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Based on data from the American Heart Association's (AHA) Get With the Guidelines-Resuscitation (GTWG-R) registry, the incidence of adult treated in-hospital cardiac arrest (IHCA) was about 10 per 1,000 bed-days (290,000 patients per year), and 15 to 20% of adult IHCA patients survived to hospital discharge (i.e., ~80% mortality). Despite the significant morbidity and mortality caused by IHCA, ED-based IHCA is surprisingly less studied. The investigators have utilized electronic medical record (EMR)'s big data (>700,000 visits) from our hospital to investigate, for the first time, the epidemiology and outcome of IHCA in the ED in Taiwan. The investigators also have developed and validated a simple prediction tool for ED-based IHCA, the Emergency Department In-hospital Cardiac Arrest Score (EDICAS). This tool has also been externally validated using Far Eastern Memorial Hospital's ED data. In addition, the investigators also have developed and validated a vital-sign trajectory-based longitudinal model (group-based trajectory modeling [GBTM]) to predict ED-based IHCA.
Based on these studies, the investigators now propose to (1) Embed the EDICAS into our hospital information system (HIS) in real-time at ED triage to identify high-risk patients (EDICAS 6+); and (2) Distribute wearable smart wristbands to high-risk patients to augment vital signs monitoring and send alerts based on GBTM results. The detection and intervention components together form the rapid response system, the Emergency Department In-hospital Cardiac Arrest Response System (EDICARS). In this study, the investigators will enroll and randomize 10 attending physicians into the EDICARS or the usual care arm for 3 months, with each of them treating 100 patients (patients clustered within physicians). The trial will stop for 2 months as a wash-out period, and an interim analysis will be performed. The physicians will then cross over, and each of them will treat 100 patients for another 3 months. A total of 2,000 adult patients will be enrolled. The primary outcome is a composite rate of ED-based IHCA and intensive care unit (ICU) admission. The secondary outcomes include time from ED triage to ED-based cardiac arrest, ICU and hospital length of stay, early ward-based IHCA, and early ICU transfer.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| EDICARS | Experimental |
| |
| Usual care | Active Comparator |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| EDICARS | Other | The investigators propose to (1) Embed the EDICAS into our hospital information system (HIS) in real-time at ED triage to identify high-risk patients (EDICAS 6+); and (2) Distribute wearable smart wristbands to high-risk patients to augment vital signs monitoring and send alerts based on GBTM results. The detection and intervention components together form the rapid response system, the Emergency Department In-hospital Cardiac Arrest Response System (EDICARS). |
| Measure | Description | Time Frame |
|---|---|---|
| ED-based in-hospital cardiac arrest (IHCA) and intensive care unit (ICU) admission. | The primary outcome is a composite rate of ED-based IHCA and intensive care unit (ICU) admission. | During the stay in the emergency department, a median length of 3 hours |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Chu-Lin Tsai, MD | Contact | +886-2-2312-3456 | 67684 | chulintsai@ntu.edu.tw |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| National Taiwan University Hospital | Recruiting | Taipei | Taiwan |
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| ID | Term |
|---|---|
| D006323 | Heart Arrest |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
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| Usual care | Other | Usual care will be assigned to this arm. No additional interventions. |
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