Work

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

Year: 2025

Type: book-chapter

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.

Source: Studies in health technology and informatics

DOI: 10.3233/shti250414

Authors: Sungsoo Hong, Heejung Hyun, Sungjun Hong

Institutions: Samsung Medical Center, Research Institute for Future Medicine

Language: English

Topic: Cardiac Arrest and Resuscitation

Subfield: Emergency Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W4410447969

FWCI:

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