Improving CPR Predictive Model in ED: The Role of Initial Data and KTAS

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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Publication Details

Journal
Studies in health technology and informatics
Published
2025-05-15
DOI
https://doi.org/10.3233/shti250414
Primary Topic
Emergency and Acute Care Studies
Type
article
Field-Weighted Citation Impact
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article

Improving CPR Predictive Model in ED: The Role of Initial Data and KTAS

Sungjun Hong, Heejung Hyun, Sungsoo Hong
Studies in health technology and informatics
Emergency and Acute Care Studies
article

Improving CPR Predictive Model in ED: The Role of Initial Data and KTAS

Sungjun Hong, Heejung Hyun, Sungsoo Hong
article en

Abstract

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.

Studies in health technology and informaticsVol. 327
Samsung Medical Center (KR)
Good health and well-being
Openalex Percentile: Top 75%
Emergency and Acute Care Studies
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