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Even in patients with successful return of spontaneous circulation (ROSC), outcome after cardiac arrest remains poor. The overall in-hospital survival rate widely varies both worldwide and across communities, from 1 to 4 folds according to circumstances of arrest and post-resuscitation interventions. Several studies have already shown that early interventions performed after ROSC, such as treatment of the cause, targeted temperature management, optimal hemodynamic management and extra-corporeal life support in selected patients, could improve the outcome in post-cardiac arrest patients. However, the decision process regarding the allocation of these resources, in parallel with the management of patients' proxies, remains a complex challenge for physicians facing these situations. Consequently, several prediction models and scores have been developed in order to stratify the risk of unfavorable outcome and to discriminate the best candidates for post-resuscitation interventions. Overall, several scores exist, but external validation are lacking and direct comparisons are needed to assess relative interest of scoring systems. Indeed, establishing the optimal scoring system is crucial, for optimal treatment allocation and appropriate information to relatives.
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