ScholarWorks@성균관대학교

초록

This study develops a CPR prediction model using initial admission data in the emergency department. We retrospectively analyzed EMR data from Severance Hospital (2018-2022), excluding patients aged under 18 or without initial vital signs and KTAS, and those with DNR orders. We developed and compared two models: one using patient information and initial vital signs and another incorporating KTAS. The model with KTAS showed significantly better predictive performance. Our findings suggest that combining vital signs and KTAS can effectively predict CPR, helping to prevent cardiac arrest.

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