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Δευτέρα 10 Ιουνίου 2019

Can real-time feedback improve the simulated infant cardiopulmonary resuscitation performance of basic life support and lay rescuers?
Jeyapal Kandasamy1, Peter S Theobald1, Ian K Maconochie2, Michael D Jones1
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Abstract
Background Performing high-quality chest compressions during cardiopulmonary resuscitation (CPR) requires achieving of a target depth, release force, rate and duty cycle.

Objective This study evaluates whether ‘real time’ feedback could improve infant CPR performance in basic life support-trained (BLS) and lay rescuers. It also investigates whether delivering rescue breaths hinders performing high-quality chest compressions. Also, this study reports raw data from the two methods used to calculate duty cycle performance.

Methodology BLS (n=28) and lay (n=38) rescuers were randomly allocated to respective ‘feedback’ or ‘no-feedback’ groups, to perform two-thumb chest compressions on an instrumented infant manikin. Chest compression performance was then investigated across three compression algorithms (compression only; five rescue breaths then compression only; five rescue breaths then 15:2 compressions). Two different routes to calculate duty cycle were also investigated, due to conflicting instruction in the literature.

Results No-feedback BLS and lay groups demonstrated <3% compliance against each performance target. The feedback rescuers produced 20-fold and 10-fold increases in BLS and lay cohorts, respectively, achieving all targets concurrently in >60% and >25% of all chest compressions, across all three algorithms. Performing rescue breaths did not impede chest compression quality.

Conclusions A feedback system has great potential to improve infant CPR performance, especially in cohorts that have an underlying understanding of the technique. The addition of rescue breaths—a potential distraction—did not negatively influence chest compression quality. Duty cycle performance depended on the calculation method, meaning there is an urgent requirement to agree a single measure.


http://dx.doi.org/10.1136/archdischild-2018-316576

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