Clinical trial Recruiting at 1 site Interventional Ages 18 and up

AI-powered decision support to boost thrombolysis for ischemic stroke

Official title: Artificial Intelligence-Assisted Decision Support for Intravenous Thrombolysis in Acute Ischemic Stroke at Basic Hospitals in China (ASSIST)

Run by Capital Medical University · NCT07785492 · Data updated 2026-11-12

This trial tests whether an AI-assisted decision tool helps doctors give intravenous thrombolysis to eligible ischemic stroke patients within 24 hours at a primary hospital in China, compared with standard care.

Quick facts

Study typeInterventional
Ages18 Years and up
SexAll
Enrollment516 (estimated)
SponsorCapital Medical University
Academic / other
Locations1 site (Changsha, Hunan)
StatusRecruiting
StartedAugust 26, 2026
Main results expectedDecember 31, 2026
Study endsMarch 31, 2027
Registry record updatedAugust 27, 2026
Trial IDNCT07785492 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Adults 18 or older with acute ischemic stroke, last known well within 24 hours, confirmed without hemorrhage, and able to provide consent or have a representative.

Probably not a fit

Patients outside the 24-hour window, those with contraindications to thrombolysis, or environments where the AI tool cannot be effectively implemented may not benefit.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This is a single-center, randomized, open-label trial with blinded endpoints comparing an AI-assisted thrombolysis decision tool added to routine care versus standard guidelines. Cluster randomization occurs at the level of attending physicians. The study measures whether the AI tool increases the proportion of patients treated with intravenous thrombolysis within 24 hours of onset and examines effects on clinical outcomes, treatment timelines, and safety. Eligible adults with acute ischemic stroke within 24 hours, confirmed imaging, and consent are enrolled at Liuyang Jili Hospital under Capital Medical University guidance. The trial does not alter standard care except for the AI tool guidance, and no delays to care are permitted for research purposes.

Why it matters

Potential benefit: If successful, the AI tool could help more patients receive timely thrombolysis and potentially improve outcomes after acute ischemic stroke.

How similar studies have gone: Previous work in AI-assisted decision support for stroke care has shown promise in aiding treatment decisions, but evidence for widespread impact on thrombolysis rates remains evolving.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

1. Age ≥18 years.
2. Clinical diagnosis of acute ischemic stroke.
3. Onset time (last known well) \<24 hours.
4. CT or MRI examination excluding intracerebral hemorrhage.
5. Signed informed consent by the patient or a legally authorized representative

Exclusion Criteria:

1. Currently participating in another interventional clinical trial related to drugs or devices.
2. Pregnant women.
3. Has received intravenous thrombolysis at another hospital.
4. Has completed a definitive reperfusion therapy decision at another hospital and is transferred to this hospital solely for follow-up observation or rehabilitation.

Where it's running

  • Liuyang Jili Hospital
    Changsha, Hunan, China
    Recruiting

Study contacts

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.