OPTIMAL - OsteoPorosis Treatment Identification using Machine Learning

  • Research type

    Research Study

  • Full title

    OPTIMAL - OsteoPorosis Treatment Identification using Machine Learning

  • IRAS ID

    313853

  • Contact name

    Christopher Sainsbury

  • Contact email

    christopher.sainsbury@ggc.scot.nhs.uk

  • Sponsor organisation

    NHS GG&C R&I

  • Clinicaltrials.gov Identifier

    NCT05678569

  • Duration of Study in the UK

    0 years, 6 months, 1 days

  • Research summary

    OPTIMAL is a pilot feasibility study for a machine learning derived enhanced screening software for osteoporosis. This tool has been created using machine learning, based on data from NHS Greater Glasgow and Clyde. The study will contact individuals deemed at high risk by the study (750 patients will be re-identified, and these will be contacted starting from the highest risk until 250 patients are recruited) and perform DXA scans, clinical review, and bloods tests that are relevant to osteoporosis. This data will then be compared to the predictions made by the OPTIMAL enhanced screening tool, in order to validate its efficacy.

  • REC name

    Wales REC 7

  • REC reference

    22/WA/0269

  • Date of REC Opinion

    8 Nov 2022

  • REC opinion

    Further Information Favourable Opinion