Deep Learning Based Early Warning Score in Rapid Response Team Activation

• Conditions: Hospital Rapid Response Team; Hospital Medical Emergency Team

• Registration Number: NCT04951973
• Lead Sponsor: Seoul National University Hospital

Brief Summary

The objective of this study is to evaluate the safety and clinical usefulness of the Deep learning based Early Warning Score (DEWS).

Detailed Description

SPTTS is the representative trigger tracking system. In addition to the conventional SPTTS, DEWS will be calculated at each time point by the previously developed algorithm. SPTTS and DEWS will be shown simulataneously on the screening board. The rapid response team performs the rescue activity as before, using both SPTTS and DEWS simultaneously.

The alarm threshold setting of DEWS will be changed to 70 points, 75 points, and 80 points every month.

The primary and secondary outcomes will be evaluated to compare SPTTS and DEWS (based on each threshold).

Study Timeline

• Status Verified: 2021-06
• Study First Submitted: 2021-06-27
• Study First Submitted QC: 2021-06-30
• Last Update Submitted: 2021-06-30
• Study First Posted: 2021-07-07
• Last Update Posted: 2021-07-07
• Study Start: 2021-08-01
• Primary Completion: 2021-12-30
• Study Completion: 2022-04-30

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 50000

Inclusion Criteria

• Patients admitted to general ward and monitored by in-hospital rapid response system

Exclusion Criteria

• patients admitted to pediatric ward
• patients in emergency room, intensive care unit, and operating room

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
In-hospital cardiac arrest	3 month	Compare the predictability of in-hospital cardiac arrest between DEWS and SPTTS.

Secondary Outcome Measures

Name	Time	Method
Total alarm count.	3 month	Compare the total alarm count between DEWS and SPTTS.
Alarm coincidence	3 month	Evaluate the alarm coincidence between DEWS and SPTTS.