Artificial Intelligence Identified Dyskalemia Using Electrocardiogram (AIDE)

NCT ID: NCT05118022

Last Updated: 2024-09-19

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 14989 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-01-01
• Study Completion Date: 2023-02-28

Brief Summary

This is a randomized controlled trial (RCT) to test a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis and management of potassium abnormalities.

Conditions

Hyperkalemia; Hypokalemia

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: SCREENING
• Blinding Strategy: NONE

Study Groups

Intervention

Patients randomized to intervention will be cared by physicians under AI-ECG support.

Group Type: EXPERIMENTAL

Artificial Intelligence identified Dyskalemia using Electrocardiogram (AIDE) system

Intervention Type: OTHER

Once the AIDE indicates high risk of dyskalemia, an obvious message by scarlet letter was appeared in the HIS operation interface to corresponding physicians. To avoid the alert fatigue, we selected the cut-off points with expected positive predictive values of ≥40% according to previous data, which was the consensus of enrolled physicians before the trial considering the clinical loading. The physicians received the AIDE alerts as long as they were operating HIS logged in by their account, even if they were caring other patients. Physicians can review the AIDE predictions of patients in the intervention group. Therefore, this was a single-blind study since HIS presented different information for patients in intervention and control groups. The participated physicians understood the likelihood of dyskalemia and cardiac risk for those patients with ECG-dyskalemia, and provided suitable medical care according to patients' conditions.

Control

Patients randomized to control will be cared by routine practice.

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

Artificial Intelligence identified Dyskalemia using Electrocardiogram (AIDE) system

Once the AIDE indicates high risk of dyskalemia, an obvious message by scarlet letter was appeared in the HIS operation interface to corresponding physicians. To avoid the alert fatigue, we selected the cut-off points with expected positive predictive values of ≥40% according to previous data, which was the consensus of enrolled physicians before the trial considering the clinical loading. The physicians received the AIDE alerts as long as they were operating HIS logged in by their account, even if they were caring other patients. Physicians can review the AIDE predictions of patients in the intervention group. Therefore, this was a single-blind study since HIS presented different information for patients in intervention and control groups. The participated physicians understood the likelihood of dyskalemia and cardiac risk for those patients with ECG-dyskalemia, and provided suitable medical care according to patients' conditions.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Patients in emergency department.
• Patients recieved at least 1 ECG examination.

Exclusion Criteria

• Patients recieved dyskalemia-related treatment before ECG examination.
• The patients recieved ECG at the period of inactive AI-ECG system.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

National Defense Medical Center, Taiwan

OTHER

Sponsor Role: lead

Responsible Party

Chin Lin

Associate Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

National Defense Medical Center

Taipei, , Taiwan

Countries

Taiwan

Other Identifiers

NDMC2021004

Identifier Type: -

Identifier Source: org_study_id