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
© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ..
BACKGROUND: 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.
AIMS: 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.
DESIGN: 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.
CONCLUSIONS: Once the effectiveness is verified, the cerebrovascular disease AI-CDSS could improve stroke care and outcomes in China.
TRIAL REGISTRATION NUMBER: NCT04524624.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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| Enthalten in: |
Stroke and vascular neurology - (2024) vom: 02. Feb. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Li, Zixiao [VerfasserIn] |
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Date Revised 02.02.2024 published: Print-Electronic ClinicalTrials.gov: NCT04524624 Citation Status Publisher |
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| doi: |
10.1136/svn-2023-002411 |
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| 245 | 1 | 0 | |a Rationale and design of the GOLDEN BRIDGE II |b 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 |
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| 520 | |a © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. | ||
| 520 | |a BACKGROUND: 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 | ||
| 520 | |a AIMS: 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 | ||
| 520 | |a DESIGN: 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 | ||
| 520 | |a CONCLUSIONS: Once the effectiveness is verified, the cerebrovascular disease AI-CDSS could improve stroke care and outcomes in China | ||
| 520 | |a TRIAL REGISTRATION NUMBER: NCT04524624 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Stroke | |
| 700 | 1 | |a Zhang, Xinmiao |e verfasserin |4 aut | |
| 700 | 1 | |a Ding, Lingling |e verfasserin |4 aut | |
| 700 | 1 | |a Jing, Jing |e verfasserin |4 aut | |
| 700 | 1 | |a Gu, Hong-Qiu |e verfasserin |4 aut | |
| 700 | 1 | |a Jiang, Yong |e verfasserin |4 aut | |
| 700 | 1 | |a Meng, Xia |e verfasserin |4 aut | |
| 700 | 1 | |a Du, Chunying |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Chunjuan |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Meng |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Man |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Yanxu |e verfasserin |4 aut | |
| 700 | 1 | |a Hu, Meera |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Hao |e verfasserin |4 aut | |
| 700 | 1 | |a Gong, Xiping |e verfasserin |4 aut | |
| 700 | 1 | |a Dong, Kehui |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Xingquan |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yilong |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Liping |e verfasserin |4 aut | |
| 700 | 1 | |a Xian, Ying |e verfasserin |4 aut | |
| 700 | 1 | |a Peterson, Eric |e verfasserin |4 aut | |
| 700 | 1 | |a Fonarow, Gregg C |e verfasserin |4 aut | |
| 700 | 1 | |a Schwamm, Lee H |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yongjun |e verfasserin |4 aut | |
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