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| ID | Type | Description | Link |
|---|---|---|---|
| RS-2025-02213791 | Other Grant/Funding Number | Korea Health Technology R&D Project |
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This study is to see whether the AI ECG assisted protocol is as safe and efficacious as conventional protocol in early triage of suspected myocardial infarction.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control group | No Intervention | The patients in control group would be managed with usual care using HEART score in addition to recent acute coronary syndrome guideline. | |
| AI-ECG group | Experimental | The patients in AI-ECG group would be managed with the information of the myocardial infarction risk score in AI-ECG in addition to the usual care. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI-ECG | Device | The patients in AI-ECG group would be managed with the information of the myocardial infarction risk score in AI-ECG in addition to the usual care. |
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| Measure | Description | Time Frame |
|---|---|---|
| 30 Days MACE(Major adverse cardiac events) | Death, acute myocardial infarction, stroke, target vessel revascularization, stent thrombosis within 30 days from index visit | 30 days |
| Measure | Description | Time Frame |
|---|---|---|
| Missed acute myocardial infarction at index visit | Missed acute myocardial infarction at index ED visit, but is detected later in anyplace (Outpatient clinic, revisit to ED, or other hospital, etc) | 30 days |
| AI-ECG 30 days MACE prediction performance |
| Measure | Description | Time Frame |
|---|---|---|
| Compliance of medical doctor in AI-ECG low risk group | Compliance of medical doctors to AI-ECG results in AI-ECG low risk group according to the study period(Q1 to Q4), which would be evaluated by discharge rate from ED. | 7 days |
| Compliance of medical doctor in AI-ECG low risk group |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Kyuseok Kim, MD, PhD | Contact | +821047808321 | dreinstein70@gmail.com |
| Name | Affiliation | Role |
|---|---|---|
| KYUSEOK Kim, MD, PhD | CHA University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Asan Medical Center | Recruiting | Seoul | 06628 | South Korea |
The data would be shared with other researchers when they contact to the principal investigator with reasonable context.
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AUROC and AUPRC by continuous AI-ECG score
| 30 days |
| AI-ECG 30 days MACE prediction performance | Sensitivity and specificity by pre-specified cutoff thresholds for Low to intermediate risk or intermediate to high risk | 30 Days |
| AI-ECG 30 days MACE prediction performance | Positive predictive value and Negative predictive value by pre-specified cutoff thresholds for Low to intermediate risk or intermediate to high risk | 30 Days |
| AI-ECG acute myocardial infarction (index visit) discrimination performance | AUROC and AUPRC by continuous AI-ECG score | 30 days |
| AI-ECG acute myocardial infarction (index visit) discrimination performance | Sensitivity and Specificity by pre-specified cutoff thresholds for Low to intermediate risk or intermediate to high risk | 30 Days |
| AI-ECG acute myocardial infarction (index visit) discrimination performance | Positive predictive value and Negative predictive value by pre-specified cutoff thresholds for Low to intermediate risk or intermediate to high risk | 30 Days |
| Medical resources utilization | Length of stay in ED | 30 days |
| Medical resources utilization | early discharge from ED(within 4 hours) | 24 hours |
| Medical resources utilization | Revisit to ED with same symptoms within 1 week | 7 Days |
| Medical resources utilization | Admission rate | 30 days |
| Medical resources utilization | length of stay in hospital | 30 days |
| Medical resources utilization | It would be evaluated by the rate of all additional tests including cardiac CT, coronary angiography, echocardiography, and stress test. | 30 days |
| Medical resources utilization | Direct medical cost | 30 days |
Compliance of medical doctors to AI-ECG results in AI-ECG low risk group according to the study period(Q1 to Q4), which would be evaluated by the rate of no follow-up troponin check. |
| 7 days |
| Compliance of medical doctor in AI-ECG low risk group | Compliance of medical doctors to AI-ECG results in AI-ECG low risk group according to the study period(Q1 to Q4), which would be evaluated by the rate of only baseline and 1 h follow-up troponin check | 7 days |
| Compliance of medical doctor in AI-ECG high risk group | Compliance of medical doctors to AI-ECG results in AI-ECG high risk group according to the study period(Q1 to Q4), which would be evaluated by admission rate. | 7 Days |
| Compliance of medical doctor in AI-ECG high risk group | Compliance of medical doctors to AI-ECG results in AI-ECG high risk group according to the study period(Q1 to Q4), which would be evaluated by the sum rate of additional tests such as coronary artery CT, CAG, stress test. | 7 Days |
| Compliance of medical doctor in AI-ECG high risk group | Compliance of medical doctors to AI-ECG results in AI-ECG high risk group according to the study period(Q1 to Q4), which would be evaluated by the rate of full check up of troponin(0, 1h, 2h). | 7 Days |
| Compliance of medical doctor in AI-ECG high risk group | Compliance of medical doctors to AI-ECG results in AI-ECG high risk group according to the study period(Q1 to Q4), which would be evaluated by time from ED to admission. | 7 Days |
| Compliance of medical doctor in AI-ECG high risk group | Compliance of medical doctors to AI-ECG results in AI-ECG high risk group according to the study period(Q1 to Q4), which would be evaluated by time to CAG. | 7 Days |
| Compliance of medical doctor in AI-ECG high risk group | Compliance of medical doctors to AI-ECG results in AI-ECG high risk group according to the study period(Q1 to Q4), which would be evaluated by cardiology contact rate. | 7 Days |
| Satisfaction score of patients | Satisfaction score using AI-ECG from 1-10 (1 is lowest, 10 is highest) | 7 Days |
| Satisfaction score of medical personnel | Satisfaction score using AI-ECG from 1-10 (1 is lowest, 10 is highest) | 7 Days |
| AI-ECG occlusive myocardial infarction detection performance | AUROC and AUPRC by continuous AI-ECG score | 30 days |
| AI-ECG occlusive myocardial infarction detection performance | Sensitivity and Specificity by pre-specified cutoff thresholds for Low to intermediate risk or intermediate to high risk | 30 days |
| AI-ECG occlusive myocardial infarction detection performance | Positive predictive value and Negative predictive value by pre-specified cutoff thresholds for Low to intermediate risk or intermediate to high risk | 30 days |
| CHA Bundang Medical Center | Recruiting | Seoul | 06628 | South Korea |
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| Ewha Womans University | Recruiting | Seoul | 06628 | South Korea |
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| Gangnam Severance Hospital | Recruiting | Seoul | 06628 | South Korea |
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| Hanyang University | Recruiting | Seoul | 06628 | South Korea |
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| Jeonbuk National University Hospital | Recruiting | Seoul | 06628 | South Korea |
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| Korea University Ansan Hospital | Recruiting | Seoul | 06628 | South Korea |
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| Korea University Guro Hospital | Recruiting | Seoul | 06628 | South Korea |
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| Kyung Hee University Hospital | Recruiting | Seoul | 06628 | South Korea |
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| Samsung Medical Center | Recruiting | Seoul | 06628 | South Korea |
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| Soonchunhyang University Bucheon Hospital | Recruiting | Seoul | 06628 | South Korea |
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| Yonsei University Wonju College of Medicine | Recruiting | Seoul | 06628 | South Korea |
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| ID | Term |
|---|---|
| D009203 | Myocardial Infarction |
| D002637 | Chest Pain |
| D004630 | Emergencies |
| D054058 | Acute Coronary Syndrome |
| ID | Term |
|---|---|
| D017202 | Myocardial Ischemia |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D014652 | Vascular Diseases |
| D007238 | Infarction |
| D007511 | Ischemia |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D009336 | Necrosis |
| D010146 | Pain |
| D009461 | Neurologic Manifestations |
| D012816 | Signs and Symptoms |
| D020969 | Disease Attributes |
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