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RCT aiTriage Chest Pain Risk Stratification

NCT07074808 · Status: COMPLETED · Phase: PHASE4 · Type: INTERVENTIONAL · Enrollment: 1120

Last updated 2026-01-08

No results posted yet for this study

Summary

Chest pain is one of the most common reasons people visit the Emergency Department (ED). While most cases are not serious, a small number may lead to life-threatening heart problems, known as Major Adverse Cardiac Events (MACE). Emergency staff need to quickly identify these high-risk patients, but current methods often take time, involve lab tests, and strain already busy EDs.

In Singapore, for example, SGH sees over 120,000 ED patients a year. In the U.S., chest pain accounts for around 8-10 million ED visits annually, yet fewer than 10% are ultimately diagnosed with MACE. Still, over half of chest pain patients undergo extensive and costly testing, adding up to $10-13 billion each year. This over-testing is done to avoid missing a critical case, but it's inefficient and stressful for both staff and patients.

Traditional risk scoring tools like TIMI, GRACE, HEART, and EDACS require time and blood test results, delaying early intervention. Waiting times in EDs can be 1-2 hours, during which patient conditions may worsen unnoticed.

To address this, we've developed aiTriage, a portable device that uses AI to analyze heart rate variability, ECG readings, blood pressure, and oxygen levels. It provides a real-time risk score within 5 minutes, helping doctors decide which patients need urgent care. Unlike current methods, aiTriage works without waiting for lab tests and can ease the load on EDs.

No existing devices offer real-time MACE risk scoring like aiTriage. Our previous studies show that this system outperforms standard tools and could transform how chest pain is managed in emergency care, saving time, money, and lives.

Conditions

Interventions

DEVICE

aiTriage risk score

Risk score generated by AI App aiTriage for chest pain patients

Sponsors & Collaborators

  • Singapore General Hospital

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
SCREENING
Masking
DOUBLE
Model
PARALLEL

Eligibility

Min Age
21 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-11-11
Primary Completion
2025-11-30
Completion
2025-12-29

Countries

  • Singapore

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07074808 on ClinicalTrials.gov