aim of this study was to develop a machine learning model to differentiate PEA with unfavorable (unPEA) and favorable (faPEA) evolution to ROSC. An OHCA dataset of 1921 5s PEA signal segments from defibrillator files was used, 703 faPEA segments from 107 patients with ROSC and 1218 unPEA segments from 153 patients with no ROSC. The solution consisted of a signal-processing stage of the ECG and the thoracic impedance (TI) and the extraction of the TI circulation component (ICC), which is associated with ventricular wall movement. Then, a set of 17 features was obtained from the ECG and ICC signals, and a random forest classifier was used to differentiate faPEA from unPEA. All models were trained and tested using patientwise and stratified 10-fold cross-validation partitions. The best model showed a median (interquartile range) area under the curve (AUC) of 85.7(9.8)% and a balance accuracy of 78.8(9.8)%, improving the previously available solutions at more than four points in the AUC and three points in balanced accuracy. It was demonstrated that the evolution of PEA can be predicted using the ECG and TI signals, opening the possibility of targeted PEA treatment in OHCA.

scholarly journals P003: Which factors predict resuscitation outcomes in patients arriving to the emergency department in cardiac arrest? A SHoC series study

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S57-S58
Author(s):  
P. Atkinson ◽  
N. Beckett ◽  
D. Lewis ◽  
J. Fraser ◽  
A. Banerjee ◽  
...  
Keyword(s):  
Emergency Department ◽  
Cardiac Arrest ◽  
Electrical Activity ◽  
Odds Ratio ◽  
Cardiac Rhythm ◽  
Point Of Care ◽  
Pulseless Electrical Activity ◽  
Spontaneous Circulation ◽  
Point Of Care Ultrasound ◽  
Successful Resuscitation

Introduction: The decision as to whether to end resuscitation for pre-hospital cardiac arrest (CA) patients in the field or in the emergency department (ED) is commonly made based upon standard criteria. We studied the reliability of several easily determined criteria as predictors of resuscitation outcomes in a population of adults in CA transported to the ED. Methods: A retrospective database and chart analysis was completed for patients arriving to a tertiary ED in cardiac arrest, between 2010 and 2014. Patients were excluded if aged under 19. Multiple data were abstracted from charts using a standardized form. Regression analysis was used to compare criteria that predicted return of spontaneous circulation (ROSC) and survival to hospital admission (SHA). Results: 264 patients met the study inclusion criteria. Logistic regression was used to identify predictors of ROSC and SHA. The criteria that emerged as significant predictors for ROSC included; longer ED resuscitation time (Odds ratio 1.11 (1.06- 1.18)), witnessed arrest (Odds ratio 9.43 (2.58- 53.0)) and having an initial cardiac rhythm of Pulseless Electrical Activity (Odds Ratio 3.23 (1.07-9.811)) over Asystole. Receiving point of care ultrasound (PoCUS; Odds ratio 0.22 (0.07-0.69)); and having an initial cardiac rhythm of Pulseless Electrical Activity (Odds Ratio 4.10 (1.43-11.88)) were the significant predictors for SHA. Longer times for ED resuscitation was close to reaching significance for predicting SHA Conclusion: Our results suggest that both fixed and adaptable factors, including increasing resuscitation time, and PoCUS use in the ED were important independent predictors of successful resuscitation. Several commonly used criteria were unreliable predictors.

Abstract 166: Physiological Effects of Adrenaline in Human Cardiac Arrest With Pulseless Electrical Activity: A Pilot Study

Circulation ◽  
2019 ◽  
Vol 140 (Suppl_2) ◽  
Author(s):  
Magnus Bakke ◽  
Alexander Borgen ◽  
Anders Norvik ◽  
Gunnar W Skjeflo ◽  
Unai Irusta ◽  
...  
Keyword(s):  
Heart Rate ◽  
Cardiac Arrest ◽  
Pilot Study ◽  
Electrical Activity ◽  
Ad Hoc ◽  
Pulseless Electrical Activity ◽  
Spontaneous Circulation ◽  
Qrs Duration ◽  
The Individual ◽  
Adrenaline Administration

Introduction: During resuscitation from cardiac arrest with Pulseless Electrical Activity (PEA), studies show that adrenaline facilitates return of spontaneous circulation (ROSC) and possibly leads to an isolated increase in the heart rate (HR). In this study, we investigated the immediate effects of adrenaline on ECG characteristics; HR and QRS duration (duration of ventricle depolarization). Method: We studied 19 ECG segments of 300 s duration from emergency defibrillators in 10 adult patients during resuscitation from in-hospital cardiac arrest. Information on the exact timing of adrenaline administration (between 0.5 and 1 mg i.v.) was obtained from the defibrillators or the emergency personnel involved. HR (1/min) and QRS duration (ms) were annotated and registered using an ad-hoc Matlab (Mathworks, Natic, MA) graphical Data Annotator, and interpolated linearly between individual observations. Trends were identified with LOWESS. Results: The plots show the individual observations (red points) along with the trends (blue lines) of HR and QRS Duration during resuscitation, relative to the time of adrenaline administration. We observed a gradual increase in heart rate (peaking at 150 s after adrenaline administration) and a more pronounced narrowing of the QRS (levelling off also at about 150 s). Discussion: In this pilot study, administration of adrenaline was associated with narrowing of the QRS complex, while the relation to heart rate was less apparent. A limitation is that no adjustment for the individual patient’s trajectory was made. However, the results are fairly consistent with earlier studies on out-of-hospital resuscitation, when adrenaline was typically given much later.

Abstract 052: Improved Hospital Outcomes With Hypokalemia on Admission in Cardiac Arrest Survivors Treated With Therapeutic Hypothermia

2017 ◽  
Vol 10 (suppl_3) ◽  
Author(s):  
Angelo de la Rosa ◽  
Manuel Tapia ◽  
Yong Ji ◽  
Basil Saour ◽  
Mikhail Torosoff
Keyword(s):  
Logistic Regression ◽  
Cardiac Arrest ◽  
Ventricular Fibrillation ◽  
Hospital Mortality ◽  
Electrical Activity ◽  
Therapeutic Hypothermia ◽  
Multivariate Logistic Regression Analysis ◽  
Pulseless Electrical Activity ◽  
Older Age ◽  
Chi Square

Purpose: We hypothesized that advanced circulatory compromise, as manifested by acidosis and hyperkalemia should be associated with worsened clinical outcomes in cardiac arrest patients treated with therapeutic hypothermia. Methods: Results of initial admission laboratory studies, medical history, and echocardiogram in 203 consecutive cardiac arrest patients (59 females, 59+/- 15 years old) undergoing therapeutic hypothermia were reviewed. Mortality was ascertained through hospital records. ANOVA, chi-square, Kaplan-Meier, and logistic regression analyses were used. The study was approved by the institutional IRB. Results: Increased mortality was noted with older age, decreased admission pH, elevated admission lactate, lower admission hemoglobin, and pulseless electrical activity or asystole as presenting rhythms (Table). Admission hypokalemia and ventricular fibrillation/tachycardia were associated with improved hospital mortality (Table). Potassium was significantly lower in patients admitted with ventricular fibrillation/tachycardia (3.897+/-0.92) as compared to patients with asystole (4.674+/-1.377) or pulseless electrical activity (4.491+/-1.055 mEq/dL, p<0.0001). In multivariate logistic regression analysis, independent predictors of increased hospital mortality included increased admission potassium (OR 2.0, 95%CI 1.291-3.170, p=0.002)), older age (OR 1.04, 95%CI 1.007-1.071, p=0.017), admission PEA (OR 3.7, 95%CI 1.358-10.282, p=0.011 when compared to ventricular fibrillation/tachycardia) or asystole (OR 17.2, 95%CI 4.423-66.810, p<0.001 when compared to ventricular fibrillation/tachycardia); while decreased mortality was associated with higher hemoglobin (OR 0.8, 95%CI 0.665-0.997, p=0.047). Conclusions: Hyperkalemia, pulseless electrical activity, and asystole are predictive of increased hospital mortality in survivors of cardiac arrest. An association between low or low-normal potassium, observed VT-VF, and better outcomes is unexpected and may be used for prognostic purposes. More prospective investigations of mortality predictors in these critically ill patients are needed.

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