Evaluating a sepsis prediction machine learning algorithm

Phase 2

• Conditions: Sepsis; sepsis, machine learning, emergency room

• Registration Number: TCTR20230120001
• Lead Sponsor: Chulalongkorn University

Brief Summary

Not available

Detailed Description

Not available

Study Timeline

• Study Start: 2023-01-20
• Study Completion: 2023-05-31
• Last Update Posted: 19 August 2024

Recruitment & Eligibility

• Status: nknown
• Sex: All
• Target Recruitment: 600

Inclusion Criteria

1. Age older than 18 years
2. Non-traumatic patient

Exclusion Criteria

1. Pregnancy

Study & Design

• Study Type: Interventional
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
time to antibiotic time since septic patient registered in emergency room to recieving antibiotic time ( minutes),Percents of sepsis patient that recieved antibiotic within 1 hour since patient registered in emergency room to discharge from emergency room Percents

Secondary Outcome Measures

Name	Time	Method
length of stay in emergency room time since patient registered in emergency room to discharge from emergency room time (minutes),Inhospital mortality ince patient registered in emergency room to discharge from hospital Percents