SmartCPR Trial: An Analysis of a Waveform-Based Automated External Defibrillation (AED) Algorithm on Survival From Out-of-Hospital Ventricular Fibrillation
Study Details
Study Description
Brief Summary
This study is designed to examine the impact of an available technology within an automated external defibrillator (AEDs) to improve survival following out-of-hospital cardiac arrest for patients presenting in ventricular fibrillation.
Condition or Disease | Intervention/Treatment | Phase |
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N/A |
Detailed Description
The delivery of an electrical shock, termed defibrillation, has long been recognized as one of the critical "links" in the "Chain of Survival" following out-of-hospital cardiac arrest. This is particularly the case for patients who present in ventricular fibrillation (VF), a state of constant and yet uncoordinate firing of the lower portions of the heart (the ventricles), and the ability to treat these patients with defibrillation prior to their arrival in the hospital has remained one of the reasons why this group represents the patients who are most likely to survive an out-of-hospital cardiac arrest.
Though this technology has been successfully utilized in the prehospital setting for more than forty years, the long-held belief that "immediate defibrillation" was the optimal treatment for all patients has now come into question.
Following research done in locations such as Seattle, WA and Oslo, Norway, there came a recognition that some patients (particularly those who have been in cardiac arrest for 4-5 minutes prior to EMS arrival) may actually benefit from a period of CPR prior to defibrillation ("delayed defibrillation"). This has to do with the changes that take place within the heart and even at the level of the cells within the heart following the onset of VF. After several minutes of VF, the cells within the heart have been deprived and depleted of oxygen and other energy-containing molecules, and there has been a build-up of other substances such as acids and potassium. By providing CPR prior to defibrillation, it is thought that the patient's heart may be provided with enough oxygen and other energy-containing molecules, making it more likely that the heart will respond favorably to defibrillation.
Yet this is not necessarily true for all VF patients. Other data from patients whose collapse and cardiac arrest were witnessed and for whom defibrillation was able to be provided quite rapidly (i.e. those in airports, airplanes, and casinos) demonstrate a very high survival rate when compared to those patients who have been in arrest for a longer period. This suggests that there are patients who are best treated with immediate defibrillation and those who are treated with "delayed defibrillation."
The problems for modern emergency medical services (EMS) systems include determining just when the VF began, the impact of bystander CPR, the patient's overall condition at the time of the cardiac arrest, and the time interval from the 911 call until the arrival of the EMS providers (EMTs and paramedics) at the side of the patient.
By choosing to provide immediate defibrillation to all patients, in hopes of benefiting those who are most likely to respond to defibrillation and to survive, an EMS system would simultaneously be choosing to provide less than ideal treatment to those patients who are likely to benefit from "delayed defibrillation." Conversely, choosing to provide "delayed defibrillation" to all patients likely treats the larger percentage of VF patients in any EMS system appropriately, yet it potentially delays life-saving treatment from those who are most likely to survive (the patients who would benefit from immediate defibrillation).
Research involving the mathematic properties of the VF waveform (something that the human eye cannot calculate) have led to the development of computer algorithms that may predict, based on the calculated mathematical "score" of the VF, whether a patient is likely to respond more favorably to immediate defibrillation or delayed defibrillation. Such a technology could, therefore, seem to be able to recommend every patient to the treatment that is best for their individual condition, and it would follow that such individual treatment may improve survival from VF cardiac arrest overall.
This study is designed to examine the effect of just such a technology on VF patients presenting to EMS providers in New York, NY and London, England.
Study Design
Arms and Interventions
Arm | Intervention/Treatment |
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Active Comparator: Standard resusc Patients in this arm will be treated with standard resuscitation efforts, including the delivery of an immediate defibrillatory shock for all patients presenting in VF. |
Device: Automated external defibrillator (Philips FR2+ AED)
Patients in this arm will be provided with immediate defibrillatory shock coupled with otherwise standard resuscitative efforts.
Other Names:
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Experimental: SmartCPR Patient in this arm will be treated with standard resuscitation efforts except that the first AED analysis will utilize an waveform-based algorithm to recommend either immediate defibrillation or delayed defibrillation for each patient. |
Device: SmartCPR
Patient in this arm will be treated with standard resuscitation efforts except that the first AED analysis will utilize an waveform-based algorithm to recommend either immediate defibrillation or delayed defibrillation for each patient.
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Active Comparator: Delayed defib In New York City only, all patients not initially treated by study personnel will receive other regional standard for resuscitation - delayed defibrillation. Data is being collected on this population as well, thereby providing a cohort population for comparative purposes. |
Other: Delayed defibrillation
In New York City only, all patients not initially treated by study personnel will receive other regional standard for resuscitation - delayed defibrillation.
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Outcome Measures
Primary Outcome Measures
- Survival to Hospital Discharge [Variable (depends upon interval needed for hospital admission and discharge)]
Secondary Outcome Measures
- Survival to hospital admission [within hours from the time of arrest]
- Return of spontaneous circulation (ROSC) in prehospital setting [Variable (depends on EMS contact time)]
- Neurological status among survivors [Variable (measured at hospital discharge)]
- Survival (defined as ROSC, survival to hospital admission, and survival to hospital discharge) as compared to a "delayed defibrillation" cohort in NYC [Variable (depends upon interval needed for hospital admission and discharge)]
- Impact of CPR interval on VF waveform characteristics [Immediately after CPR interval]
- Utility of AED algorithm and VF characteristics among EMS-witnessed arrests [Variable (some immediate data, some depends upon interval needed for hospital admission and discharge)]
- Utility of this AED technology and VF characteristics among pediatric patients [Variable (some immediate data, some depends upon interval needed for hospital admission and discharge)]
- Impact of bystander CPR on VF waveform characteristics [Immediate (taken from data during arrest)]
- Comparison of EMS response times to VF waveform characteristics [Immediate (data obtained during EMS response and arrest period)]
- Frequency of unmanageable airways in out-of-hospital cardiac arrest patients [Immediate (measured at the time of arrest)]
- Impact of patient race upon the provision of bystander CPR, VF waveform characteristics, and survival [Variable (depends upon interval needed for hospital admission and discharge)]
- Relationship between presenting and interval waveform capnography readings and survival [Variable (depends upon interval needed for hospital admission and discharge)]
- Frequency of organ donation among out-of-hospital cardiac arrest patients transported to the hospital who do not survive to hospital discharge [Variable (depends upon interval needed for hospital admission and discharge)]
- Waveform characteristics among patients presenting in secondary VF (initial presenting rhythm asystole or pulseless electrical activity) [Immediate (derived from data collected during the arrest)]
- Description of and outcomes of patients for whom intraosseous access is utilized during the cardiac arrest [Variable (depends upon interval needed for hospital admission and discharge)]
- Utstein comparison of two cities (London and New York) [Variable (depends upon interval needed for hospital admission and discharge)]
- Impact of bystander CPR on survival as a function of response time [Variable (depends upon interval needed for hospital admission and discharge)]
- Association between ambient small particle (PM2.5) pollution and cardiac arrest indicence in New York City [To be determined by modelling]
Eligibility Criteria
Criteria
Inclusion Criteria:
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initial treatment includes application of a study AED
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complete initial waveform analysis
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presenting rhythm is ventricular fibrillation
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arrest of cardiac etiology
Exclusion Criteria:
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arrest of noncardiac etiology
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initial treatment with a non-study defibrillator
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missing AED data
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age <18 (London only)
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resuscitation terminated due to a DNR order / decision
Contacts and Locations
Locations
Site | City | State | Country | Postal Code | |
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1 | New York City Fire Department | New York | New York | United States | 11201 |
2 | London Ambulance Service | London | England | United Kingdom |
Sponsors and Collaborators
- New York City Fire Department
- Philips Medical Systems
- London Ambulance Service
Investigators
- Principal Investigator: John P Freese, MD, New York City Fire Department
- Study Director: Bradley J Kaufman, MD, MPH, New York City Fire Department
- Study Director: Rachael Donohoe, PhD, London Ambulance Service
- Study Director: Dawn Jorgenson, PhD, Philips Medical Systems
Study Documents (Full-Text)
None provided.More Information
Publications
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- Amann A, Achleitner U, Antretter H, Bonatti JO, Krismer AC, Lindner KH, Rieder J, Wenzel V, Voelckel WG, Strohmenger HU. Analysing ventricular fibrillation ECG-signals and predicting defibrillation success during cardiopulmonary resuscitation employing N(alpha)-histograms. Resuscitation. 2001 Jul;50(1):77-85.
- Amann A, Rheinberger K, Achleitner U, Krismer AC, Lingnau W, Lindner KH, Wenzel V. The prediction of defibrillation outcome using a new combination of mean frequency and amplitude in porcine models of cardiac arrest. Anesth Analg. 2002 Sep;95(3):716-22, table of contents.
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