Hands-on defibrillation and electrocardiogram artefact filtering technology increases chest compression fraction and decreases peri-shock pause duration in a simulation model of cardiac arrest

Chest Compression Fraction and Factors influencing it

Introduction:

Chest compression fraction (CCF) is the cumulative time spent providing chest compressions divided by the total time taken for the entire resuscitation. Targeting a CCF of at least 60% is intended to limit interruptions in compressions and maximize coronary perfusion during resuscitation. We aimed to identify the mean CCF and its relationship with various factors affecting it.

Methods:

Patients presenting to the emergency department in cardiac arrest at a single center were prospectively included in this study. Resuscitation was provided by trained health-care providers. The feedback device Cprmeter2™ was placed on the patient's sternum at the beginning of resuscitation. The total time taken for the entire resuscitation was noted by the device and CCF calculated.

Results:

The mean CCF was analyzed using descriptive statistics and was found to be 71.60% ± 7.52%. The total duration of resuscitation (R = −0.55, P = < 0.001, min-max, 2.02–34.31, mean 12.25 ± 6.54), number of people giving chest compressions (R = −0.48, P = < 0.001, min-max, 1–6, mean 4.04 ± 1.12), and total number of team members in resuscitation (R = −0.50, P = < 0.001, min-max, 4–10, mean 6.65 ± 1.32) had negative correlation with CCF. Diurnal variation (day, n = 35; mean 69.20% ± 7% and night, n = 20; mean 75.80% ± 5.6%, P = 0.001) and patients receiving defibrillation (receiving n = 10 mean 67.00% ± 4.11% and not receiving n = 45 mean 72.62 ± 7.42%, P = 0.005) were found to significantly affect CCF.

Conclusion:

The mean CCF for cardiac arrest patients was well within the targets of guideline recommendation. CCF decreased when resuscitation lasted longer, during daytime when the defibrillator was used, the total team members increased, and also when the number of people giving chest compressions increased. CCF during resuscitation may improve if there is a focus on improving these factors and requires validation in multicentric settings.

Towards evidence-based emergency medicine: best BETs from the Manchester Royal InfirmaryBET 1: Can hands-on defibrillation be performed safely?BET 2: FAST or ROSIER to identify suspected stroke in the prehospital setting?

A review was carried out to see whether hands-on defibrillation could be performed safely. 6 papers presented the best evidence to answer the clinical question. The author, date and country of publication, patient group studied, study type, relevant outcomes, results and study weaknesses of these papers are tabulated. It is concluded that hands-on defibrillation has the potential to be performed safely if the rescuer uses appropriate electrical insulating barriers such as polyethylene gloves or class 1 electrical insulating gloves. The safety profile of nitrile gloves is unclear. Since detection of shock was used as a proxy for safety, additional investigation is warranted before hands-on defibrillation becomes common practice.

Analysis of bystander CPR quality during out-of-hospital cardiac arrest using data derived from automated external defibrillators

BACKGROUND

Little is known regarding the quality of cardiopulmonary resuscitation (CPR) performed by bystanders in out-of-hospital cardiac arrest (OHCA). We sought to determine quality of bystander CPR provided during OHCA using CPR quality data stored by Automated External Defibrillators (AEDs).

METHODS

We used the Resuscitation Outcomes Consortium database to identify OHCA cases of presumed cardiac etiology where an AED was utilized. We then matched AED data to each case identified. AED data was analyzed using manufacturer software in order to determine overall measures of bystander CPR quality, changes in bystander CPR quality over time, and adherence to existing 2010 Resuscitation Quality Guidelines.

RESULTS

100 cases of OHCA of presumed cardiac etiology involving bystander CPR and with corresponding AED data. Mean age was 62.3 years, and 75% were male. Bystanders demonstrated high-quality CPR over all minutes of resuscitation, with a chest compression fraction of 76%, a compression depth of 5.3 cm, and a compression rate of 111.2 compressions/min. Mean perishock pause was 26.8 s. Adherence rates to 2010 Resuscitation Guidelines for compression rate and depth were found to be 66% and 55%, respectively. CPR quality was lowest in the first minute, resulting from increased delay to rhythm analysis (mean 40.7 s). In cases involving shock delivery, latency from initiation of AED to shock delivery was 59.2 s.

CONCLUSIONS

We found that bystanders perform high-quality CPR, with strong adherence rates to existing Resuscitation Guidelines. High-quality CPR is maintained over the first five minutes of resuscitation, but was lowest in the first minute.

Causes for Pauses During Simulated Pediatric Cardiac Arrest

OBJECTIVES

Pauses in cardiopulmonary resuscitation negatively impact clinical outcomes; however, little is known about the contributing factors. The objective of this study is to determine the frequency, duration, and causes for pauses during cardiac arrest.

DESIGN

This is a secondary analysis of video data collected from a prospective multicenter trial. Twenty-six simulated pediatric cardiac arrest scenarios each lasting 12 minutes in duration were analyzed by two independent reviewers to document events surrounding each pause in chest compressions.

SETTING

Ten children's hospitals across Canada, the United, and the United Kingdom.

SUBJECTS

Resuscitation teams composed of three healthcare providers trained in cardiopulmonary resuscitation.

INTERVENTIONS

A simulated pediatric cardiac arrest case in a 5 year old.

MEASUREMENTS AND MAIN RESULTS

The frequency, duration, and associated factors for each pause were recorded. Communication was rated using a four-point scale reflecting the team's shared mental model. Two hundred fifty-six pauses were reviewed with a median of 10 pauses per scenario (interquartile range, 7-12). Median pause duration was 5 seconds (interquartile range, 2-9 s), with 91% chest compression fraction per scenario (interquartile range, 88-94%). Only one task occurred during most pauses (66%). The most common tasks were a change of chest compressors (25%), performing pulse check (24%), and performing rhythm check (15%). Forty-nine (19%) of the pauses lasted greater than 10 seconds and were associated with shock delivery (p < 0.001), performing rhythm check (p < 0.001), and performing pulse check (p < 0.001). When a shared mental model was rated high, pauses were significantly shorter (mean difference, 4.2 s; 95% CI, 1.6-6.8 s; p = 0.002).

CONCLUSIONS

Pauses in cardiopulmonary resuscitation occurred frequently during simulated pediatric cardiac arrest, with variable duration and underlying causes. A large percentage of pauses were greater than 10 seconds and occurred more frequently than the recommended 2-minute interval. Future efforts should focus on improving team coordination to minimize pause frequency and duration.