RESULTS Overall, the CPRcard group achieved a better median compression rate (CPRcard 117 vs. control 122, p = 0.001) and proportion of compressions within the adequate rate range (CPRcard 83% vs. control 47%, p < 0.001). Compared to the no-card and blinded-card groups, the CPRcard group had a higher proportion of adequate compression rate (CPRcard 88% vs. no-card 46.8%, p = 0.037; CPRcard 73% vs. blinded-card 43%, p = 0.003). Proportion of compressions with adequate depth was similar in all groups (CPRcard 52% vs. control 48%, p = 0.957). The CPRcard group more often met targets for compression rate of 100-120/min and depth of at least 5 cm (CPRcard 36% vs. control 4%, p = 0.022). Chest compression fl ow fraction rate was similar but not statistically signifi cant in all groups (92%, p = 1.0). Respondents using the CPRcard expressed higher confi dence (mean 2.7 ± 2.4; 1 = very confi dent, 10 = not confi dent).CONCLUSION Use of the CPRcard by non-healthcare workers in simulated resuscitation improved the quality of chest compressions, thus boosting user confi dence in performing compressions.
ObjectiveThe quality of cardiopulmonary resuscitation (CPR) has been shown to affect the survival of out-of-hospital cardiac arrest cases (OHCA). There are various individual factors that can affect the quality of chest compression. We aimed to determine if age, gender and physical attributes (height, weight and BMI) affected the quality of chest compressions administered by laypersons during training.Design and methodsThe CPRcard™ is a novel device that captures and provides real-time visual feedback on chest compression quality through a 2 metre display. We analysed data from our layperson CPR and AED training sessions from October 2015 to November 2015. Measurement parameters were adequate depth, adequate rate and flow fraction. Adequate depth was the percentage of total chest compressions with depth 5 cm. Adequate rate was the percentage of compression with rate between 100–120 chest compressions per minute. Flow fraction is the percentage of time chest compressions were performed without more than a 3 s pause. An adequate flow fraction target was >80%.Results77 participant’s data were analysed. 35% were male and 65% were female, with majority (34%) being 35–44 years old. The mean height was 1.63 m±0.10 m, mean weight 61.4 kg ±14.0 kg and mean BMI 23±4 kg/m2. Median adequate rate decreased significantly with age (p value=0.02). Median adequate depth and flow time showed no association with age (p=0.56, p=0.46 respectively). Males managed a significantly better median adequate depth (82.0% vs 56.0%, p value=0.01). There was no significant difference in chest compression quality with height, weight and BMI.ConclusionsOverall, at least 1 parameter of chest compression quality decreased with age, and was better in males than females. A possible application of these results is to have differences in training methods for different ages and sexes, targeting parameters that they are weaker at.
Background Early cardiopulmonary resuscitation (CPR) and use of an automated external defibrillator (AED) can increase 30-day survival from 10% up to 70%. An unmanned aerial vehicle (UAV) might have a role in transporting an AED to the site of an OHCA. The aim of this experimental study was to describe the potential benefit of an UAV system for delivery of an AED in a rural environment. Materials and methods Optimal placement and response times for AED equipped UAV were calculated using GIS-models based on two weighting alternatives. UAV delivery testflights were performed using three different techniques. Results All OHCA cases with a cardiac aetiology n = 7923 in Stockholm county 2006-2013 were analyzed. Ten optimal locations with a 10 km radius in the greater Stockholm area were identified for implementation of UAV systems. With a simulated 50/50 weighting n = 7905 cases were found primarily in the city centre. The UAV arrived before EMS in 32% of cases with a mean timesaving of 1.5 min. With a simulated 80/20 weighting including n = 134 OHCA cases in primarily remote areas, the UAV arrived before EMS in 93% of cases with a mean timesaving of 19 min. Delivery of the AED in testflights n = 14 was successful in favourable conditions within sight primarily by latch-released technique or by landing the UAV on flat ground. Conclusions By using GIS models optimal placement of UAV systems can be calculated. These locations might in the future significantly reduce time to defibrillation and serve as a complement to EMS services. A4 Prehospital patient safety incidentsa description based on a national mandatory reporting system
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