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NCT07316049Not yet recruiting

Construction and Evaluation of an Intelligent Decision System for Reperfusion Therapy in Acute Ischemic Stroke

Source: ClinicalTrials.gov · Last updated 4 Jun 2026

Brief summary (registry, in English)

This multicenter, cluster-randomized controlled trial will evaluate the effectiveness and safety of the LingBao System, an AI-enabled clinical decision support platform for reperfusion therapy in acute ischemic stroke (AIS). Twenty certified stroke centers will be randomized 1:1 to LingBao-assisted care or standard care. Consecutive patients aged 18 years or older who present within 24 hours of symptom onset or last-known-well and are evaluated for intravenous thrombolysis and/or endovascular therapy will be prospectively enrolled. The study initially plans to enroll approximately 3,000 patients from about 20 certified stroke centers, with approximately 150 patients per center. Because this is a cluster-randomized trial, a pre-specified blinded sample size re-estimation will be performed after approximately 40% of participants have completed the 90-day mRS assessment. The re-estimation will be based only on pooled, blinded information, including cluster size, cluster-size variability, intracluster correlation, follow-up completeness, missingness of the primary outcome, and the overall distribution of the 90-day mRS. No between-group treatment effect will be examined, and any sample size adjustment will only allow an increase in enrollment. At intervention sites, clinicians may use the LingBao System during their routine workflows. The platform integrates routinely available clinical and imaging data, automatically estimates onset-to-treatment windows, screens contraindications, and provides evidence-based, guideline-concordant recommendations for reperfusion therapy; all treatment decisions remain at physician discretion. The primary endpoint is the 90-day modified Rankin Scale (mRS) score analyzed by ordinal shift. Secondary endpoints include workflow metrics (door-to-needle time and door-to-puncture time), reperfusion treatment rates, early neurological improvement, symptomatic intracranial hemorrhage, and mortality. The findings will provide real-world evidence on the clinical value of AI-assisted decision support for reperfusion therapy in AIS and inform broader implementation of intelligent stroke management systems.

Status (registry)
Not yet recruiting
Study type
Interventional
Enrollment
3000 (estimated)
First submitted
2 Dec 2025
Start date
15 Jun 2026
Primary completion date
31 Oct 2026
Lead sponsor
Second Affiliated Hospital, Zhejiang University, School of Medicine
Diseases
Stroke
NCT number
NCT07316049

What you commit to

  • Study type: Interventional
  • Planned participants: 3000
  • From 15 Jun 2026 to the primary completion date, 31 Oct 2026
  • No sites listed in no country
  • Visits and tests: ask the trial team, the registry does not list them

Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.

Who cannot take part

Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.

Prior treatment

  • Prior participation in other AI-based decision support trials within the past 12 months.

Other

  • Absence of key clinical or imaging data necessary for analysis.
  • Patients not undergoing reperfusion assessment or outside the pre-defined workflow.
  • Explicit refusal of data use or withdrawal of consent (if applicable).

Who the study is looking for

  • Age ≥ 18 years.
  • Clinical diagnosis of acute ischemic stroke (AIS).
  • Presentation within 24 hours of symptom onset or last-known-well.
  • Evaluated for reperfusion therapy (intravenous thrombolysis and/or endovascular treatment).

Age in the registry: 18 years to - · Sex: All · Does not accept healthy volunteers

Full criteria on ClinicalTrials.gov

This page is information, not medical advice. Discuss any trial with your doctor.