Expedited transport versus continued on-scene resuscitation for refractory out-of-hospital cardiac arrest: A systematic review and meta-analysis

Burns, Brian; Hsu, Henry R.; Keech, Anthony; Huang, Yating; Tian, David H.; Coggins, Andrew; Dennis, Mark

doi:10.1016/j.resplu.2023.100482

Resuscitation Plus

2023

DOI: 10.1016/j.resplu.2023.100482

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Expedited transport versus continued on-scene resuscitation for refractory out-of-hospital cardiac arrest: A systematic review and meta-analysis

Brian Burns,

Henry R. Hsu,

Anthony Keech

et al.

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Cited by 2 publications

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Expedited transport versus continued on-scene resuscitation for refractory out-of-hospital cardiac arrest: A systematic review and meta-analysis

Burns,

Hsu,

Keech

et al. 2023

Resuscitation Plus

Self Cite

View full text Add to dashboard Cite

Expedited transport versus continued on-scene resuscitation for refractory out-of-hospital cardiac arrest: A systematic review and meta-analysis

Burns,

Hsu,

Keech

et al. 2023

Resuscitation Plus

Self Cite

View full text Add to dashboard Cite

Individualized decision making in on-scene resuscitation time for out-of-hospital cardiac arrest using reinforcement learning

Choi,

Lim,

Hong

et al. 2024

npj Digit. Med.

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On-scene resuscitation time is associated with out-of-hospital cardiac arrest (OHCA) outcomes. We developed and validated reinforcement learning models for individualized on-scene resuscitation times, leveraging nationwide Korean data. Adult OHCA patients with a medical cause of arrest were included ( N = 73,905). The optimal policy was derived from conservative Q-learning to maximize survival. The on-scene return of spontaneous circulation hazard rates estimated from the Random Survival Forest were used as intermediate rewards to handle sparse rewards, while patients’ historical survival was reflected in the terminal rewards. The optimal policy increased the survival to hospital discharge rate from 9.6% to 12.5% (95% CI: 12.2–12.8) and the good neurological recovery rate from 5.4% to 7.5% (95% CI: 7.3–7.7). The recommended maximum on-scene resuscitation times for patients demonstrated a bimodal distribution, varying with patient, emergency medical services, and OHCA characteristics. Our survival analysis-based approach generates explainable rewards, reducing subjectivity in reinforcement learning.

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Expedited transport versus continued on-scene resuscitation for refractory out-of-hospital cardiac arrest: A systematic review and meta-analysis

Cited by 2 publications

References 43 publications

Expedited transport versus continued on-scene resuscitation for refractory out-of-hospital cardiac arrest: A systematic review and meta-analysis

Expedited transport versus continued on-scene resuscitation for refractory out-of-hospital cardiac arrest: A systematic review and meta-analysis

Individualized decision making in on-scene resuscitation time for out-of-hospital cardiac arrest using reinforcement learning

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