This study is a prospective, open-label, randomized controlled trial designed to evaluate a new artificial intelligence (AI) tool for heart monitoring. Researchers will use an AI-enabled electrocardiography (ECG) system to screen patients before they undergo surgery. The main goal is to determine if this AI system can accurately detect pulmonary hypertension and related heart diseases in the preoperative setting. The study is being conducted at Taipei Veterans General Hospital.
This is an open-label, prospective, randomized controlled trial at Taipei Veterans General Hospital. Approximately 1,380 adult patients who already have a preoperative electrocardiogram (ECG) scheduled as part of routine care and have an established plan for elective surgery will be enrolled, along with approximately 30-60 participating physicians responsible for preoperative assessment and perioperative clinical care. The study evaluates whether integrating the Taiwan Medical Imaging Pulmonary Hypertension Detection System (TAIMedImg PHDS), an ECG-based clinical decision-support tool, during the preoperative preparation period can enable earlier identification of patients at risk of pulmonary hypertension and cardiopulmonary complications, and supports assessment of the potential cost-effectiveness of earlier risk recognition. Patients are randomized to determine whether their responsible participating physician will receive TAIMedImg PHDS output derived from the patient's routine ECG. In the intervention arm, research staff upload the ECG to TAIMedImg PHDS and provide the analysis result to the participating physician; all other processes proceed as usual care. In the control arm, usual care proceeds without provision of TAIMedImg PHDS output. Randomization affects only access to this supplementary ECG-based output; it does not change patients' scheduled tests, clinical workflow, or rights to care. Clinical evaluation and management remain at the physician's discretion according to standard practice. The study measures physicians' responses to ECG interpretation with versus without TAIMedImg PHDS output and documents the clinical decision-making trajectory, using routinely available medical record data for analysis. Results may inform improved preoperative pulmonary hypertension risk assessment and future perioperative care.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
1,380
The intervention involves using an artificial intelligence-enabled electrocardiography system to analyze standard ECGs for the preoperative detection of pulmonary hypertension.
Taipei Veterans General Hospital
Taipei, Taiwan
The incidence of newly diagnosed pulmonary hypertension or pulmonary hypertension-related cardiopulmonary diseases
The incidence of newly diagnosed pulmonary hypertension (defined as an echocardiographic right ventricular systolic pressure \> 50 mmHg) or pulmonary hypertension-related cardiopulmonary diseases before surgery, or within 90 days after electrocardiography in patients who did not undergo surgery.
Time frame: Before surgery, or within 90 days after electrocardiography in patients who did not undergo surgery.
Incidence of Surgical Complications
Comparison of the incidence rates of surgical complications between the two groups.
Time frame: From the date of surgery up to 3 months post-operation.
Length of Hospital Stay
Comparison of the total duration of hospitalization (in days) between the intervention and control groups.
Time frame: From admission until hospital discharge (assessed up to 3 months).
Cardiovascular Mortality
Evaluation of the rates of cardiovascular-related death between the two groups during the postoperative observation period.
Time frame: From the date of surgery up to 3 months post-operation.
All-Cause Mortality
Evaluation of the rates of all cause mortality between the two groups during the postoperative observation period.
Time frame: From the date of surgery up to 3 months post-operation.
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