5 resultados para HSJ CPR

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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PURPOSE: Computer-based feedback systems for assessing the quality of cardiopulmonary resuscitation (CPR) are widely used these days. Recordings usually involve compression and ventilation dependent variables. Thorax compression depth, sufficient decompression and correct hand position are displayed but interpreted independently of one another. We aimed to generate a parameter, which represents all the combined relevant parameters of compression to provide a rapid assessment of the quality of chest compression-the effective compression ratio (ECR). METHODS: The following parameters were used to determine the ECR: compression depth, correct hand position, correct decompression and the proportion of time used for chest compressions compared to the total time spent on CPR. Based on the ERC guidelines, we calculated that guideline compliant CPR (30:2) has a minimum ECR of 0.79. To calculate the ECR, we expanded the previously described software solution. In order to demonstrate the usefulness of the new ECR-parameter, we first performed a PubMed search for studies that included correct compression and no-flow time, after which we calculated the new parameter, the ECR. RESULTS: The PubMed search revealed 9 trials. Calculated ECR values ranged between 0.03 (for basic life support [BLS] study, two helpers, no feedback) and 0.67 (BLS with feedback from the 6th minute). CONCLUSION: ECR enables rapid, meaningful assessment of CPR and simplifies the comparability of studies as well as the individual performance of trainees. The structure of the software solution allows it to be easily adapted to any manikin, CPR feedback devices and different resuscitation guidelines (e.g. ILCOR, ERC).

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BACKGROUND Efficiently performed basic life support (BLS) after cardiac arrest is proven to be effective. However, cardiopulmonary resuscitation (CPR) is strenuous and rescuers' performance declines rapidly over time. Audio-visual feedback devices reporting CPR quality may prevent this decline. We aimed to investigate the effect of various CPR feedback devices on CPR quality. METHODS In this open, prospective, randomised, controlled trial we compared three CPR feedback devices (PocketCPR, CPRmeter, iPhone app PocketCPR) with standard BLS without feedback in a simulated scenario. 240 trained medical students performed single rescuer BLS on a manikin for 8min. Effective compression (compressions with correct depth, pressure point and sufficient decompression) as well as compression rate, flow time fraction and ventilation parameters were compared between the four groups. RESULTS Study participants using the PocketCPR performed 17±19% effective compressions compared to 32±28% with CPRmeter, 25±27% with the iPhone app PocketCPR, and 35±30% applying standard BLS (PocketCPR vs. CPRmeter p=0.007, PocketCPR vs. standard BLS p=0.001, others: ns). PocketCPR and CPRmeter prevented a decline in effective compression over time, but overall performance in the PocketCPR group was considerably inferior to standard BLS. Compression depth and rate were within the range recommended in the guidelines in all groups. CONCLUSION While we found differences between the investigated CPR feedback devices, overall BLS quality was suboptimal in all groups. Surprisingly, effective compression was not improved by any CPR feedback device compared to standard BLS. All feedback devices caused substantial delay in starting CPR, which may worsen outcome.