StrokeNCT04524624
An AI-Based CDSS for Integrated Management of Patients With Acute Ischemic Stroke(GOLDEN BRIDGE II)
A study testing AI-based CDSS in people with Stroke, run by Beijing Tiantan Hospital at 1 site in China.
Trial summary
This study will conduct a cluster randomized controlled trial to evaluate the impact of an artificial intelligence-based clinical decision support system for the integrated management of patients with acute ischemic stroke on the adherence to guideline-based therapies and the incidence of new clinical vascular events. Read more about this study
- Who is it for?
- Ages 18 to 90 years
- Conditions the study is for
- Stroke
- What is being tested?
- AI-based CDSS
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 21,689 participants
- Where
- 1 siteChina
- Study dates
- 1 Sep 2020to 30 Jun 2023
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 90 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Cluster Inclusion Criteria:
- Secondary or tertiary hospitals with an emergency department and neurologic wards that receive patients with AIS.
- Hospitals with available brain MRI scans (1.5T or 3.0T).
- Patient Inclusion Criteria:
- Patients of 18 years or older.
- Patients admitted with neurological deficit consistent with ischemic stroke within 7 days of of symptoms onset. (*Symptom onset is defined by the "last seen normal" principle)
- Confirmation of new ischemic stroke by objective modality of CT scan and MRI (had relevant lesions on DWI).
- Informed consent from patient or legally authorised representative (primarily spouse, parents, adult children, otherwise indicated).
Who cannot join
- Cluster Exclusion Criteria:
- Grade-one hospitals and rural hospitals.
- The specialized hospitals, such as women and children specialist hospital and tumor hospital.
- Hospitals with less than 20 patients with suspected AIS per month.
- Patient Exclusion Criteria:
- Diagnosed DWI negative stroke.
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- Diagnosed other types of cerebrovascular diseases, such as transient ischaemic attack, hemorrhagic stroke, cerebral venous sinus thrombosis, and so on.
- Diagnosed non cerebral vascular disease, such as stroke mimic, seizures, central nervous system infections, metabolic encephalopathy, and so on.
- Received carotid endarterectomy (CEA) and carotid angioplasty and stenting (CAS).
- Involving in other investigational drug or device clinical trials.
- Patients with malignant disease and life expectancy of less than 3 months or patients who are unable to complete the study for other reasons.
- Women who are pregnant or postpartum (≤6 weeks).
- Patients refuse to participate in this study.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: A Multi-centre, Cluster Randomized Controlled Trial of an Artificial Intelligence-Based Clinical Decision Support System for Integrated Management of Patients With Acute Ischemic Stroke: The GOLDEN BRIDGE II Trial
This study will conduct a cluster randomized controlled trial to evaluate the impact of an artificial intelligence-based clinical decision support system for the integrated management of patients with acute ischemic stroke on the adherence to guideline-based therapies and the incidence of new clinical vascular events.
Read the detailed description
Artificial intelligence (AI) and clinical decision support system (CDSS) have demonstrated great progress in the diagnosis and treatment of cerebrovascular diseases.CDSS can use computer technology to simulate and extend expert knowledge and empirical evidence in a timely and efficient manner. The combination of AI and CDSS is a potential solution to the shortage of medical resources and can improve the quality of and promote the standardization of medical services. At intervention sites, neurologists will receive support on use of the AI-based CDSS.
Aim: To evaluate the effectiveness of an AI-based CDSS for stroke management in patients with acute ischemic stroke within 7 days of symptom onset.
Intervention: An AI-based CDSS for an integrated management of patients with acute ischemic stroke. The strategy includes automatically identifying acute stroke lesions and lesion patterns, automated classification of stroke subtypes and mechanisms, evidence-based alerts, and guideline-recommended secondary stroke prevention strategies.
Eighty eligible hospitals in china, stratified by hospital capacity (secondary grade or tertiary) and economic-geographical regions (eastern, central, and western), will be randomized into either the CDSS group or the usual care group.
- Conditions
- Stroke
- Being tested
- AI-based CDSS
- Keywords
- acute ischemic stroke, artificial intelligence, clinical decision support system, cluster randomized controlled trial, evidence-based performance
- Medical subject headings
- Stroke, Ischemic Stroke
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-based CDSSDevice
- Automatically identifying acute ischemic stroke lesions on DWI.
- Classification of stroke subtypes and mechanisms.
- Evidence-based alerts and guidelines for early stroke management.
- Guideline-recommended secondary stroke prevention strategies.
| Study group | Role | What they receive |
|---|---|---|
| AI-based CDSS | Experimental | 1. Automatically identifying acute ischemic stroke lesions on DWI.
2. Classification of stroke subtypes and mechanisms.
3. Evidence-based alerts and guidelines for early stroke management.
4. Guideline-recommended secondary stroke prevention strategies. Receives: Device: AI-based CDSS |
| Usual Care | No intervention | Usual Care |
What is being measured
The primary outcome is the main question the study is designed to answer.
Incidence rate of new clinical vascular events (ischemic stroke, hemorrhagic stroke, myocardial infarction, or vascular death)
To evaluate the efficacy of AI-based CDSS in reducing the risk of new clinical vascular events (ischemic stroke, hemorrhagic stroke, myocardial infarction, or vascular death) at 3 months after initial symptom onset.
Measured: 3 months
Secondary outcomes (5)
Incidence rate of new clinical vascular events (ischemic stroke, hemorrhagic stroke, myocardial infarction, or vascular death)
Incidence rate of new clinical vascular events (ischemic stroke, hemorrhagic stroke, myocardial infarction, or vascular death) at discharge, 6,12-months after initial symptom onset.
Measured: 6, 12 months
Disability
Degree of disability (measured by the Modified Rankin Scale) at discharge, 3, 6, and 12 months
Measured: 3, 6, 12 months
All-or-none measure of evidence-based performance measures
Proportion of prescription of evidence-based performance measures. "All or none" measures including the evidence-based therapies: antithrombotic medication within 48 hours after symptom onset, dual antiplatelet therapy (aspirin and clopidogrel) started within 24 hours after symptom onset (NIHSS score ≤3), intensive statin therapy, antihypertensive, hypoglycemic medications, dysphagia screening, and deep vein thrombosis prophylaxis within 48 hours of admission. Discharge therapies include: antithrombotics, lipid lowering agents, anticoagulants for atrial fibrilation or flutter, antihypertensive, and hypoglycemic medications.
Measured: Participants will be followed for the duration of hospital stay, an expected average of 2 weeks
A composite measure score of performance measures
The composite measure score was defined as the total number of eligible performance measures performed divided by the total number of performance measures for which a given patient was eligible.
Measured: Participants will be followed for the duration of hospital stay, an expected average of 2 weeks
All-cause mortality
All-cause mortality
Measured: 3, 6, 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Aug 2020
- Study start1 Sep 2020 (estimated)
- Primary completion30 Sep 2022 (estimated)
- Study completion30 Jun 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for StrokeStudies of the same condition, open and under way.
- More trials run by Beijing Tiantan HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 21,689 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Beijing Tiantan Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yongjun Wang, Beijing Tiantan Hospital
- Investigators
- Yongjun Wang, MD, Principal investigator, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04524624
- Sponsor's protocol ID
- KY 2020-016-02
- Status last verified
- Aug 2020
- First submitted
- 7 Aug 2020
- Last updated
- 24 Aug 2020
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Wang Y, Li Z, Zhao X, Wang C, Wang X, Wang D, Liang L, Liu L, Wang C, Li H, Shen H, Bettger J, Pan Y, Jiang Y, Yang X, Zhang C, Han X, Meng X, Yang X, Kang H, Yuan W, Fonarow GC, Peterson ED, Schwamm LH, Xian Y, Wang Y; GOLDEN BRIDGE-AIS Investigators. Effect of a Multifaceted Quality Improvement Intervention on Hospital Personnel Adherence to Performance Measures in Patients With Acute Ischemic Stroke in China: A Randomized Clinical Trial. JAMA. 2018 Jul 17;320(3):245-254. doi: 10.1001/jama.2018.8802.
PubMed 29959443Zhang X, Ding L, Jing J, Wang C, Gu H, Jiang Y, Meng X, Liu T, Xie X, Xu M, Hu M, Zhang Y, Fu H, Liu P, Du C, Du K, Wang M, Li H, Gong X, Dong K, Xiong Y, Wang Y, Liu L, Zhang Z, Zang Y, Yang C, Xian Y, Peterson E, Fonarow GC, Schwamm LH, Zhao X, Wang Y, Li Z; GOLDEN BRIDGE II Investigators. Effect of a clinical decision support system on stroke care quality and outcomes in patients with acute ischaemic stroke (GOLDEN BRIDGE II): cluster randomised clinical trial. BMJ. 2026 Mar 20;392:e085810. doi: 10.1136/bmj-2025-085810.
PubMed 41862204Li Z, Zhang X, Ding L, Jing J, Gu HQ, Jiang Y, Meng X, Du C, Wang C, Wang M, Xu M, Zhang Y, Hu M, Li H, Gong X, Dong K, Zhao X, Wang Y, Liu L, Xian Y, Peterson E, Fonarow GC, Schwamm LH, Wang Y. Rationale and design of the GOLDEN BRIDGE II: a cluster-randomised multifaceted intervention trial of an artificial intelligence-based cerebrovascular disease clinical decision support system to improve stroke outcomes and care quality in China. Stroke Vasc Neurol. 2024 Dec 30;9(6):723-729. doi: 10.1136/svn-2023-002411.
PubMed 37699726
Study at a glance
From the registry record, last updated by the sponsor on 24 Aug 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Multi-centre, Cluster Randomized Controlled Trial of an Artificial Intelligence-Based Clinical Decision Support System for Integrated Management of Patients With Acute Ischemic Stroke: The GOLDEN BRIDGE II Trial
- ClinicalTrials.gov ID
- NCT04524624
- Acronym / sponsor ID
- KY 2020-016-02
- Conditions
- Stroke
- Keywords
- acute ischemic stroke, artificial intelligence, clinical decision support system, cluster randomized controlled trial, evidence-based performance
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 21,689 participants (estimated)
- Lead sponsor
- Beijing Tiantan HospitalUniversity, hospital or other
- Study start
- 1 Sep 2020 (estimated)
- Primary completion
- 30 Sep 2022 (estimated)
- Study completion
- 30 Jun 2023 (estimated)
- First posted
- 24 Aug 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study will conduct a cluster randomized controlled trial to evaluate the impact of an artificial intelligence-based clinical decision support system for the integrated management of patients with acute ischemic stroke on the adherence to guideline-based therapies and the incidence of new clinical vascular events.
Detailed description
Artificial intelligence (AI) and clinical decision support system (CDSS) have demonstrated great progress in the diagnosis and treatment of cerebrovascular diseases.CDSS can use computer technology to simulate and extend expert knowledge and empirical evidence in a timely and efficient manner. The combination of AI and CDSS is a potential solution to the shortage of medical resources and can improve the quality of and promote the standardization of medical services. At intervention sites, neurologists will receive support on use of the AI-based CDSS.
Aim: To evaluate the effectiveness of an AI-based CDSS for stroke management in patients with acute ischemic stroke within 7 days of symptom onset.
Intervention: An AI-based CDSS for an integrated management of patients with acute ischemic stroke. The strategy includes automatically identifying acute stroke lesions and lesion patterns, automated classification of stroke subtypes and mechanisms, evidence-based alerts, and guideline-recommended secondary stroke prevention strategies.
Eighty eligible hospitals in china, stratified by hospital capacity (secondary grade or tertiary) and economic-geographical regions (eastern, central, and western), will be randomized into either the CDSS group or the usual care group.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-based CDSS | Experimental | Device: AI-based CDSS1. Automatically identifying acute ischemic stroke lesions on DWI. 2. Classification of stroke subtypes and mechanisms. 3. Evidence-based alerts and guidelines for early stroke management. 4. Guideline-recommended secondary stroke prevention strategies. |
| Usual Care | No intervention | –Usual Care |
Who may qualify
- Ages
- 18 to 90 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (8 listed)
- Cluster Inclusion Criteria:
- Patient Inclusion Criteria:
Key exclusion criteria (13 listed)
- Cluster Exclusion Criteria:
- Patient Exclusion Criteria:
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-based CDSS1. Automatically identifying acute ischemic stroke lesions on DWI. 2. Classification of stroke subtypes and mechanisms. 3. Evidence-based alerts and guidelines for early stroke management. 4. Guideline-recommended secondary stroke prevention strategies. | Device | AI-based CDSS |
Primary outcome
Incidence rate of new clinical vascular events (ischemic stroke, hemorrhagic stroke, myocardial infarction, or vascular death)
Time frame: 3 months
To evaluate the efficacy of AI-based CDSS in reducing the risk of new clinical vascular events (ischemic stroke, hemorrhagic stroke, myocardial infarction, or vascular death) at 3 months after initial symptom onset.
5 secondary outcomes
Incidence rate of new clinical vascular events (ischemic stroke, hemorrhagic stroke, myocardial infarction, or vascular death)
Time frame: 6, 12 months
Disability
Time frame: 3, 6, 12 months
All-or-none measure of evidence-based performance measures
Time frame: Participants will be followed for the duration of hospital stay, an expected average of 2 weeks
A composite measure score of performance measures
Time frame: Participants will be followed for the duration of hospital stay, an expected average of 2 weeks
All-cause mortality
Time frame: 3, 6, 12 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Aug 2020.
- Background: PubMed 29959443Wang Y, Li Z, Zhao X, Wang C, Wang X, Wang D, Liang L, Liu L, Wang C, Li H, Shen H, Bettger J, Pan Y, Jiang Y, Yang X, Zhang C, Han X, Meng X, Yang X, Kang H, Yuan W, Fonarow GC, Peterson ED, Schwamm LH, Xian Y, Wang Y; GOLDEN BRIDGE-AIS Investigators. Effect of a Multifaceted Quality Improvement Intervention on Hospital Personnel Adherence to Performance Measures in Patients With Acute Ischemic Stroke in China: A Randomized Clinical Trial. JAMA. 2018 Jul 17;320(3):245-254. doi: 10.1001/jama.2018.8802.
- Derived from this study: PubMed 41862204Zhang X, Ding L, Jing J, Wang C, Gu H, Jiang Y, Meng X, Liu T, Xie X, Xu M, Hu M, Zhang Y, Fu H, Liu P, Du C, Du K, Wang M, Li H, Gong X, Dong K, Xiong Y, Wang Y, Liu L, Zhang Z, Zang Y, Yang C, Xian Y, Peterson E, Fonarow GC, Schwamm LH, Zhao X, Wang Y, Li Z; GOLDEN BRIDGE II Investigators. Effect of a clinical decision support system on stroke care quality and outcomes in patients with acute ischaemic stroke (GOLDEN BRIDGE II): cluster randomised clinical trial. BMJ. 2026 Mar 20;392:e085810. doi: 10.1136/bmj-2025-085810.
- Derived from this study: PubMed 37699726Li Z, Zhang X, Ding L, Jing J, Gu HQ, Jiang Y, Meng X, Du C, Wang C, Wang M, Xu M, Zhang Y, Hu M, Li H, Gong X, Dong K, Zhao X, Wang Y, Liu L, Xian Y, Peterson E, Fonarow GC, Schwamm LH, Wang Y. Rationale and design of the GOLDEN BRIDGE II: a cluster-randomised multifaceted intervention trial of an artificial intelligence-based cerebrovascular disease clinical decision support system to improve stroke outcomes and care quality in China. Stroke Vasc Neurol. 2024 Dec 30;9(6):723-729. doi: 10.1136/svn-2023-002411.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Yongjun Wang, MD principal investigator
Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-based CDSS in people with Stroke, run by Beijing Tiantan Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 8 inclusion and 13 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 24 Aug 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Zixiao Li, MD (00861013683234256, lizixiao2008@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Incidence rate of new clinical vascular events (ischemic stroke, hemorrhagic stroke, myocardial infarction, or vascular death) (time frame: 3 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04524624, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Aug 2020.