Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Additional supplemental material is published online only. To view, please visit the journal online (
None declared.
ZL, XZ, LD and JJ contributed equally.
DrYongjunWang;
DrZixiaoLi;
Given the swift advancements in artificial intelligence (AI), the utilisation of AI-based clinical decision support systems (AI-CDSSs) has become increasingly prevalent in the medical domain, particularly in the management of cerebrovascular disease.
To describe the design, rationale and methods of a cluster-randomised multifaceted intervention trial aimed at investigating the effect of cerebrovascular disease AI-CDSS on the clinical outcomes of patients who had a stroke and on stroke care quality.
The GOLDEN BRIDGE II trial is a multicentre, open-label, cluster-randomised multifaceted intervention study. A total of 80 hospitals in China were randomly assigned to the AI-CDSS intervention group or the control group. For eligible participants with acute ischaemic stroke in the AI-CDSS intervention group, cerebrovascular disease AI-CDSS will provide AI-assisted imaging analysis, auxiliary stroke aetiology and pathogenesis analysis, and guideline-based treatment recommendations. In the control group, patients will receive the usual care. The primary outcome is the occurrence of new vascular events (composite of ischaemic stroke, haemorrhagic stroke, myocardial infarction or vascular death) at 3 months after stroke onset. The sample size was estimated to be 21 689 with a 26% relative reduction in the incidence of new composite vascular events at 3 months by using multiple quality-improving interventions provided by AI-CDSS. All analyses will be performed according to the intention-to-treat principle and accounted for clustering using generalised estimating equations.
Once the effectiveness is verified, the cerebrovascular disease AI-CDSS could improve stroke care and outcomes in China.
Received 2023 Feb 20; Accepted 2023 Aug 11; Collection date 2024 Dec.
We designed the GOLDEN BRIDGE II trial to investigate the effects of the cerebrovascular disease AI-CDSS on stroke outcomes and the quality of stroke care.
The GOLDEN BRIDGE II trial will produce objective data on whether cerebrovascular disease AI-CDSS improves the quality of stroke care and outcomes among patients who had an ischaemic stroke.
In China, the incidence of stroke has increased over the past three decades, becoming the primary cause of death.
Artificial intelligence (AI) technology has been widely used in the medical field. The AI-based clinical decision support system (AI-CDSS) is a novel practice and application of AI technology in cerebrovascular diseases.
In our study, we developed the cerebrovascular disease AI-CDSS to provide clinical guideline-based interventions, including AI-assisted imaging analysis, auxiliary analysis of aetiology and pathogenesis, and guideline-based treatment recommendations for patients who had an acute ischaemic stroke (AIS). We designed a clustered-randomised controlled study to investigate the effects of the AI-CDSS (the cerebrovascular disease AI-CDSS) on the patient’s early recurrence of composite vascular events and on stroke care quality.
The GOLDEN BRIDGE II trial is a multicentre, open-labelled, cluster-randomised multifaceted intervention study designed to evaluate the effects of cerebrovascular disease AI-CDSS on new composite vascular events (including ischaemic stroke, haemorrhagic stroke, myocardial infarction or vascular death) at 3 months in patients who had an AIS. The cerebrovascular disease AI-CDSS will provide AI-assisted imaging analysis, auxiliary stroke aetiology and pathogenesis analysis, and guideline-based treatment recommendations for patients in the intervention group. On the other hand, patients in the control group will receive usual care. All patients will be enrolled sequentially and receive follow-ups at 3, 6 and 12 months after stroke onset. The flow chart of the study is shown in
To ensure diversity, the geographical location and grade of hospitals were considered. The included hospitals cover the eastern, central and western regions of China, with proportional recruitment of secondary and tertiary hospitals. A total of 80 hospitals located across 23 provinces, autonomous regions or municipalities in mainland China were included. The criteria for hospital inclusion and exclusion are shown in
| Inclusion criteria | Exclusion criteria |
| 1. Tertiary-grade or secondary-grade hospitals | 1. Primary-grade (ie, community) hospitals |
| 2. Consisting of emergency department and neurological wards for patients who had a stroke | 2. <20 patients who had an acute ischaemic stroke admitted per month |
| 3. Consisting of 1.5T or 3T MRI machine with the functionalities for completing DWI and MRA scan | 3. Specialised hospitals (cancer hospitals, maternity hospitals, children’s hospitals, etc) |
DWIdiffusion weighted imaging
This trial is specifically designed for patients over the age of 18 with AIS confirmed by imaging of the brain within 7 days of symptom onset, and excludes those with the diagnosis of transient ischaemic attack (TIA), haemorrhagic stroke or non-cerebrovascular diseases. The inclusion and exclusion criteria for the participants are shown in
| Inclusion criteria | Exclusion criteria |
| 1. Older than 18 years | 1. Negative ischaemic stroke on DWI or transient ischaemic attack |
| 2. Ischaemic stroke within 7 days of symptom onset | 2. Diagnosis of other cerebrovascular diseases (cerebral haemorrhage, subarachnoid haemorrhage, cerebral venous sinus thrombosis, etc) |
| 3. Ischaemic stroke confirmed by imaging of the brain | 3. Diagnosis of other diseases (epilepsy, central nervous system infection, metabolic encephalopathy, etc) |
| 4. Hospitalisation from emergency or outpatient department | 4. Pregnancy or delivery within the 6 weeks before the study |
| 5. Participants or their legal guardians give their permission to conduct the study by signing an informed consent | 5. Participation in other pharmaceutical or device-based interventional studies |
| 6. With terminal diseases (life expectancy<3 months) or cannot commit to completing the study due to other reasons |
DWIdiffusion weighted imaging
The clustered randomisation will be completed before each hospital is enrolled in the study, and the eligible participants with AIS in the intervention group will receive the AI-based analysis and the recommended treatment provided by the cerebrovascular disease AI-CDSS. The specific AI-CDSS intervention protocol includes AI-assisted imaging analysis, auxiliary analysis of ischaemic stroke aetiology and pathogenesis, and guideline-based treatment recommendations for acute and secondary prevention.
The AI-CDSS obtains patients’ clinical data and imaging data from the hospital information system and uses the method of stroke image automatic interpretation technology based on deep learning combined with a stroke clinical knowledge base to provide assistant clinical decisions including imaging diagnosis, aetiological classification and treatment decision of ischaemic stroke (
The neurologists in the intervention hospitals will complete training on cerebrovascular disease AI-CDSS before the start of this study. A 2-week transition phase of AI-CDSS intensive intervention will be completed before the patients are enrolled. All participants in the hospital of the control group received normal routine diagnosis and treatment (
The computer-generated random number sequence will be used for cluster randomisation at the hospital level, and two independent biostatisticians (YJ and H-QG) will be aware of it. Participating hospitals are randomly grouped on a 1:1 basis. To prevent imbalance, hospital location and grade are matched during randomisation. A confirmation letter will be provided to each hospital 1 month before the intervention’s implementation to assure readiness. If the chosen hospital could not complete the study, it was replaced with another one of equivalent capacity and economic–geographic region strata.
The primary outcome is a new composite vascular event (including ischaemic stroke, haemorrhagic stroke, myocardial infarction or vascular death) at 3 months after stroke onset.
The secondary outcomes include: (1) the composite measure score of medical service indicators for AIS care quality, (2) a new composite vascular event at 6 and 12 months after stroke onset, (3) disability based on the modified Rankin Scale (mRS=3–6) at 3, 6 and 12 months after stroke onset and (4) average hospitalisation days, average total hospitalisation cost, average hospitalisation drug cost and average hospitalisation examination cost.
The primary safety outcome refers to the occurrence of moderate or severe bleeding events as defined by the Global Utilisation of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries (GUSTO) within 3 months after stroke onset. The secondary safety outcomes include severe or moderate bleeding (as defined by GUSTO) within 6 and 12 months. In addition, all bleeding events (including severe or moderate bleeding) within 3, 6 and 12 months are included.
The International Academic Steering Committee is comprised of the cochief investigators and members. It provides the scientific basis and strategic guidance for the trial, overseeing research design, execution and publication-related activities. Additionally, the Academic Steering Committee chairs meetings of the Senior Management Group. The Executive Committee, comprised of experienced experts guided by the International Academic Steering Committee, aims to monitor the trial’s progress, ensure participants’ safety and provide scientifically grounded decisions on whether to terminate, modify or continue the trial. The Data Safety Monitoring Board regularly monitors the progress of the study to ensure adherence to the highest ethical and patient safety standards. Furthermore, it provides written recommendations to the Chair of the Trial Steering Committee following each meeting. The Quality Improvement Committee, consisting of clinical specialists and experts in stroke quality improvement, is responsible for supervising adherence to stroke care quality standards.
The executive committee has approved the case report form.
The main null hypothesis of this study was that, compared with those who receive traditional routine diagnosis and treatment, there would be no difference in the incidence of new vascular events observed at 3 months among patients who had a stroke treated with interventions recommended by the cerebrovascular disease AI-CDSS.
According to the findings of the third China National stroke Registry study, patients who had an AIS or TIA had a 3-month new composite vascular event rate of 6.4%.
In this study, efficacy analysis will be performed using intention-to-treat analysis.
The AI-CDSS has experienced several stages of development and has the ultimate goal of assisting with actual clinical care scenarios.
Nagenthiraja
A portable decision system for stroke classification, named iTOAST, was created by Nam
The Self-management TO Prevent (STOP) Stroke Tool is an AI-CDSS tool developed by using an integrated model. The goal of this system is to provide health management for veterans, promote evidence-based management by automatically providing clinicians with guidelines for the secondary prevention of stroke based on electronic medical records, develop a web-based system for stroke self-management and facilitate patient-centred decision-making.
The application of AI-CDSS in clinical practice still faces multiple challenges, such as (1) how to develop an advanced strategy for the integration of electronic medical records to achieve automatic acquisition and sharing of clinical information; (2) how to construct a standardised clinical knowledge base to provide evidence-based guidelines; and (3) how to combine the output information of AI-CDSS with clinical practice in diagnosis and treatment to establish an effective human–computer interaction.
Although many challenges remain, AI-CDSS has initiated a predictable trend in the development of stroke management in clinical practice. Prior studies of performance improvement systems/quality feedback such as Get With The Guidelines-Stroke (GWTG-Stroke) and the GOLDEN BRIDGE-AIS have demonstrated improved ischaemic stroke care and outcomes. The incidence of new vascular events over a 3-month period was reduced by 26% thanks to a multifaceted quality improvement intervention.
We thank all investigators and participating hospitals of the GOLDEN BRIDGE II trial.
Data are available upon reasonable request.
Data are available upon reasonable request.