Patient with chest pain and suspected of acute coronary syndrome Chest pain Acute coronary syndrome MACE Artificial intelligent AI
Conditions
Interventions
When patients visit the ED,
they will be recruit if they meet the inclusion criteria. Participant’s demographic data will be record.
aiTriage probes will be attached at pateint’s arms and leg for analyzing the predicting sco
Experimental Device
AiTriage
Sponsors
Siriraj hospital
TIIM Healthcare
Eligibility
Sex/Gender
All
Age
20 Years to No maximum
Inclusion criteria
Inclusion criteria: 1.Age >20 years 2.Presentation in ED with chest pain that possible for ACS
Exclusion criteria
Exclusion criteria: 1.ST elevation or new LBBB on EKG 2.Terminal illness 3.Patients who are lost to follow-up or transfer to other hospitals within 72-hour 4.EKGs have high percentage of artefacts and ectopic beats
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| severe complication within 72 hours of arrival and within 30 days at the ED if they had at least one of the following complication: death, cardiac arrest, sustained ventricular | — |
Secondary
| Measure | Time frame |
|---|---|
| Major adverse cardiac event At 72 hours and 30 days after ED visit Calculation of sensitivity, specificity and accuracy | — |
Countries
Thailand
Contacts
Public ContactChok Limsuwat
Mahidol University
Outcome results
None listed