Artificial Intelligence for Pulmonary Embolism

(ASCENT Trial)

Overseen By Jun Li, MD

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: University Hospitals Cleveland Medical Center

Disqualifiers: Age <18, Pregnancy, Unable to walk, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 30

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial explores the use of artificial intelligence (AI) to assist doctors in deciding whether to call a special team to treat patients with pulmonary embolism (PE), a serious condition where blood clots block blood vessels in the lungs. The AI, known as Aidoc, will help identify patients who might need extra care and compare this approach's effectiveness against past methods. Participants in the trial will be randomly assigned to receive either traditional medical therapy or an early-invasive strategy, which may involve direct treatments like catheter procedures. Candidates for this study include those who have had a CT scan showing a pulmonary embolism and certain heart stress indicators. As an unphased trial, this study offers participants the chance to contribute to innovative research that could improve future PE treatments.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

What prior data suggests that this AI algorithm is safe for use in activating PERT?

Research shows that the AI tool used in this trial, Aidoc, has FDA approval for diagnosing blood clots in the lungs, known as pulmonary embolism (PE). Studies have demonstrated that this AI can quickly identify patients at high risk for PE, enabling doctors to diagnose and treat them sooner. The AI accurately identifies the most serious PE cases, with evidence showing it correctly found all confirmed high-risk cases in past tests.

The FDA approval indicates a strong safety record for its use in diagnosing and managing PE. No specific reports have linked negative effects directly to the AI's use in patient care. This approval and these findings offer reassurance about the safety and reliability of using Aidoc in medical settings. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the trial of Aidoc for pulmonary embolism because it leverages artificial intelligence to enhance diagnosis and treatment strategies. Unlike traditional methods that rely heavily on manual assessment and experience-based decision-making, Aidoc uses AI to quickly and accurately identify pulmonary embolisms in imaging scans. This could potentially lead to faster diagnosis and more targeted interventions. Additionally, the trial explores an early-invasive strategy using catheter-directed therapies, which could offer more immediate relief and improve outcomes for patients compared to standard medical therapy alone.

What evidence suggests that this AI algorithm is effective for activating PERT in pulmonary embolism cases?

Research has shown that using artificial intelligence (AI) to manage pulmonary embolism (PE) can greatly improve patient outcomes. In this trial, participants may receive an early-invasive strategy where AI guides catheter-directed therapies. Studies indicate that AI can identify more cases of PE that might otherwise be missed, leading to better treatment choices. For example, one AI system reduced stays in the ICU and hospital by an average of three days each. Another study found that AI cut the time spent in the intensive care unit by about 33.5%. These findings suggest that AI can make PE care more efficient and effective, potentially saving time and helping patients recover faster. ^{3 5 6 7 8}

Who Is on the Research Team?

Jun Li, MD

Principal Investigator

University Hospitals

Are You a Good Fit for This Trial?

This trial is for patients with pulmonary embolism, a condition where blood clots block the lungs' arteries. It's designed to help those who might benefit from quick and aggressive treatment. Details on specific inclusion or exclusion criteria are not provided.

Inclusion Criteria

I have a lung clot and heart strain shown in a CT scan, with either high heart rate, fast breathing, low blood pressure, or low oxygen levels.

My doctor thinks I should consider enzyme replacement therapy.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Active Phase

Participants undergo randomization to early-invasive strategy or traditional medical therapy, including walk testing and assessment by PERT

30 days

Daily visits during hospital stay

Follow-up

Participants are monitored for safety and effectiveness after treatment, including quality of life assessments

90 days

Visits at 30 days and 90 days

What Are the Treatments Tested in This Trial?

Interventions

• Aidoc

Trial Overview The study tests an AI program called Aidoc that decides which patients need urgent care for their pulmonary embolism. It compares outcomes of patients selected by AI for immediate action versus traditional methods.

How Is the Trial Designed?

Group I: Early-Invasive Strategy Experimental Treatment 1 Intervention

Patients who do not clearly qualify for early intervention (including catheter-directed therapies, systemic thrombolysis, or invasive hemodynamic support) based on assessment by PERT members, will undergo walk testing on the first day of admission. If the subject meets criteria based on pre-specified hemodynamic changes, then the patient will be randomized in a 2:1 fashion to early invasive strategy with catheter-directed therapies as treatment arm.

Group II: Traditional Medical Therapy Active Control 1 Intervention

Patients who do not clearly qualify for early intervention (including catheter-directed therapies, systemic thrombolysis, or invasive hemodynamic support) based on assessment by PERT members, will undergo walk testing on the first day of admission. If the subject meets criteria based on pre-specified hemodynamic changes, then the patient will be randomized (2:1, treatment to control) to traditional routine care with medical therapy.

Who Is Running the Clinical Trial?

University Hospitals Cleveland Medical Center

Lead Sponsor

Trials

348

Recruited

394,000+

Inari Medical

Industry Sponsor

Trials

18

Recruited

5,300+

Citations

1. aidoc.com aidoc.com/learn/clinical-studies/clinical-outcome-of-incidental-pulmonary-embolism-detected-by-artificial-intelligence-software-a-retrospective-analysis/

Clinical Outcome Of iPE Detected By AI Software 45 cases were positive by both AI and radiologist report and AI detected 23 additional discordant positive cases.87% (20/23) were considered TP on secondary ...

2. aidoc.com aidoc.com/learn/clinical-studies/cost-effectiveness-analysis-ai-driven-pert/

Cost-Effectiveness Analysis of AI-Driven PERT Activation AI-driven PERT activation for mechanical thrombectomy in acute PE patients was associated with reduced ICU and hospital stays by an average of three days each.

3. aidoc.com aidoc.com/learn/clinical-studies/improving-patient-outcomes-ai-enhanced/

Improving Patient Outcomes with AI-Enhanced PERT The study involved a retrospective review of patients with suspected acute pulmonary embolism (PE), comparing outcomes before and after AI implementation.

4. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC11991795/

Independent Evaluation of a Commercial AI Software for ... The objective of this study is to provide a retrospective, independent assessment of the CE–marked and FDA–approved AI algorithm for IPE detection (Aidoc, Tel ...

5. evtoday.com evtoday.com/news/aidocs-ai-solution-for-pe-management-evaluated-in-three-single-center-studies

Aidoc's AI Solution for PE Management Evaluated in Three ... The mean length of stay in the intensive care unit decreased by 33.5% (pre-AI: 2.30 days; post-AI: 1.53 days), while the mean length of stay in ...

6. aidoc.com aidoc.com/learn/blog/pulmonary-embolism-ai/

Pulmonary Embolism AI Solution | Impact On Diagnosis The AI solution enables rapid risk assessment, shortens time to treatment, helps build standardized protocols, and shortens time to PERT activation.

7. aidoc.com aidoc.com/learn/blog/pe-risk-stratification-how-ai-helps/

PE Risk Stratification and How AI Can Help PE risk stratification is categorizing patients by risk to prioritize treatment. AI helps by identifying high-risk patients, improving early diagnosis and care.

8. aidoc.com aidoc.com/learn/blog/advancements-in-pe-management-aidocs-impact/

Studies Share a Glimpse into Aidoc's Impact on PE ... The system's precision in identifying the most critical patients was also evident, successfully identifying 100% of confirmed High-Risk PE cases ...