期刊
PREHOSPITAL EMERGENCY CARE
卷 27, 期 2, 页码 184-191出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/10903127.2022.2079782
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The duration of low flow prior to eCPR initiation is found to affect survival rates. Strategies aiming to reduce low-flow interval for out-of-hospital cardiac arrest include expedited patient transport and prehospital extracorporeal support. By comparing the low-flow interval at different locations in Albuquerque, a model predicts that prehospital cannulation consistently outperforms expedited transport, with a difference of 34.3 to 37.2 minutes. This suggests the potential of prehospital cannulation strategy in achieving shorter low-flow interval and broader eCPR coverage.
The duration of low flow prior to initiation of extracorporeal cardiopulmonary resuscitation (eCPR) appears to influence survival. Strategies to reduce the low-flow interval for out-of-hospital cardiac arrest have been focused on expediting patient transport to the hospital or initiating extracorporeal support in the prehospital setting. To date, a direct comparison of low-flow interval between these strategies has not been made. To attempt this comparison, a model was created to predict low-flow intervals for each strategy at different locations across the city of Albuquerque, New Mexico. The data, specific to Albuquerque, suggest that a prehospital cannulation strategy consistently outperforms an expedited transport strategy, with an estimated difference in low-flow interval of 34.3 to 37.2 minutes, depending on location. There is no location within the city in which an expedited transport strategy results in a shorter low-flow interval than prehospital cannulation. It would be rare to successfully initiate eCPR by either strategy in fewer than 30 minutes from the time of patient collapse. Using a prehospital cannulation strategy, the entire coverage area could be eligible for eCPR within 60 minutes of patient collapse. The use of predictive modeling can be a low-cost solution to assist with strategic deployment of prehospital resources and may have potential for real-time decision support for prehospital clinicians.
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