Systematic downloading and analysis of data from automated external defibrillators used in out-of-hospital cardiac arrest

Community first response and out-of-hospital cardiac arrest: Identifying priorities for data collection, analysis, and use via the nominal group technique

AIM

Community First Response (CFR) is an important component of Out-of-hospital Cardiac Arrest management in many countries, including Ireland. Reliable, strategic data collection and analysis are required to support the development of CFR. However, data on CFR are currently limited in Ireland and internationally. This research aimed to identify the most important CFR data to record, the most important uses of CFR data, and barriers and facilitators to CFR data collection and use.

METHODS

The Nominal Group Technique structured consensus process was used. An expert panel comprising key stakeholders, including volunteers, clinicians, researchers, policy-makers, and a patient, completed a survey to generate lists of the most important CFR data to record and the most important uses of CFR data. Subsequently, they participated in a consensus meeting to agree the top ten priorities from each list. They also identified barriers and facilitators to CFR data collection and use.

RESULTS

The top ten CFR data items to record included volunteer response time, interventions/activities completed by volunteers, and the mental/physical impact on volunteers. The top ten most important uses of CFR data included providing feedback to volunteers, improving volunteer training, and measuring CFR effectiveness. Barriers included time constraints and limited training. Facilitators included having appropriate software/equipment and collecting minimal data.

CONCLUSION

The results can guide CFR research and inform the development of CFR data collection and analysis policy and practice in Ireland and internationally. Ultimately, improving CFR data collection and use will help to optimise this important intervention and enhance its evidence base.

How to improve automated external defibrillator placement for out-of-hospital cardiac arrests: A case study

Introduction

In out-of-hospital cardiac arrests (OHCAs), the use of an automatic external defibrillator (AED) by a bystander remains low, as AEDs may be misplaced with respect to the locations of OHCAs. As the distribution of historical OHCAs is potentially predictive of future OHCA locations, the purpose of this study is to assess AED positioning with regard to past locations of OHCAs, in order to improve the efficiency of public access defibrillation programs.

Methods

This is a retrospective observational study from 2014 to 2018. The locations of historical OHCAs and AEDs were loaded into a geodata processing tool. Median distances between AEDs were collected, as well as the number and rates of OHCAs covered (distance of <100 meters from the nearest AED). Areas with high densities of uncovered OHCAs (hotspots) were identified in order to propose the placement of additional AEDs. Areas over-covered by AEDs (overlays) were also identified in order to propose the relocation of overlapping AEDs.

Results

There were 2,971 OHCA, 79.3% of which occurred at home, and 633 AEDs included in the study. The global coverage rate was 7.5%. OHCAs occurring at home had a coverage rate of 4.5%. Forty hotspots were identified, requiring the same number of additional AEDs. The addition of these would increase the coverage from 7.5% to 17.6%. Regarding AED overlays, 17 AEDs were found to be relocatable without reducing the AED coverage of historical OHCAs.

Discussion

This study confirms that geodata tools can assess AED locations and increase the efficiency of their placement. Historical hotspots and AED overlays should be considered, with the aim of efficiently relocating or adding AEDs. At-home OHCAs should become a priority target for future public access defibrillation programs as they represent the majority of OHCAs but have the lowest AED coverage rates.

Transfer of essential AED information to treating hospital (TREAT)

BACKGROUND

Defibrillation in out-of-hospital cardiac arrest (OHCA) is increasingly performed by using an Automated External Defibrillator (AED). Therefore presence of a shockable rhythm is recurrently only documented by the AED. However, AED-information is rarely available to the treating physician.

PURPOSE

To determine (1) how often a shockable rhythm was recorded only in the AED; (2) if so, how often information that a shockable rhythm had been present reached the physician.

METHODS

Data on OHCA patients with (presumed) cardiac cause with an AED connected in the years 2012-2014 (Study period 1) and 2016 (Study period 2) in the Amsterdam Resuscitation Study (ARREST) database were collected. We determined how often only the AED had defibrillated. In these patients, we retrospectively analyzed EMS run sheets and hospital discharge letters to determine if a shockable rhythm and/or AED use was correctly noted. In Study period 2, we prospectively contacted the physicians to study whether AED defibrillation was known.

RESULTS

In Study period 1, of 2840 OHCA CPR attempts with (presumed) cardiac cause, 1521 (54%) patients had a shockable rhythm, with 356 patients (13%) receiving AED defibrillation only. Of these patients, 11 hospital discharge letters (4%) contained no information about a shockable rhythm. In Study period 2, 125/1128 patients (11%) received AED defibrillation only; of these, in two cases the shockable rhythm was unknown by the physician.

CONCLUSION

In 11-13% of OHCAs, a shockable rhythm is only seen on the AED-ECG. Adequate transfer to the physician of vital AED-information is essential but not always accomplished.

Global positioning system alerted volunteer first responders arrive before emergency medical services in more than four out of five emergency calls

AIM

To evaluate response rates for volunteer first responders (VFRs) activated by use of a smartphone GPS-tracking system and to compare response times of VFRs with those of emergency medical services (EMS). Furthermore, to evaluate 30-day-survival after out-of-hospital cardiac arrest (OHCA) on a rural island.

METHODS

Since 2012 a GPS-tracking system has been used on a rural island to activate VFRs during all emergency calls requesting an EMS. When activated, three VFRs were recruited and given distinct roles, including collection of the nearest automatic external defibrillator (AED). We retrospectively investigated EMS response data from April 2012 to December 2017. These were matched with VFR response times from the GPS-tracking system. The 30-day survival in OHCA patients was also assessed.

RESULTS

In 2266 of 2662 emergency calls (85%) at least one VFR arrived to the site before EMS. Median response times for VFRs (n = 2662) was 4:46 min:sec (IQR 3:16-6:52) compared with 10:13 min:sec (6:14-13:41) for EMS (p < 0.0001). A total of 17 OHCAs took place in public locations and 65 in residential areas. Thirty-day survival in these were 24% and 15%, respectively.

CONCLUSION

Use of a smartphone GPS-tracking system to dispatch VFRs ensures that in more than four of five cases, a VFR arrives to the site before EMS. Response times for VFRs were also found to be lower than EMS response times. Finally, the 30-day survival of OHCA patients in a rural area, based on these results, surpass our expectations.

Return of spontaneous circulation and long-term survival according to feedback provided by automated external defibrillators

Background

We aimed to investigate the effect of automated external defibrillator (AED) feedback mechanisms on survival in out‐of‐hospital cardiac arrest (OHCA) victims. In addition, we investigated converting rates in patients with shockable rhythms according to AED shock waveforms and energy levels.

Methods

We collected data on OHCA occurring between 2011 and 2014 in the Capital Region of Denmark where an AED was applied prior to ambulance arrival. Patient data were obtained from the Danish Cardiac Arrest Registry and medical records. AED data were retrieved from the Emergency Medical Dispatch Centre (EMDC) and information on feedback mechanisms, energy waveform and energy level was downloaded from the applied AEDs.

Results

A total of 196 OHCAs had an AED applied prior to ambulance arrival; 62 of these (32%) provided audio visual (AV) feedback while no feedback was provided in 134 (68%). We found no difference in return of spontaneous circulation (ROSC) at hospital arrival according to AV‐feedback; 34 (55%, 95% confidence interval (CI) [13–67]) vs. 72 (54%, 95% CI [45–62]), P = 1 (odds ratio (OR) 1.1, 95% CI [0.6–1.9]) or 30‐day survival; 24 (39%, 95% CI [28–51]) vs. 53 (40%, 95% CI [32–49]), P = 0.88 (OR 1.1 (95% CI [0.6–2.0])). Moreover, we found no difference in converting rates among patients with initial shockable rhythm receiving one or more shocks according to AED energy waveform and energy level.

Conclusions

No difference in survival after OHCA according to AED feedback mechanisms, nor any difference in converting rates according to AED waveform or energy levels was detected.

Quality of bystander cardiopulmonary resuscitation during real-life out-of-hospital cardiac arrest

BACKGROUND

Cardiopulmonary resuscitation (CPR) can increase survival in out-of-hospital cardiac arrest (OHCA). However, little is known about bystander CPR quality in real-life OHCA.

AIM

To describe bystander CPR quality based on automated external defibrillator (AED) CPR process data during OHCA and compare it with the European Resuscitation Council 2010 and 2015 Guidelines.

METHODS

We included OHCA cases from the Capital Region, Denmark, (2012-2016) where a Zoll AED was used before ambulance arrival. For cases with at least one minute of continuous data, the initial 10min of CPR data were analysed for compression rate, depth, fraction and compressions delivered for each minute of CPR. Data are presented as median [25th;75th percentile].

RESULTS

We included 136 cases. Bystander median compression rate was 101min^-1 [94;113], compression depth was 4.8cm [3.9;5.8] and compressions per minute were 62 [48;73]. Of all cases, the median compression rate was 100-120min^-1 in 42%, compression depth was 5-6cm in 26%, compression fraction≥60% in 51% and compressions delivered per minute exceeded 60 in 54%. In a minute-to-minute analysis, we found no evidence of deterioration in CPR quality over time. The median peri-shock pause was 27s [23;31] and the pre-shock pause was 19s [17;22].

CONCLUSIONS

The median CPR performed by bystanders using AEDs with audio-feedback in OHCA was within guideline recommendations without deterioration over time. Compression depth had poorer quality compared with other parameters. To improve bystander CPR quality, focus should be on proper compression depth and minimizing pauses.

The Effects of Public Access Defibrillation on Survival After Out-of-Hospital Cardiac Arrest: A Systematic Review of Observational Studies

BACKGROUND

Despite recent advances, the average survival after out-of-hospital cardiac arrest (OHCA) remains <10%. Early defibrillation by an automated external defibrillator is the most important intervention for patients with OHCA, showing survival proportions >50%. Accordingly, placement of automated external defibrillators in the community as part of a public access defibrillation program (PAD) is recommended by international guidelines. However, different strategies have been proposed on how exactly to increase and make use of publicly available automated external defibrillators. This systematic review aimed to evaluate the effect of PAD and the different PAD strategies on survival after OHCA.

METHODS

PubMed, Embase, and the Cochrane Library were systematically searched on August 31, 2015 for observational studies reporting survival to hospital discharge in OHCA patients where an automated external defibrillator had been used by nonemergency medical services. PAD was divided into 3 groups according to who applied the defibrillator: nondispatched lay first responders, professional first responders (firefighters/police) dispatched by the Emergency Medical Dispatch Center (EMDC), or lay first responders dispatched by the EMDC.

RESULTS

A total of 41 studies were included; 18 reported PAD by nondispatched lay first responders, 20 reported PAD by EMDC-dispatched professional first responders (firefighters/police), and 3 reported both. We identified no qualified studies reporting survival after PAD by EMDC-dispatched lay first responders. The overall survival to hospital discharge after OHCA treated with PAD showed a median survival of 40.0% (range, 9.1-83.3). Defibrillation by nondispatched lay first responders was associated with the highest survival with a median survival of 53.0% (range, 26.0-72.0), whereas defibrillation by EMDC-dispatched professional first responders (firefighters/police) was associated with a median survival of 28.6% (range, 9.0-76.0). A meta-analysis of the different survival outcomes could not be performed because of the large heterogeneity of the included studies.

CONCLUSIONS

This systematic review showed a median overall survival of 40% for patients with OHCA treated by PAD. Defibrillation by nondispatched lay first responders was found to correlate with the highest impact on survival in comparison with EMDC-dispatched professional first responders. PAD by EMDC-dispatched lay first responders could be a promising strategy, but evidence is lacking.

The Girona Territori Cardioprotegit Project: Performance Evaluation of Public Defibrillators

INTRODUCTION AND OBJECTIVES

In recent years, public access defibrillation programs have exponentially increased the availability of automatic external defibrillators (AED) in public spaces but there are no data on their performance in our setting. We conducted a descriptive analysis of the performance of AED since the launch of a public defibrillation program in our region.

METHODS

A retrospective analysis was conducted of electrocardiographic tracings and the performance of AED in a public defibrillation program from June 2011 to June 2015 in the province of Girona, Spain.

RESULTS

There were 231 AED activations. Full information was available on 188 activations, of which 82% corresponded to mobile devices and 18% to permanent devices. Asystole was the most prevalent rhythm (42%), while ventricular fibrillation accounted for 23%. The specificity of the device in identifying a shockable rhythm was 100%, but there were 8 false negatives (sensitivity 83%). There were 47 shockable rhythms, with a spontaneous circulation recovery rate of 49% (23 cases). There were no accidents related to the use of the device.

CONCLUSIONS

Nearly half of the recorded rhythms were asystole. The AED analyzed showed excellent safety and specificity, with moderate sensitivity. Half the patients with a shockable rhythm were successfully treated by the AED.

Combining Amplitude Spectrum Area with Previous Shock Information Using Neural Networks Improves Prediction Performance of Defibrillation Outcome for Subsequent Shocks in Out-Of-Hospital Cardiac Arrest Patients

Objective

Quantitative ventricular fibrillation (VF) waveform analysis is a potentially powerful tool to optimize defibrillation. However, whether combining VF features with additional attributes that related to the previous shock could enhance the prediction performance for subsequent shocks is still uncertain.

Methods

A total of 528 defibrillation shocks from 199 patients experienced out-of-hospital cardiac arrest were analyzed in this study. VF waveform was quantified using amplitude spectrum area (AMSA) from defibrillator's ECG recordings prior to each shock. Combinations of AMSA with previous shock index (PSI) or/and change of AMSA (ΔAMSA) between successive shocks were exercised through a training dataset including 255shocks from 99patientswith neural networks. Performance of the combination methods were compared with AMSA based single feature prediction by area under receiver operating characteristic curve(AUC), sensitivity, positive predictive value (PPV), negative predictive value (NPV) and prediction accuracy (PA) through a validation dataset that was consisted of 273 shocks from 100patients.

Results

A total of61 (61.0%) patients required subsequent shocks (N = 173) in the validation dataset. Combining AMSA with PSI and ΔAMSA obtained highest AUC (0.904 vs. 0.819, p<0.001) among different combination approaches for subsequent shocks. Sensitivity (76.5% vs. 35.3%, p<0.001), NPV (90.2% vs. 76.9%, p = 0.007) and PA (86.1% vs. 74.0%, p = 0.005)were greatly improved compared with AMSA based single feature prediction with a threshold of 90% specificity.

Conclusion

In this retrospective study, combining AMSA with previous shock information using neural networks greatly improves prediction performance of defibrillation outcome for subsequent shocks.

Interventional strategies associated with improvements in survival for out-of-hospital cardiac arrests in Singapore over 10 years

AIM

We aim to study if there has been an improvement in survival for Out-of-Hospital Cardiac Arrest (OHCA) in Singapore, the effects of various interventional strategies over the past 10 years, and identify strategies that contributed to improved survival.

METHODS

Rates of OHCA survival were compared between 2001-2004 and 2010-2012, using nationwide data for all OHCA presenting to EMS and public hospitals. A multivariate logistic regression model for survival to discharge was constructed to identify strategies with significant impact.

RESULTS

A total of 5453 cases were included, 2428 cases from 2001 to 2004 and 3025 cases from 2010 to 2012. There was significant improvement in Utstein (witnessed, shockable) survival to discharge from 2001-2004 (2.5%) to 2010-2012 (11.0%), adjusted odds ratio (OR) 9.6 [95% CI: 2.2-41.9]). Overall survival to discharge increased from 1.6% to 3.2% (adjusted OR 2.2 [1.5-3.3]). Bystander CPR rates increased from 19.7% to 22.4% (p=0.02). The multivariate regression model (adjusted for important non-modifiable risk factors) showed that response time <8min (OR 1.5 [1.0-2.3]), bystander AED (OR 5.8 [2.0-16.2]), and post-resuscitation hypothermia (OR 30.0 [11.5-78.0]) were significantly associated with survival to hospital discharge. Conversely, pre-hospital epinephrine (OR 0.6 [0.4-0.9]) was associated negatively with survival.

CONCLUSIONS

OHCA survival has improved in Singapore over the past 10 years. Improvement in response time, public AEDs and post-resuscitation hypothermia appear to have contributed to the increase in survival. Singapore's experience might suggest that developing EMS systems should focus on reducing times to basic life support, including bystander defibrillation and post-resuscitation care.