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The study protocol for the LINC (LUCAS in cardiac arrest) study: a study comparing conventional adult out-of-hospital cardiopulmonary resuscitation with a concept with mechanical chest compressions and simultaneous defibrillation.

ABSTRACT: The LUCAS™ device delivers mechanical chest compressions that have been shown in experimental studies to improve perfusion pressures to the brain and heart as well as augmenting cerebral blood flow and end tidal CO2, compared with results from standard manual cardiopulmonary resuscitation (CPR). Two randomised pilot studies in out-of-hospital cardiac arrest patients have not shown improved outcome when compared with manual CPR. There remains evidence from small case series that the device can be potentially beneficial compared with manual chest compressions in specific situations. This multicentre study is designed to evaluate the efficacy and safety of mechanical chest compressions with the LUCAS™ device whilst allowing defibrillation during on-going CPR, and comparing the results with those of conventional resuscitation.This article describes the design and protocol of the LINC-study which is a randomised controlled multicentre study of 2500 out-of-hospital cardiac arrest patients. The study has been registered at ClinicalTrials.gov (http://clinicaltrials.gov/ct2/show/NCT00609778?term=LINC&rank=1).Primary endpoint is four-hour survival after successful restoration of spontaneous circulation. The safety aspect is being evaluated by post mortem examinations in 300 patients that may reflect injuries from CPR.This large multicentre study will contribute to the evaluation of mechanical chest compression in CPR and specifically to the efficacy and safety of the LUCAS™ device when used in association with defibrillation during on-going CPR.

SUBMITTER: Rubertsson S

PROVIDER: S-EPMC3575236 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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The study protocol for the LINC (LUCAS in cardiac arrest) study: a study comparing conventional adult out-of-hospital cardiopulmonary resuscitation with a concept with mechanical chest compressions and simultaneous defibrillation.

Rubertsson Sten S Silfverstolpe Johan J Rehn Liselott L Nyman Thomas T Lichtveld Rob R Boomars Rene R Bruins Wendy W Ahlstedt Björn B Puggioli Helena H Lindgren Erik E Smekal David D Skoog Gunnar G Kastberg Robert R Lindblad Anna A Halliwell David D Box Martyn M Arnwald Fredrik F Hardig Bjarne Madsen BM Chamberlain Douglas D Herlitz Johan J Karlsten Rolf R

Scandinavian journal of trauma, resuscitation and emergency medicine 20130125

<h4>Background</h4>The LUCAS™ device delivers mechanical chest compressions that have been shown in experimental studies to improve perfusion pressures to the brain and heart as well as augmenting cerebral blood flow and end tidal CO2, compared with results from standard manual cardiopulmonary resuscitation (CPR). Two randomised pilot studies in out-of-hospital cardiac arrest patients have not shown improved outcome when compared with manual CPR. There remains evidence from small case series tha ...[more]

PMID: 23351178

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Project description:BackgroundQuality of cardiopulmonary resuscitation (CPR) is key to increase survival from cardiac arrest. Providing chest compressions with adequate rate and depth is difficult even for well-trained rescuers. The use of real-time feedback devices is intended to contribute to enhance chest compression quality. These devices are typically based on the double integration of the acceleration to obtain the chest displacement during compressions. The integration process is inherently unstable and leads to important errors unless boundary conditions are applied for each compression cycle. Commercial solutions use additional reference signals to establish these conditions, requiring additional sensors. Our aim was to study the accuracy of three methods based solely on the acceleration signal to provide feedback on the compression rate and depth.Materials and methodsWe simulated a CPR scenario with several volunteers grouped in couples providing chest compressions on a resuscitation manikin. Different target rates (80, 100, 120, and 140 compressions per minute) and a target depth of at least 50 mm were indicated. The manikin was equipped with a displacement sensor. The accelerometer was placed between the rescuer's hands and the manikin's chest. We designed three alternatives to direct integration based on different principles (linear filtering, analysis of velocity, and spectral analysis of acceleration). We evaluated their accuracy by comparing the estimated depth and rate with the values obtained from the reference displacement sensor.ResultsThe median (IQR) percent error was 5.9% (2.8-10.3), 6.3% (2.9-11.3), and 2.5% (1.2-4.4) for depth and 1.7% (0.0-2.3), 0.0% (0.0-2.0), and 0.9% (0.4-1.6) for rate, respectively. Depth accuracy depended on the target rate (p < 0.001) and on the rescuer couple (p < 0.001) within each method.ConclusionsAccurate feedback on chest compression depth and rate during CPR is possible using exclusively the chest acceleration signal. The algorithm based on spectral analysis showed the best performance. Despite these encouraging results, further research should be conducted to asses the performance of these algorithms with clinical data.

Project description:IntroductionEarly defibrillation is an important factor of survival in cardiac arrest. However, novice resuscitators often struggle with cardiac arrest patients. We investigated factors leading to delayed defibrillation performed by final-year medical students within a simulated bystander cardiac arrest situation.MethodsFinal-year medical students received a refresher lecture and basic life support training before being confronted with a simulated cardiac arrest situation in a simulation ambulance. The scenario was analyzed for factors leading to delayed defibrillation. We compared the time intervals the participants needed for various measures with a benchmark set by experienced resuscitators. After training, the participants were interviewed regarding challenges and thoughts during the scenario.ResultsThe median time needed for defibrillation was 158 s (n = 49, interquartile range: 107-270 s), more than six-fold of the benchmark time. The major part of total defibrillation time (49%; median, n = 49) was between onset of ventricular fibrillation and beginning to prepare the defibrillator, more specifically the time between end of preparation of the defibrillator and actual delivery of the shock, with a mean proportion of 26% (n = 49, SD = 17%) of the overall time needed for defibrillation (maximum 67%). Self-reported reasons for this delay included uncertainty about the next step to take, as reported by 73% of the participants. A total of 35% were unsure about which algorithm to follow. Diagnosing the patient was subjectively difficult for 35% of the participants. Overall, 53% of the participants felt generally confused.ConclusionsOur study shows that novice resuscitators rarely achieve guideline-recommended defibrillation times. The most relative delays were observed when participants had to choose what to do next or which algorithm to follow, and thus i.e. performed extensive airway management before a life-saving defibrillation. Our data provides a first insight in the process of defibrillation delay and can be used to generate new hypotheses on how to provide a timely defibrillation.

Project description:BACKGROUND: Although nurses must be able to respond quickly and effectively to cardiac arrest, numerous studies have demonstrated poor performance. Simulation is a promising learning tool for resuscitation team training but there are few studies that examine simulation for training defibrillation and cardiopulmonary resuscitation (D-CPR) in teams from the nursing education perspective. The aim of this study was to investigate the extent to which nursing student teams follow the D-CPR-algorithm in a simulated cardiac arrest, and if observing a simulated cardiac arrest scenario and participating in the post simulation debriefing would improve team performance. METHODS: We studied video-recorded simulations of D-CPR performance in 28 nursing student teams. Besides describing the overall performance of D-CPR, we compared D-CPR performance in two groups. Group A (n = 14) performed D-CPR in a simulated cardiac arrest scenario, while Group B (n = 14) performed D-CPR after first observing performance of Group A and participating in the debriefing. We developed a D-CPR checklist to assess team performance. RESULTS: Overall there were large variations in how accurately the nursing student teams performed the specific parts of the D-CPR algorithm. While few teams performed opening the airways and examination of breathing correctly, all teams used a 30:2 compression: ventilation ratio.We found no difference between Group A and Group B in D-CPR performance, either in regard to total points on the check list or to time variables. CONCLUSION: We found that none of the nursing student teams achieved top scores on the D-CPR-checklist. Observing the training of other teams did not increase subsequent performance. We think all this indicates that more time must be assigned for repetitive practice and reflection. Moreover, the most important aspects of D-CPR, such as early defibrillation and hands-off time in relation to shock, must be highlighted in team-training of nursing students.

Dataset Information

The study protocol for the LINC (LUCAS in cardiac arrest) study: a study comparing conventional adult out-of-hospital cardiopulmonary resuscitation with a concept with mechanical chest compressions and simultaneous defibrillation.

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The study protocol for the LINC (LUCAS in cardiac arrest) study: a study comparing conventional adult out-of-hospital cardiopulmonary resuscitation with a concept with mechanical chest compressions and simultaneous defibrillation.

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