A Randomized Controlled Trial of an AI-based Decision Support in Emergency Department Chest Pain Patients (AIDE-CP1)
| Registry | NCT07864038, acronym AIDE-CP1 |
|---|---|
| Status | Not yet recruiting |
| Phase | Not applicable |
| Study type | Interventional; randomized, parallel, masking: none, diagnostic |
| Enrollment | 4500 (Estimated) |
| Sponsor | Region Skane (Other); collaborators: Lund University |
| Conditions | Myocardial Infarction, Chest Pain |
| Interventions | AIDE-CP available (Other) |
| Dates | start 2027-01-18 (estimated), primary completion 2027-06-01 (estimated), completion 2027-12-01 (estimated), first posted 2026-10-07, last updated 2026-10-07 |
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All trials for Myocardial Infarction All trials for Chest Pain All trials of AIDE-CP available
The AIDE-CP1 trial will test whether a decision support tool based on artificial intelligence (AI) can improve care for patients who come to an emergency department with chest pain. The AI tool uses the patient's age, sex, first blood tests and ECG to estimate the risk of a heart attack within 30 days and suggests what to do next. About 4,500 patients at five Swedish emergency departments will be included. The study will examine whether the AI tool can shorten time spent in the emergency department while maintaining patient safety. It will also study healthcare use, costs, and how AI affects doctors' decisions.
The AIDE-CP1 trial is a multicenter, randomized controlled trial evaluating whether an artificial intelligence-based clinical decision support system can improve the management of adults presenting to emergency departments (EDs) with chest pain. AIDE-CP integrates age, sex, initial laboratory results, and ECG data to estimate the 30-day probability of acute myocardial infarction (AMI) and provides risk-based management recommendations.
Approximately 4,500 unselected adult chest pain patients will be included across five Swedish EDs. Randomization occurs at the level of the study day, with AIDE-CP either available to clinicians or unavailable, in which case patients receive standard care. The primary outcome is ED length of stay among patients discharged from the ED. Secondary outcomes include 30-day AMI and major adverse cardiac events, admission and discharge rates, time to disposition, downstream healthcare utilization and costs, and effects on overall ED patient flow.
A nested substudy of 400 patients will assess how AIDE-CP influences physicians' estimates of AMI probability and clinical decision-making. The trial is designed to determine whether integrating AI-based risk prediction into routine emergency care can accelerate patient management while maintaining safety, and to provide prospective evidence on the real-world clinical impact of AI-supported decision-making.
| Arm | Type | Interventions | Description |
|---|---|---|---|
| Intervention | Active comparator | Other: AIDE-CP available | AIDE-CP available |
| Control | No intervention | Standard care |
Sex: All, ages: 18 Years to any
Inclusion Criteria: * Non-traumatic chest pain, presentation to the ED. Exclusion Criteria: * Patient declining participation.