The American journal of emergency medicine
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Multicenter Study Observational Study
Real-world comparison between mechanical and manual cardiopulmonary resuscitation during the COVID-19 pandemic.
The COVID-19 pandemic has posed significant challenges to healthcare systems worldwide, including an increase in out-of-hospital cardiac arrests (OHCA). Healthcare providers are now required to use personal protective equipment (PPE) during cardiopulmonary resuscitation (CPR). Additionally, mechanical CPR devices have been introduced to reduce the number of personnel required for resuscitation. This study aimed to compare the outcomes of CPR performed with a mechanical device and the outcomes of manual CPR performed by personnel wearing PPE. ⋯ This study found no significant differences in survival rates and neurological outcomes between mechanical CPR and PPE-equipped manual CPR in the ED setting. However, a longer total CPR duration was observed in the mechanical CPR group. Further research is required to explore the impact of PPE on healthcare providers' performance and fatigue during CPR in the context of the pandemic and beyond.
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Multicenter Study
Mortality risk factors in patients receiving ECPR after cardiac arrest: Development and validation of a clinical prognostic prediction model.
Previous studies have shown an increasing trend of extracorporeal cardiopulmonary resuscitation (ECPR) use in patients with cardiac arrest (CA). Although ECPR have been found to reduce mortality in patients with CA compared with conventional cardiopulmonary resuscitation (CCPR), the mortality remains high. This study was designed to identify the potential mortality risk factors for ECPR patients for further optimization of patient management and treatment selection. ⋯ Risk factors have been identified among ECPR patients including a history of cerebrovascular diseases, higher Lac and presence of PEA or asystole. While factor such as age 45-60, higher pH and use of IABP have been found protective against in-hospital mortality. These factors can be used for risk prediction, thereby improving the management and treatment selection of patients for this resource-intensive therapy.