CPREzy: an evaluation during simulated cardiac arrest on a hospital bed.

Division of Medical Sciences, University of Birmingham, Birmingham B152TT, UK.
Resuscitation (Impact Factor: 3.96). 01/2005; 64(1):103-8. DOI: 10.1016/j.resuscitation.2004.08.011
Source: PubMed

ABSTRACT CPREzy is a new adjunct designed to improve the application of manual external chest compressions (ECC) during cardiopulmonary resuscitation (CPR). The aim of this study was to determine the effect of using the CPREzy device compared to standard CPR during the simulated resuscitation of a patient on a hospital bed. Twenty medical student volunteers were randomised using a cross over trial design to perform 3 min of continuous ECC using CPREzy and standard CPR. There was a significant improvement in ECC depth with CPREzy compared to standard CPR 42.9 (4.4) mm versus 34.2 (7.6): mm, P = 0.001; 95% CI d.f. 4.4-12.9 mm. This translated to a reduction in the percentage of shallow compressions (<38 mm) with CPREzy 16 (23)% compared to standard CPR 59 (44)%, P = 0.003. There was a small increase in the percentage of compression regarded excessive (>51 mm): CPREzy 6.5 (19)% versus standard CPR 0 (0.1)%. P = 0.012). There was no difference in compression rate or duty cycle between techniques. Equal numbers of participants (40% in each group) performed one of more incorrectly placed chest compression. However the total number of incorrect compressions was higher for the CPREzy group (26% versus 3.9% standard CPR, P < 0.001). This was due to a higher number of low compressions (26% of total compressions for CPREzy versus 1% for standard CPR, P < 0.001). In conclusion, CPREzy was associated with significant improvements in ECC performance. Further animal and clinical studies are required to validate this finding in vivo and to see if it translates to an improvement in outcome in human victims of cardiac arrest.

  • [Show abstract] [Hide abstract]
    ABSTRACT: The quality of cardiopulmonary resuscitation (CPR) impacts on outcome after cardiac arrest. This review will explore the factors that contribute to high-quality CPR and the metrics that can be used to monitor performance. A recent consensus statement from North America defined five key components of high-quality CPR: minimizing interruptions in chest compressions, providing compressions of adequate rate and depth, avoiding leaning on the chest between compressions, and avoiding excessive ventilation. Studies have shown that real-time feedback devices improve the quality of CPR and, in one before-and-after study, outcome from out-of-hospital cardiac arrest. There is evidence for increasing survival rates following out-of-hospital cardiac arrest and this is associated with increasing rates of bystander CPR. The quality of CPR provided by healthcare professionals can be improved with real-time feedback devices. The components of high-quality CPR and the metrics that can be measured and fed back to healthcare professionals have been defined by expert consensus. In the future, real-time feedback based on the physiological responses to CPR may prove more effective.
    Current opinion in critical care 04/2014; · 3.18 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Quality of cardiopulmonary resuscitation (CPR) improves through the use of CPR feedback devices. Most feedback devices integrate the acceleration twice to estimate compression depth. However, they use additional sensors or processing techniques to compensate for large displacement drifts caused by integration. This study introduces an accelerometer-based method that avoids integration by using spectral techniques on short duration acceleration intervals. We used a manikin placed on a hard surface, a sternal triaxial accelerometer, and a photoelectric distance sensor (gold standard). Twenty volunteers provided 60 s of continuous compressions to test various rates (80-140 min(-1)), depths (3-5 cm), and accelerometer misalignment conditions. A total of 320 records with 35312 compressions were analysed. The global root-mean-square errors in rate and depth were below 1.5 min(-1) and 2 mm for analysis intervals between 2 and 5 s. For 3 s analysis intervals the 95% levels of agreement between the method and the gold standard were within -1.64-1.67 min(-1) and -1.69-1.72 mm, respectively. Accurate feedback on chest compression rate and depth is feasible applying spectral techniques to the acceleration. The method avoids additional techniques to compensate for the integration displacement drift, improving accuracy, and simplifying current accelerometer-based devices.
    BioMed Research International 01/2014; 2014:865967. · 2.71 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Abstract Background: Although many smartphone application (app) programs provide education and guidance for basic life support, they do not commonly provide feedback on the chest compression depth (CCD) and rate. The validation of its accuracy has not been reported to date. This study was a feasibility assessment of use of the smartphone as a CCD feedback device. In this study, we proposed the concept of a new real-time CCD estimation algorithm using a smartphone and evaluated the accuracy of the algorithm. Materials and Methods: Using the double integration of the acceleration signal, which was obtained from the accelerometer in the smartphone, we estimated the CCD in real time. Based on its periodicity, we removed the bias error from the accelerometer. To evaluate this instrument's accuracy, we used a potentiometer as the reference depth measurement. The evaluation experiments included three levels of CCD (insufficient, adequate, and excessive) and four types of grasping orientations with various compression directions. We used the difference between the reference measurement and the estimated depth as the error. The error was calculated for each compression. Results: When chest compressions were performed with adequate depth for the patient who was lying on a flat floor, the mean (standard deviation) of the errors was 1.43 (1.00) mm. When the patient was lying on an oblique floor, the mean (standard deviation) of the errors was 3.13 (1.88) mm. Conclusions: The error of the CCD estimation was tolerable for the algorithm to be used in the smartphone-based CCD feedback app to compress more than 51 mm, which is the 2010 American Heart Association guideline.
    Telemedicine and e-Health 11/2014; · 1.54 Impact Factor

Full-text (2 Sources)

Available from
Jun 5, 2014