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Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines

Author

Listed:
  • Alexander P. L. Martindale

    (Brighton and Sussex Medical School)

  • Benjamin Ng

    (Sandwell and West Birmingham NHS Trust
    University of Oxford)

  • Victoria Ngai

    (University College London Medical School)

  • Aditya U. Kale

    (University of Birmingham
    University Hospitals Birmingham NHS Foundation Trust
    University of Birmingham)

  • Lavinia Ferrante di Ruffano

    (University of York)

  • Robert M. Golub

    (Northwestern University Feinberg School of Medicine)

  • Gary S. Collins

    (University of Oxford)

  • David Moher

    (Ottawa Hospital Research Institute)

  • Melissa D. McCradden

    (The Hospital for Sick Children
    Peter Gilgan Centre for Research & Learning
    Dalla Lana School of Public Health)

  • Lauren Oakden-Rayner

    (University of Adelaide)

  • Samantha Cruz Rivera

    (University of Birmingham
    University of Birmingham)

  • Melanie Calvert

    (University of Birmingham
    University of Birmingham
    University of Birmingham
    University of Birmingham)

  • Christopher J. Kelly

    (Google Health)

  • Cecilia S. Lee

    (University of Washington)

  • Christopher Yau

    (University of Oxford
    Health Data Research UK)

  • An-Wen Chan

    (Women’s College Hospital. University of Toronto)

  • Pearse A. Keane

    (Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology)

  • Andrew L. Beam

    (Harvard. T.H. Chan School of Public Health
    Harvard Medical School)

  • Alastair K. Denniston

    (University of Birmingham
    University Hospitals Birmingham NHS Foundation Trust
    University of Birmingham
    University of Birmingham)

  • Xiaoxuan Liu

    (University of Birmingham
    University Hospitals Birmingham NHS Foundation Trust
    University of Birmingham)

Abstract

The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been published but their completeness and transparency of reporting is unknown. This systematic review assesses the completeness of reporting of AI RCTs following publication of CONSORT-AI and provides a comprehensive summary of RCTs published in recent years. 65 RCTs were identified, mostly conducted in China (37%) and USA (18%). Median concordance with CONSORT-AI reporting was 90% (IQR 77–94%), although only 10 RCTs explicitly reported its use. Several items were consistently under-reported, including algorithm version, accessibility of the AI intervention or code, and references to a study protocol. Only 3 of 52 included journals explicitly endorsed or mandated CONSORT-AI. Despite a generally high concordance amongst recent AI RCTs, some AI-specific considerations remain systematically poorly reported. Further encouragement of CONSORT-AI adoption by journals and funders may enable more complete adoption of the full CONSORT-AI guidelines.

Suggested Citation

  • Alexander P. L. Martindale & Benjamin Ng & Victoria Ngai & Aditya U. Kale & Lavinia Ferrante di Ruffano & Robert M. Golub & Gary S. Collins & David Moher & Melissa D. McCradden & Lauren Oakden-Rayner , 2024. "Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45355-3
    DOI: 10.1038/s41467-024-45355-3
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    References listed on IDEAS

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