Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
This is a randomized controlled trial (RCT) to test a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for early detection of clinical deterioration for reducing mortality.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intervention | Experimental | Patients randomized to intervention will have access to the screening tool. Once the AI-ECG indicates high risk of mortality, a warning message would be immediately triggered and sent to the corresponding attending physicians. Notifications appear in the recipient's smartphone message system for the prompt attention. The message notified the physician that, "An ECG was received for patient X. An ECG indicates high risk of mortality. Please intensively attend to patient's conditions. If the physicians need to further identify the ECG, click on the following link to connect the ECG and the result of AI-ECG prediction." Of note, although we will actively send a warning message for high risk cases, the AI-ECG report for low risk cases still presented the degree of risk. Physicians can check the relative severity by access EHR for patients in the intervention group. |
|
| Control | No Intervention | Patients will continue routine practice. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI-enabled ECG-based Screening Tool | Other | Primary care clinicians in the intervention group had access to the report, which shows the risk prediction results for each patients. Moreover, the clinicians will recieve a short message when patients with a high risk ECG identified by AI. |
| Measure | Description | Time Frame |
|---|---|---|
| All cause mortality (death) | After performing an electrocardiogram, the patient's survival is tracked. | Within 90 days |
| Measure | Description | Time Frame |
|---|---|---|
| Cardiovascular cause mortality (death) | After performing an electrocardiogram, the patient's survival is tracked. | Within 90 days |
| Arrhythmia medication | After performing an electrocardiogram, the patient recieved related intervention. |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| National Defense Medical Center | Taipei | 114 | Taiwan |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 40494963 | Derived | Hsieh PH, Lin C, Lin CS, Liu WT, Lin TK, Tsai DJ, Hung YJ, Chen YH, Lin CY, Lin SH, Tsai CS. Economic analysis of an AI-enabled ECG alert system: impact on mortality outcomes from a pragmatic randomized trial. NPJ Digit Med. 2025 Jun 11;8(1):348. doi: 10.1038/s41746-025-01735-7. | |
| 38684860 | Derived | Lin CS, Liu WT, Tsai DJ, Lou YS, Chang CH, Lee CC, Fang WH, Wang CC, Chen YY, Lin WS, Cheng CC, Lee CC, Wang CH, Tsai CS, Lin SH, Lin C. AI-enabled electrocardiography alert intervention and all-cause mortality: a pragmatic randomized clinical trial. Nat Med. 2024 May;30(5):1461-1470. doi: 10.1038/s41591-024-02961-4. Epub 2024 Apr 29. |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D002318 | Cardiovascular Diseases |
Not provided
Not provided
Not provided
intervention group:8001 control group:7964
Not provided
Not provided
Not provided
|
| Within 12 hours |
| Electrolyte examination | After performing an electrocardiogram, the patient recieved electrolyte examination | Within 3 days |
| Cadiac examination | After performing an electrocardiogram, the patient recieved cadiac examination | Within 3-7 days |