Verification of clinical efficacy of artificial intelligence based prediction system of cardiac arrest: a Multicenter Randomized Trial

Verification of clinical efficacy of artificial intelligence based prediction system of cardiac arrest in general ward admitted patients : a Multicenter Pragmatic Cluster Randomized Trial

Status

Active, not recruiting

Phases

Phase 4

Study type

Interventional

Source

CRIS

Registry ID

KCT0010243

Enrollment

72695

Registered

2025-02-28

Start date

2025-04-01

Completion date

Unknown

Last updated

2026-08-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

Medical Device : This study is designed as a Stepped-Wedge, Cluster Randomized, Pragmatic Trial (SW-CRT) involving four hospitals, each forming a cluster. To minimize inter-cluster differences, hospit

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Patients 19 years of age or older who are admitted to a general ward

Exclusion criteria

Exclusion criteria: Patients under 19 years of age Suspected computational error due to missing all of the of basic vital signs after hospitalization, including SBP/DBP, HR, BT, and RR

Design outcomes

Primary

Measure	Time frame
General Ward IHCA incidence rate	—

Secondary

Measure	Time frame
In hospital mortality;Intensive care unit (ICU) stay;Hospital stay;Intensive care unit (ICU) transfer time after DeepCARS™ elevation;Cerebral Performance Catergories Score after IHCA;Primary and Secondary Outcomes(Target vs Nontarget)	—

Countries

Korea, Republic of

Contacts

Public ContactJung Soo Kim

Inha University Hospital

jungsookim@inha.ac.kr+82-32-890-2114

Outcome results