ClinicalTrials.gov
public full text
Public Domain
RCT aiTriage Chest Pain Risk Stratification
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.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Rule Out Myocardial Infarction by Computer Assisted Tomography#918007
- The Percutaneous Coronary Intervention Registry in University Medical Center of Ho Chi Minh City#832355
- Automated Cardioverter Defibrillator in Children#1047349
- Coronary CT Angiography as the Primary Initial Method of Evaluating Patients With Subacute Chest Pain (CT PRIME)#1093390
- Alert-HF: Early Detection and Intervention on Atrial Fibrillation in Heart Failure Patients#1095962
Record · ID 876659
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive