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AI-Guided Intensified Follow-up After Surgery for Acute Type A Aortic Dissection (AIMS-ATAAD-FU)

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Zhejiang University

Status

Begins enrollment in 5 months

Conditions

Postoperative Aortic Dissection Follow-up
Stanford Type A Aortic Dissection
Acute Type A Aortic Dissection

Treatments

Other: Usual Postoperative Follow-up Strategy
Other: AI Prediction Model-Guided Intensified Follow-up Strategy

Study type

Interventional

Funder types

Other

Identifiers

NCT07623213
ATAAD-AI-RCT-001

Details and patient eligibility

About

This multicenter, prospective, randomized controlled trial will evaluate whether an artificial intelligence (AI) multimodal prediction model-guided intensified follow-up strategy improves 1-year outcomes after surgery for acute Stanford type A aortic dissection. Eligible adult patients who have undergone open surgical repair or open plus endovascular/hybrid repair and are clinically stable to enter the postoperative follow-up phase will be randomized 1:1 to usual postoperative follow-up or AI-guided intensified follow-up. The AI-guided arm will receive usual follow-up plus an AI-generated risk stratification report for 1-year mortality and adverse aortic remodeling. Higher-risk patients may receive more frequent follow-up, prioritized CTA review, multidisciplinary assessment, and targeted management reminders. The primary outcome is all-cause mortality through postoperative day 365. Key secondary outcomes include aortic reintervention, adverse aortic remodeling, and ICU readmission within 1 year.

Full description

Acute Stanford type A aortic dissection is a life-threatening aortic disease. Even after successful surgical repair, patients may experience death, residual dissection progression, false lumen patency, distal aortic dilation, reintervention, infection, renal dysfunction, readmission, or other adverse outcomes during the first postoperative year. Current follow-up pathways may not fully integrate longitudinal clinical, biochemical, CTA imaging, and hemodynamic/biomechanical information for individualized risk management.

This study is a multicenter, prospective, randomized, controlled, open-label trial with blinded endpoint adjudication. It tests whether embedding a previously developed and validated AI multimodal prediction model into the postoperative follow-up pathway can identify high-risk patients earlier, improve completion of imaging follow-up, trigger multidisciplinary review, and support intensified management, thereby improving 1-year clinical outcomes.

Eligible participants will be adults with acute Stanford type A aortic dissection who have undergone open surgery or open combined with endovascular/hybrid repair, have stable postoperative status, and are ready for discharge or early postoperative follow-up. After written informed consent and confirmation of eligibility, participants will be randomized in a 1:1 ratio to usual postoperative follow-up or AI prediction model-guided intensified follow-up. Randomization is planned to be center-stratified with block randomization, with optional pre-specified stratification by early postoperative risk, DeBakey type, or Penn class according to the final randomization plan.

The usual follow-up group will receive each center's standard ATAAD postoperative follow-up pathway, including discharge education, blood pressure and medication management, outpatient and telephone follow-up, and CTA or ultrasound review according to local practice. The AI-guided intensified follow-up group will receive usual follow-up plus an AI-generated risk report classifying participants as low, moderate, high, or very high risk for 1-year mortality and adverse aortic remodeling. Depending on the risk level, clinicians may arrange intensified telephone or outpatient follow-up, earlier or prioritized CTA review, multidisciplinary team discussion, reminders for blood pressure, renal function, infection or nutritional management, rapid review of abnormal imaging findings, and reintervention assessment pathways. The AI report is an auxiliary decision-support tool and does not replace guideline-based care, imaging review, or the treating surgical team's judgment.

The planned total sample size is 1,314 participants, approximately 657 per group, allowing for 10% loss to follow-up or major protocol deviation. The primary endpoint is all-cause mortality from randomization through postoperative day 365. Key secondary endpoints include 1-year aortic reintervention, adverse aortic remodeling, and ICU readmission. Other secondary outcomes include aorta-related death, unplanned readmission, major adverse cardiovascular events, stroke, renal failure or continuous renal replacement therapy, infection, imaging follow-up completion, follow-up adherence, and execution of AI-triggered follow-up actions. Outcome events will be supported by hospital records, follow-up data, death registry information where available, imaging core laboratory review, AI system logs, and blinded Clinical Event Committee adjudication.

Enrollment

1,314 estimated patients

Sex

All

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • 1. Age 18 years or older. 2. Acute Stanford type A aortic dissection confirmed by CTA, intraoperative findings, or medical records.

    3. Underwent open surgical repair or open repair combined with endovascular/hybrid repair.

    4. Postoperative condition is stable and the patient is planned for discharge or has entered early post-discharge follow-up.

    5. Core baseline data required for AI model operation are available, including at least one eligible preoperative or postoperative CTA imaging dataset.

    6. Able to complete telephone, outpatient, or inpatient follow-up and willing to provide written informed consent.

Exclusion criteria

  • 1. Predominantly chronic type A dissection, traumatic dissection, or iatrogenic dissection, if the investigator judges the patient unsuitable for this follow-up strategy study.

    2. Did not undergo surgical repair, received only palliative treatment, or did not meet postoperative randomization conditions.

    3. Expected inability to complete 12-month follow-up, no stable contact information, or inability to obtain outpatient, telephone, or inpatient follow-up data.

    4. Severe missing baseline data preventing generation of the AI risk report. 5. Concurrent participation in another interventional study that may substantially affect postoperative follow-up intensity or the primary outcome.

    6. Any other condition that, in the investigator's judgment, makes the patient unsuitable for participation.

Trial design

Primary purpose

Health Services Research

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Single Blind

1,314 participants in 2 patient groups

Usual Postoperative Follow-up Strategy
Active Comparator group
Description:
Participants will receive the existing postoperative follow-up pathway at each center after ATAAD repair, including routine discharge education, blood pressure and medication management, outpatient or telephone follow-up, CTA or ultrasound follow-up according to center practice, and management of abnormal findings through routine clinical pathways. AI risk stratification reports will not be provided to the clinical team in this arm, except for ethically required safety information if applicable.
Treatment:
Other: Usual Postoperative Follow-up Strategy
AI Prediction Model-Guided Intensified Follow-up Strategy.
Experimental group
Description:
Participants will receive usual postoperative follow-up plus AI-generated risk stratification for 1-year mortality and adverse aortic remodeling. The risk report will classify participants as low, moderate, high, or very high risk. Higher-risk participants may receive more frequent follow-up, earlier or prioritized CTA review, active telephone tracking, multidisciplinary team discussion, rapid review of abnormal imaging findings, and reintervention risk assessment. The AI report is auxiliary and does not replace physician judgment.
Treatment:
Other: AI Prediction Model-Guided Intensified Follow-up Strategy

Trial contacts and locations

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Central trial contact

Cai Cheng, MD, PhD

Data sourced from clinicaltrials.gov

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