Cardiovascular Diseases, Intensity Care, Morality
Conditions
Brief summary
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.
Interventions
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.
Sponsors
National Defense Medical Center, Taiwan
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SCREENING
Masking
SINGLE (Subject)
Intervention model description
intervention group:8001 control group:7964
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Patients in emergency department or inpatient department. * Patients recieved at least 1 ECG examination.
Exclusion criteria
* The patients recieved ECG at the period of inactive AI-ECG system.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| All cause mortality (death) | Within 90 days | After performing an electrocardiogram, the patient's survival is tracked. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Cardiovascular cause mortality (death) | Within 90 days | After performing an electrocardiogram, the patient's survival is tracked. |
| Arrhythmia medication | Within 12 hours | After performing an electrocardiogram, the patient recieved related intervention. |
| Electrolyte examination | Within 3 days | After performing an electrocardiogram, the patient recieved electrolyte examination |
| Cadiac examination | Within 3-7 days | After performing an electrocardiogram, the patient recieved cadiac examination |
Countries
Taiwan
Outcome results
None listed