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NCT Number: NCT07344207

GUARD-PH: Guided Use of AI-ECG for Risk Detection of PH in Surgery (GUARD-PH Trial)

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.

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Key information

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age between 18 and 80 years.
  • Patients scheduled for non-cardiac surgery under general anesthesia.
  • Patients who have a scheduled standard preoperative electrocardiogram (ECG).
  • Patients capable of understanding the study and willing to provide medical records for research purposes, and who have signed the informed consent form.

Exclusion criteria

  • Patients scheduled for emergency surgery.
  • Patients who explicitly refuse to participate or withdraw consent.
  • Patients with specific comorbidities that interfere with ECG interpretation or data collection (e.g., implanted pacemakers).

Treatment and study plan

Artificial Intelligence-Enabled Electrocardiography System

Diagnostic Test

The intervention involves using an artificial intelligence-enabled electrocardiography system to analyze standard ECGs for the preoperative detection of pulmonary hypertension.

Primary outcomes

  1. The incidence of newly diagnosed pulmonary hypertension or pulmonary hypertension-related cardiopulmonary diseases

    Time frame: Before surgery, or within 90 days after electrocardiography in patients who did not undergo surgery.

    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.

Secondary outcomes

  1. Incidence of Surgical Complications

    Time frame: From the date of surgery up to 3 months post-operation.

    Comparison of the incidence rates of surgical complications between the two groups.

  2. Length of Hospital Stay

    Time frame: From admission until hospital discharge (assessed up to 3 months).

    Comparison of the total duration of hospitalization (in days) between the intervention and control groups.

  3. Cardiovascular Mortality

    Time frame: From the date of surgery up to 3 months post-operation.

    Evaluation of the rates of cardiovascular-related death between the two groups during the postoperative observation period.

  4. All-Cause Mortality

    Time frame: From the date of surgery up to 3 months post-operation.

    Evaluation of the rates of all cause mortality between the two groups during the postoperative observation period.

Study contacts

Contact information is provided by the study sponsor or research team.

Cheng-Hsueh Wu, M.D

CONTACT

[email protected]

886-2-2871-2121

Yu-Feng Hu, M.D.

CONTACT

[email protected]

886-2-2871-2121 ext. #1262

Sponsors and collaborators

Lead sponsor

Taipei Veterans General Hospital, Taiwan

Other Gov

Registry information

Official study title

A Prospective, Open-Label, Randomized Controlled Trial of an Artificial Intelligence Enabled Electrocardiography System for Preoperative Detection of Pulmonary Hypertension and Related Diseases(GUARD-PH)

Acronym: GUARD-PH

Important dates

Study start
2026
Primary completion
2026
Study completion
2027
First posted
Jan 15, 2026
Registry last updated
Jan 15, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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