Resuscitation
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Out-of-hospital cardiac arrest (OHCA) affects nearly 400,000 people each year in the United States of which only 10% survive. Using data from the Cardiac Arrest Registry to Enhance Survival (CARES), and machine learning (ML) techniques, we developed a model of neurological outcome prediction for OHCA in Chicago, Illinois. ⋯ ML modeling of the complex Chicago OHCA rescue system can predict neurologic outcomes with a reasonable level of accuracy and can be used to support intervention decisions such as CPR or coronary angiography. The discriminative ability of this ML model requires validation in external cohorts to establish generalizability.
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It has previously been shown that continuous intratracheal insufflation of oxygen (CIO) is superior to intermittent positive pressure ventilation (IPPV) regarding gas exchange and haemodynamics. The purpose of this study was to investigate gas exchange and haemodynamics with a new technique of phase-controlled intermittent insufflation of oxygen (PIIO) compared to CIO. ⋯ PIIO results in significantly higher CPP and compression phase aortic pressure during mCPR in a porcine population. Further studies are needed to validate these findings in humans. Study protocol conforming with ethic approval M174-15, issued by the Malmö/Lunds regionala djurförsöksetiska nämnd (REB).