Comparison of Dual-Dispatch Protocols on Return of Spontaneous Circulation in Patients with Out-of-Hospital Cardiac Arrest: A Nationwide Observational Study

Objective

In South Korea, the National Fire Agency (NFA) conducted a pilot project on the advanced life support (ALS) protocol, including epinephrine administration, to improve the survival rate of out-of hospital cardiac arrest (OHCA). Therefore, this study aimed to evaluate the effect of the ALS protocol of NFA on prehospital return of spontaneous circulation (PROSC) in patients with OHCA.

Methods

This study was conducted on patients with adult-presumed cardiac arrest between January and December 2020. The main factor of interest was ambulance type according to the ALS protocol, which was divided into dedicated ALS(DA), smartphone-based ALS(SALS), and non-dedicated ALS(Non-DA), and the main analysis factor was PROSC. Multivariate logistic regression analysis was performed.

Results

During the study period, a total of 18,031 adult patients with OHCA were treated by the emergency medical service (EMS), including 7,520 (41.71 %) DA, 2,622 (14.54 %) SALS, and 7,889 (43.75 %) Non-DA. The prehospital ROSC ratio was 13.19% for the DA, 11.17% for the SALS, and 7.91% for the Non-DA ambulance (P < 0.01). Compared with that of the DA group, the odds ratio (95% confidence interval [CI]) for PROSC ratio in the SALS and Non-DA groups were 0.97 (0.82-1.15) and 0.57 (0.50-0.65), respectively. It was shown that the PROSC ratio of the DA group was higher than that of the Non-DA group and was not lower than that of the SALS group.

Conclusion

ALS protocol intervention was associated with difference in PROSC rates. Therefore, continuous efforts on the systemic implementation of the ALS protocol to improve OHCA outcomes are necessary.

Effect of COVID-19 on the prevalence of bystanders performing cardiopulmonary resuscitation: A systematic review and meta-analysis

BACKGROUND

The importance of bystander cardiopulmonary resuscitation (CPR) during out-of-hospital cardiac arrests is especially important in the context of coronavirus disease 2029 (COVID-19) because it can significantly influence survival outcomes. The objective of this meta-analysis was to examine the primary outcomes of bystander CPR during the pandemic and pre-pandemic periods.

METHODS

A search was conducted in the PubMed Central, Scopus, and EMBASE databases, as well as the Cochrane Central Register of Controlled Trials database, up to December 10, 2023. In cases where the value of I² was greater than or equal to 50% or the Q-test indicated that the p-value was less than or equal to 0.05, the studies were considered to be heterogeneous. Sensitivity assessment was performed using the leave-one-out methodology. The study protocol was registered in PROSPERO with the ID number CRD42023494912.

RESULTS

Twenty-five articles were included in this meta-analysis. Pooled analysis showed that bystander CPR frequency during the COVID-19 pandemic was 38.8%, compared to 44.8% for the pre-pandemic period (odds ratio: 1.04; 95% confidence interval: 0.93-1.16; p = 0.48).

CONCLUSIONS

The article's conclusions indicate that the COVID-19 pandemic influenced a reduction in bystander CPR compared to the pre-pandemic period, but this difference was not statistically significant. Further research is recommended to understand attitudes, including the fears of witnesses, before performing CPR on patients with suspected or confirmed infectious diseases. The study highlights the importance of bystander intervention in emergency situations and the impact of a pandemic on public health response behaviors.

Telephone-Cardiopulmonary Resuscitation Guided by a Telecommunicator: Design of a Guiding Algorithm for Telecommunicators

BACKGROUND

Out-of-hospital cardiac arrest is considered a global problem. In the last few years, there has been a growing interest in telephone-cardiopulmonary resuscitation guided by a telecommunicator. Indeed, several studies have demonstrated that it increases the chances of survival rate. This study focuses on the key points the operator should follow when performing telephone-cardiopulmonary resuscitation. The main objective of this paper is to design an algorithm to improve the telephone-cardiopulmonary resuscitation response protocol.

METHODS

The available evidence and the areas of uncertainty that have not been previously mentioned in the literature are discussed. All the information has been analyzed by two discussion groups. Later, a consensus was reached among all members. Finally, a response algorithm was designed and implemented in clinical simulation.

RESULTS

All the witnesses were able to recognize the OHCA, call for emergency assistance, follow all the operator's instructions, move the victim, and place their hands in the correct position to perform CPR.

DISCUSSION

The results of the pilot study provide us a basis for further experimental studies using randomization and experimental and control groups.

CONCLUSIONS

No standardized recommendations exist for the operator to perform telephone-guided CPR. For this reason, a response algorithm was designed.

Characteristics of out-of-hospital cardiac arrest patients in Riyadh province, Saudi Arabia: a cross-sectional study

Introduction

Little work has been done on out-of-hospital cardiac arrest (OHCA) in Saudi Arabia. Our goal is to report the characteristics of OHCA patients and predictors of bystander cardiopulmonary resuscitation (CPR).

Materials and methods

This cross-sectional study utilized data from the Saudi Red Crescent Authority (SRCA), a governmental emergency medical service (EMS). A standardized data collection form based on the "Utstein-style" guidelines was developed. Data were retrieved from the electronic patient care reports that SRCA providers fill out for every case. OHCA cases that were attended by SRCA in Riyadh province between June 1st, 2020 and May 31st, 2021 were included. Multivariate regression analysis was performed to assess independent predictors of bystander CPR.

Results

A total of 1,023 OHCA cases were included. The mean age was 57.2 (±22.6). 95.7% (979/1,023) of cases were adults and 65.2% (667/1,023) were males. Home was the most common location of OHCA [784/1,011 (77.5%)]. The initial recorded rhythm was shockable in 131/742 (17.7%). The EMS mean response time was 15.9 min (±11.1). Bystander CPR was performed in 130/1,023 (12.7%) and was more commonly performed in children as compared to adults [12/44 (27.3%) vs. 118/979 (12.1%), p = 0.003]. Independent predictors of bystander CPR were being a child (OR = 3.26, 95% CI [1.21-8.82], p = 0.02) and having OHCA in a healthcare institution (OR = 6.35, 95% CI [2.15-18.72], p = 0.001).

Conclusion

Our study reported the characteristics of OHCA cases in Saudi Arabia using EMS data. We observed young age at presentation, low rates of bystander CPR, and long response time. These characteristics are distinctly different from other countries and call for urgent attention to OHCA care in Saudi Arabia. Lastly, being a child and having OHCA in a healthcare institution were found to be independent predictors of bystander CPR.

Out-of-Hospital Cardiac Arrest during the COVID-19 Pandemic: A Systematic Review

Objective: Out-of-hospital cardiac arrest (OHCA) is a prominent cause of death worldwide. As indicated by the high proportion of COVID-19 suspicion or diagnosis among patients who had OHCA, this issue could have resulted in multiple fatalities from coronavirus disease 2019 (COVID-19) occurring at home and being counted as OHCA. Methods: We used the MeSH term "heart arrest" as well as non-MeSH terms "out-of-hospital cardiac arrest, sudden cardiac death, OHCA, cardiac arrest, coronavirus pandemic, COVID-19, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)." We conducted a literature search using these search keywords in the Science Direct and PubMed databases and Google Scholar until 25 April 2022. Results: A systematic review of observational studies revealed OHCA and mortality rates increased considerably during the COVID-19 pandemic compared to the same period of the previous year. A temporary two-fold rise in OHCA incidence was detected along with a drop in survival. During the pandemic, the community's response to OHCA changed, with fewer bystander cardiopulmonary resuscitations (CPRs), longer emergency medical service (EMS) response times, and worse OHCA survival rates. Conclusions: This study's limitations include a lack of a centralised data-gathering method and OHCA registry system. If the chain of survival is maintained and effective emergency ambulance services with a qualified emergency medical team are given, the outcome for OHCA survivors can be improved even more.

The Impact of Prehospital and Hospital Care on Clinical Outcomes in Out-of-Hospital Cardiac Arrest

Background: In recent years, several actions have been made to shorten the chain of survival in out-of-hospital cardiac arrest (OHCA). These include placing defibrillators in public places, training first responders, and providing dispatcher-assisted CPR (DA-CPR). In this work, we aimed to evaluate the impact of these changes on patients' outcomes, including achieving return of spontaneous circulation (ROSC), survival to discharge, and survival with favorable neurological function. Methods: We retrospectively retrieved data of all calls to the national emergency medical service in Ashdod city, Israel, of individuals who underwent OHCA at the age of 18 and older between the years 2018 and 2021. Data was collected on prehospital and hospital interventions. The association between pre-hospital and hospital interventions to ROSC, survival to discharge, and neurological outcomes was evaluated. Logistic regression was used for multivariable analysis. Results: During the years 2018-2021, there were 1253 OHCA cases in the city of Ashdod. ROSC was achieved in 207 cases (32%), survival to discharge was attained in 48 cases (7.4%), and survival with favorable neurological function was obtained in 26 cases (4%). Factors significantly associated with good prognosis were shockable rhythm, witnessed arrest, DA-CPR, use of AED, and treatment for STEMI. All patients that failed to achieve ROSC outside of the hospital setting had a poor prognosis. Conclusions: This study demonstrates the prognostic role of the initial rhythm and the use of AED in OHCA. Hospital management, including STEMI documentation and catheterization, was also an important prognostication factors. Additionally, when ROSC is not achieved in the field, hospital transfer should be considered.

End-Stage Renal Disease Patients Undergoing Hemodialysis Have Higher Possibility of Return of Spontaneous Circulation during Out-of-Hospital Cardiac Arrest and Non-Inferior Short-Term Survival

End-stage renal disease (ESRD) patients on long-term hemodialysis (HD) have an elevated risk of sudden cardiac death. This study hypothesizes, for the first time, that these patients have a higher odds of return of spontaneous circulation (ROSC) and subsequent better hospital-outcomes, post out-of-hospital cardiac arrest (OHCA), as opposed to non-ESRD patients. A national database from Taiwan was utilized, in which 101,876 ESRD patients undergoing HD and propensity score-matched non-ESRD patients were used to conduct two analyses: (i) Cox-proportional-hazards-regression for OHCA incidence and (ii) logistic-regression analysis of attaining ROSC after OHCA, both for ESRD patients in comparison to non-ESRD patients. Kaplan-Meier analyses were conducted to determine the difference of survival rates after ROSC between the two cohorts. ESRD patients were found to be at a higher risk of OHCA (adjusted-HR = 2.11, 95% CI: (1.89−2.36), p < 0.001); however, they were at higher odds of attaining ROSC (adjusted-OR = 2.47, 95% CI: 1.90−3.21, p < 0.001), as opposed to non-ESRDs. Further, Kaplan-Meier analysis demonstrated ESRD patients with a better 30-day hospital survival rate than non-ESRD patients. Although ESRD patients had a higher risk of OHCA, they demonstrated higher possibility of ROSC and a better short-term hospital outcome than non-ESRDs. Chronic toxin tolerance and the training of vascular-compliance during regular HD may be possible explanations for better outcomes in ESRD patients.

Occurrence and Temporal Variability of Out-of-Hospital Cardiac Arrest during COVID-19 Pandemic in Comparison to the Pre-Pandemic Period in Poland-Observational Analysis of OSCAR-POL Registry

An investigation of the chronobiology of out-of-hospital cardiac arrest (OHCA) during the coronavirus disease 2019 (COVID-19) pandemic and the differences in comparison to the 6-year pre-pandemic period. A retrospective analysis of the dispatch cards from the Emergency Medical Service between January 2014 and December 2020 was performed within the OSCAR-POL registry. The circadian, weekly, monthly, and seasonal variabilities of OHCA were investigated. A comparison of OHCA occurrence between the year 2020 and the 6-year pre-pandemic period was made. A total of 416 OHCAs were reported in 2020 and the median of OHCAs during the pre-pandemic period was 379 (interquartile range 337−407) cases per year. Nighttime was associated with a decreased number of OHCAs (16.6%) in comparison to afternoon (31.5%, p < 0.001) and morning (30.0%, p < 0.001). A higher occurrence at night was observed in 2020 compared to 2014−2019 (16.6% vs. 11.7%, p = 0.001). Monthly and seasonal variabilities were observed in 2020. The months with the highest OHCA occurrence in 2020 were November (13.2%) and October (11.1%) and were significantly higher compared to the same months during the pre-pandemic period (9.1%, p = 0.002 and 7.9%, p = 0.009, respectively). Autumn was the season with the highest rate of OHCA, which was also higher compared to the pre-pandemic period (30.5% vs. 25.1%, p = 0.003). The COVID-19 pandemic was related to a higher occurrence of OHCA. The circadian, monthly, and seasonal variabilities of OHCA occurrence were confirmed. In 2020, the highest occurrence of OHCA was observed in October and November, which coincided with the highest occurrence of COVID-19 infections in Poland.

Effects of a designated ambulance team response on prehospital return of spontaneous circulation and advanced cardiac life support of out-of-hospital cardiac arrest: A nationwide natural experimental study

OBJECTIVES

This study aimed to investigate the effects of adding advanced cardiac life support (ACLS) training to an existing basic life support program and the operation of a designated team response for patients with out-of-hospital cardiac arrest (OHCA) on prehospital return of spontaneous circulation (ROSC) and ACLS management.

METHODS

A natural experimental study was conducted for emergency medical service (EMS)-treated adult patients with OHCA in 2020. In 2019, a quarter of the EMS clinicians were trained in a 3-day ACLS courses, and they were designated to be dispatched first in suspected OHCA. Some were dispatched only to major emergencies, such as OHCA and myocardial infarction (dedicated team), while others were dispatched to all emergencies with priority to major ones (non-dedicated team). The exposure was the ambulance response type: dedicated, no-dedicated, and basic teams (others). The primary outcome was prehospital ROSC. The secondary outcomes were prehospital ACLS (advanced airway management and intravenous access). A multivariable logistic regression analysis was conducted to investigate the effect of ambulance response type on study outcomes.

RESULTS

Among 23,512 eligible patients with OHCA, 54.8% (12,874) were treated by the basic team, 36.5% (8,580) by the non-dedicated ACLS team, and 8.8% (2,058) were treated by the dedicated ACLS team. Prehospital ROSC was greater for the designated team than for the basic team (dedicated ACLS team 13.8%, non-dedicated ACLS team 11.3%, and basic team 6.7%) (p <0.01). In the final logistic regression analysis, compared with the basic team, the designated ACLS team was associated with a higher probability of prehospital ROSC (AOR (95% CIs), 1.88 (1.68-2.09) compared to the non-dedicated ACLS team, and 2.46 (2.09-2.90) compared to the dedicated ACLS team), prehospital advanced airway management (1.72 (1.57-1.87) and 1.73 (1.48-2.03), respectively), and intravenous access (2.29 (2.16-2.43) and 2.76 (2.50-3.04), respectively).

CONCLUSION

Additional ACLS training and operation of a designated OHCA team response were associated with higher rates of prehospital ROSC and prehospital ACLS provision. However, further research is needed to find the optimal operation for EMS to improve survival outcomes.

The Automated External Defibrillator: Heterogeneity of Legislation, Mapping and Use across Europe. New Insights from the ENSURE Study

INTRODUCTION

The rapid use of an automated external defibrillator (AED) is crucial for increased survival after an out-of-hospital cardiac arrest (OHCA). Many factors could play a role in limiting the chance of an AED use. We aimed to verify the situation regarding AED legislation, the AED mapping system and first responders (FRs) equipped with an AED across European countries.

METHODS

We performed a survey across Europe entitled "European Study about AED Use by Lay Rescuers" (ENSURE), asking the national coordinators of the European Registry of Cardiac Arrest (EuReCa) program to complete it.

RESULTS

Nineteen European countries replied to the survey request for a population covering 128,297,955 inhabitants. The results revealed that every citizen can use an AED in 15 countries whereas a training certificate was required in three countries. In one country, only EMS personnel were allowed to use an AED. An AED mapping system and FRs equipped with an AED were available in only 11 countries. The AED use rate was 12-59% where AED mapping and FR systems were implemented, which was considerably higher than in other countries (0-7.9%), reflecting the difference in OHCA survival.

CONCLUSIONS

Our survey highlighted a heterogeneity in AED legislation, AED mapping systems and AED use in Europe, which was reflected in different AED use and survival.

Observational analysiS of out-of-hospital Cardiac Arrest occurRence and temporal variability patterns in subpopulation of southern POLand from 2006 to 2018: OSCAR-POL registry

BACKGROUND

Temporal variability of out-of-hospital cardiac arrest (OHCA) occurrence was presented in previous studies, however, the data regarding long-term observation is scarce. The aim of this study was to investigate the temporal variability of OHCA occurrence during a long-time period and analyze the circadian pattern within particular timeframes.

METHODS

The retrospective analysis of 5058 OHCA cases was made covering the period from January 1st, 2006 to December 31st, 2018. Circadian, weekly, monthly and seasonal variabilities were investigated. The circadian variability of OHCA occurrence was assessed within particular years, seasons of the year, and days of the week.

RESULTS

The highest OHCA incidence was observed between 08:00 and 08:59 and the lowest between 01:00 and 01:59 (7.1% vs. 1.6%, p < 0.001). After division into 6-h intervals, a significantly lower number of OHCA cases occurred between 00:00 and 05:59 (12.3%) in comparison to the highest number observed in between 06:00 and 11:59 (12.3% vs. 33.5%, p < 0.001). The highest OHCA occurrence was observed on Monday (14.9%), however, no weekly variability was found (p = 0.557). The highest OHCA occurrence was observed in the winter and lowest in the summer (27.4% vs. 22.8%, p < 0.001). Significant circadian variability was observed for every day of the week, every season and year during the observation period (p < 0.001).

CONCLUSIONS

Circadian, monthly and seasonal variability of OHCA occurrence was confirmed in the long-term observation with no differences between particular days of the week. Significant circadian variability was observed within days of the week, seasons of the year, and particular years.

A Machine Learning Model for the Prognosis of Pulseless Electrical Activity during Out-of-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.

Optimization of End-to-End Convolutional Neural Networks for Analysis of Out-of-Hospital Cardiac Arrest Rhythms during Cardiopulmonary Resuscitation

High performance of the shock advisory analysis of the electrocardiogram (ECG) during cardiopulmonary resuscitation (CPR) in out-of-hospital cardiac arrest (OHCA) is important for better management of the resuscitation protocol. It should provide fewer interruptions of chest compressions (CC) for non-shockable organized rhythms (OR) and Asystole, or prompt CC stopping for early treatment of shockable ventricular fibrillation (VF). Major disturbing factors are strong CC artifacts corrupting raw ECG, which we aimed to analyze with optimized end-to-end convolutional neural network (CNN) without pre-filtering or additional sensors. The hyperparameter random search of 1500 CNN models with 2-7 convolutional layers, 5-50 filters and 5-100 kernel sizes was done on large databases from independent OHCA interventions for training (3001 samples) and validation (2528 samples). The best model, named CNN3-CC-ECG network with three convolutional layers (filters@kernels: 5@5,25@20,50@20) presented Sensitivity Se(VF) = 89%(268/301), Specificity Sp(OR) = 91.7%(1504/1640), Sp(Asystole) = 91.1%(3325/3650) on an independent test OHCA database. CNN3-CC-ECG's ability to effectively extract features from raw ECG signals during CPR was comprehensively demonstrated, and the dependency on the CPR corruption level in ECG was tested. We denoted a significant drop of Se(VF) = 74.2% and Sp(OR) = 84.6% in very strong CPR artifacts with a signal-to-noise ratio of SNR < -9 dB, p < 0.05. Otherwise, for strong, moderate and weak CC artifacts (SNR > -9 dB, -6 dB, -3 dB), we observed insignificant performance differences: Se(VF) = 92.5-96.3%, Sp(OR) = 93.4-95.5%, Sp(Asystole) = 92.6-94.0%, p > 0.05. Performance stability with respect to CC rate was validated. Generalizable application of the optimized computationally efficient CNN model was justified by an independent OHCA database, which to our knowledge is the largest test dataset with real-life cardiac arrest rhythms during CPR.

Target Temperature Management and Survival with Favorable Neurological Outcome After Out-of-Hospital Cardiac Arrest in Children: A Nationwide Multicenter Prospective Study in Japan

To assess whether target temperature management (TTM) is effective for 1-month survival with favorable neurological outcome among pediatric patients who achieved return of spontaneous circulation (ROSC) after out-of-hospital cardiac arrest (OHCA). The Japanese Association for Acute Medicine-out-of-hospital cardiac arrest (JAAM-OHCA) Registry, a multicenter prospective observational registry in Japan, included OHCA patients aged ≤17 years who achieved ROSC between June 2014 and December 2017. The primary outcome was 1-month survival with favorable neurological outcomes, defined as pediatric cerebral performance category 1 or 2. We conducted a propensity score analysis with inverse-probability-of-treatment weighting (IPTW) and evaluated the effect of TTM using logistic regression models with IPTW. A total of 167 patients [120 in the non-TTM group (71.9%) and 47 in the TTM group (28.1%)] were eligible for our analysis. The proportion of patients demonstrating 1-month survival with favorable neurological outcomes was 25.5% (12/47) in the TTM group and 16.7% (20/120) in the non-TTM group; there were no significant differences in favorable neurological outcomes (odds ratio, 1.36; 95% confidence interval, 0.55-3.35) between the non-TTM and TTM groups after performing adjustments with IPTW. In our study population composed of pediatric patients who achieved ROSC after OHCA, we did not find a positive association between TTM implementation and 1-month survival with favorable neurological outcomes.

Towards the Prediction of Rearrest during Out-of-Hospital Cardiac Arrest

A secondary arrest is frequent in patients that recover spontaneous circulation after an out-of-hospital cardiac arrest (OHCA). Rearrest events are associated to worse patient outcomes, but little is known on the heart dynamics that lead to rearrest. The prediction of rearrest could help improve OHCA patient outcomes. The aim of this study was to develop a machine learning model to predict rearrest. A random forest classifier based on 21 heart rate variability (HRV) and electrocardiogram (ECG) features was designed. An analysis interval of 2 min after recovery of spontaneous circulation was used to compute the features. The model was trained and tested using a repeated cross-validation procedure, on a cohort of 162 OHCA patients (55 with rearrest). The median (interquartile range) sensitivity (rearrest) and specificity (no-rearrest) of the model were 67.3% (9.1%) and 67.3% (10.3%), respectively, with median areas under the receiver operating characteristics and the precision–recall curves of 0.69 and 0.53, respectively. This is the first machine learning model to predict rearrest, and would provide clinically valuable information to the clinician in an automated way.

Rhythm Analysis during Cardiopulmonary Resuscitation Using Convolutional Neural Networks

Chest compressions during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG that may provoque inaccurate rhythm classification by the algorithm of the defibrillator. The objective of this study was to design an algorithm to produce reliable shock/no-shock decisions during CPR using convolutional neural networks (CNN). A total of 3319 ECG segments of 9 s extracted during chest compressions were used, whereof 586 were shockable and 2733 nonshockable. Chest compression artifacts were removed using a Recursive Least Squares (RLS) filter, and the filtered ECG was fed to a CNN classifier with three convolutional blocks and two fully connected layers for the shock/no-shock classification. A 5-fold cross validation architecture was adopted to train/test the algorithm, and the proccess was repeated 100 times to statistically characterize the performance. The proposed architecture was compared to the most accurate algorithms that include handcrafted ECG features and a random forest classifier (baseline model). The median (90% confidence interval) sensitivity, specificity, accuracy and balanced accuracy of the method were 95.8% (94.6-96.8), 96.1% (95.8-96.5), 96.1% (95.7-96.4) and 96.0% (95.5-96.5), respectively. The proposed algorithm outperformed the baseline model by 0.6-points in accuracy. This new approach shows the potential of deep learning methods to provide reliable diagnosis of the cardiac rhythm without interrupting chest compression therapy.

After COACT trial-new perspectives for the management of non-ST elevation myocardial infarction: early versus late cardiac catheterization post cardiac arrest

Out-of-hospital cardiac arrest (OHCA) is the leading cause of death in the United States, as 90% of them are fatal per the 2018 American Heart Association statistics. As many as fifty-percent of cardiac arrest events display an initial rhythm of pulseless ventricular tachycardia (pVT) and ventricular fibrillation (VF), and of those, coronary artery disease (CAD) is found in 60-80% of patients. Following return of spontaneous circulation, patients who present with ST-elevation myocardial infarction (STEMI) should undergo an early invasive strategy and primary intervention, which is well-established guideline-based management. The support of such a strategy in patients suspected to have underlying cardiac cause but without ST-elevation has been waxing and waning in the literature. The Coronary Angiography after Cardiac Arrest (COACT) trial was designed to compare survival between an immediate or delayed coronary angiography strategy in non-STEMI (NSTEMI) OHCA patients, following successful resuscitation. We present a systematic review of the history of management strategies in OHCA and propose guidelines to manage such patients in light of the COACT trial.

Sodium bicarbonate on severe metabolic acidosis during prolonged cardiopulmonary resuscitation: a double-blind, randomized, placebo-controlled pilot study

Background

Sodium bicarbonate administration during cardiopulmonary resuscitation (CPR) is controversial. Current guidelines recommend sodium bicarbonate injection in patients with existing metabolic acidosis, but clinical trials, particularly, those involving patients with acidosis, are limited. We aimed to evaluate the efficacy of sodium bicarbonate administration in out-of-hospital cardiac arrest (OHCA) patients with severe metabolic acidosis during prolonged CPR.

Methods

Prospective, double-blind, randomized placebo-controlled pilot trial was conducted between January 2015 and December 2015, at a single center emergency department (ED). After 10 minutes of CPR, patients who failed to achieve return of spontaneous circulation (ROSC) and with severe metabolic acidosis (pH<7.1 or bicarbonate <10 mEq/L) were enrolled. Sodium bicarbonate (n=25) or normal saline (n=25) were administered. The primary end point was sustained ROSC. The secondary end points were the change of acidosis and good neurologic survival.

Results

Sodium bicarbonate group had significant effect on pH (6.99 vs. 6.90, P=0.038) and bicarbonate levels (21.0 vs. 8.0 mEq/L, P=0.007). However, no significant differences showed between sodium bicarbonate and placebo groups in sustained ROSC (4.0% vs. 16.0%, P=0.349) or good neurologic survival at 1 month (0.0% vs. 4.0%, P=1.000).

Conclusions

The use of sodium bicarbonate improved acid-base status, but did not improve the rate of ROSC and good neurologic survival. We could not draw a conclusion, but our pilot data could be used to design a larger trial to verify the efficacy of sodium bicarbonate.

Trial Registration

NCT02303548 (http://www.ClinicalTrials.gov).

Uncontrolled Donation After Circulatory Determination of Death: A Systematic Ethical Analysis

Uncontrolled donation after circulatory determination of death (uDCDD) refers to organ donation after a refractory cardiac arrest. We analyzed ethical issues raised by the uDCDD protocols of France, Madrid, and New York City. We recommend: (1) Termination of resuscitation (TOR) guidelines need refinement, particularly the minimal duration of resuscitation efforts before considering TOR; (2) Before enrolling in an uDCDD protocol, physicians must ascertain that additional resuscitation efforts would be ineffective; (3) Inclusion in an uDCDD protocol should not be made in the outpatient setting to avoid error and conflicts of interest; (4) The patient's condition should be reassessed at the hospital and reversible causes treated; (5) A no-touch period of at least 10 minutes should be respected to avoid the risk of autoresuscitation; (6) Once death has been determined, no procedure that may resume brain circulation should be used, including cardiopulmonary resuscitation, artificial ventilation, and extracorporeal membrane oxygenation; (7) Specific consent is required prior to entry into an uDCDD protocol; (8) Family members should be informed about the goals, risks, and benefits of planned uDCDD procedures; and (9) Public information on uDCDD is desirable because it promotes public trust and confidence in the organ donation system.

Adult out-of-hospital cardiac arrest based on chain of survival in Taoyuan County, northern Taiwan

BACKGROUND

Most out-of-hospital cardiac arrest (OHCA) studies have been conducted in developed countries or metropolitan areas, and few in developing countries or rural areas.

OBJECTIVES

The aims of this study were to determine the weak links in the chain of survival and to estimate the outcomes of OHCA patients in Taoyuan, a nonmetropolitan area in Taiwan.

METHODS

A retrospective review and analysis of OHCA data was conducted. The three outcomes were whether a return of spontaneous circulation (ROSC) was achieved, whether the patient survived to admission, or whether the patient survived to hospital discharge.

RESULTS

From April to December 2008, 1048 OHCA patients were resuscitated, and 712 (67.9%) adult cardiac patients were used in this study. Among these 712 patients, 17.8% achieved ROSC (95% confidence interval [CI] 15.2-20.8%), 16.3% survived to admission (95% CI 13.6-19.0%), and 1.4% survived to discharge (95% CI 0.5-2.3%). Factors significantly associated with the three outcomes were witness status, response time to emergency medical services, and whether the patient had a shockable rhythm. Bystander cardiopulmonary resuscitation (CPR) did not add a notable benefit to the outcomes of OHCA.

CONCLUSIONS

The survival rate of OHCA patients in nonmetropolitan Taiwan was very low (1.4%). Lower witnessed rate, lower bystander CPR rate, and longer response interval in remote areas are the main causes of inferior survival rate.