{
  "abstract": "Objectives Chronic kidney disease (CKD) and cardiovascular disease (CVD) are leading global causes of morbidity and mortality, often coexisting and sharing common risk factors. Despite their interconnection, clinical care and research for affected individuals remain siloed and fragmented. Recognising the need for integrated approaches, this study aimed to identify and prioritise key research questions at the intersection of CKD and CVD that can be addressed using real-world healthcare data to inform more cohesive and data-driven strategies for improving outcomes across both disease areas.Design, setting and participants A three-round modified Delphi process was conducted: Round 1 online survey collected open-ended research questions about CKD-CVD priorities via BHF Data Science Centre, Kidney Research UK, UK Renal Health Data Network and HDR UK public involvement channels; Round 2 in-person workshop refined and consolidated items; Round 3 online survey prioritised items across urgency, feasibility and impact using 5-point scales.Main outcome measures Survey mean scores for each research question were calculated across the three prioritisation domains, each scored out of 5. The top-ranked questions were identified based on overall scores.Results Six thematic domains emerged: risk prediction and early detection, treatment optimisation, health inequities, multimorbidity, disease mechanisms and data infrastructure. The highest-rated research priority was “What are the most effective strategies for prevention, early diagnosis and intervention in CKD?” with a mean score of 12.6 (SD 1.1). Other top priorities included evaluating the cost-effectiveness of early treatment, identifying predictors of kidney failure and assessing the benefits of treating cardiovascular and renal conditions independently.Conclusions Across domains, prevention/early detection and early treatment in CKD consistently ranked highest, indicating near-term opportunities for data-enabled cardio-renal research and service improvement; these priorities can inform funder calls, data linkage work and evaluation studies.",
  "authors": [
    {
      "affiliations": [
        "HDR UK, London, UK"
      ],
      "name": "Ross Alexander Forsyth"
    },
    {
      "affiliations": [
        "British Heart Foundation Data Science Centre, Health Data Research UK, London, UK"
      ],
      "name": "Amy Coombe"
    },
    {
      "affiliations": [
        "Nephrology, University Hospital of Leicester, Leicester, UK",
        "Department of Infection, Immunity and Inflammation, University of Leicester College of Medicine Biological Sciences and Psychology, Leicester, UK"
      ],
      "name": "Nigel Brunskill"
    },
    {
      "affiliations": [
        "Department of Infection, Immunity and Cardiovascular Disease, The Medical School, The University of Sheffield, Sheffield, UK"
      ],
      "name": "Timothy Chico"
    },
    {
      "affiliations": [
        "University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Neeraj Dhaun"
    },
    {
      "affiliations": [
        "Department of Nephrology, Bart’s Health, London, UK"
      ],
      "name": "Gavin Dreyer"
    },
    {
      "affiliations": [
        "School of Health and Related Research, University of Sheffield, Sheffield, UK"
      ],
      "name": "James Fotheringham"
    },
    {
      "affiliations": [
        "British Heart Foundation Data Science Centre, Health Data Research UK, London, UK"
      ],
      "name": "Amy Hodgkinson"
    },
    {
      "affiliations": [
        "British Heart Foundation Data Science Centre, Edinburgh, UK"
      ],
      "name": "Jacqueline Ann Langdon MacArthur"
    },
    {
      "affiliations": [
        "Kidney Research UK, Peterborough, UK"
      ],
      "name": "Aisling Mcmahon"
    },
    {
      "affiliations": [
        "British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Eve Miller-Hodges"
    },
    {
      "affiliations": [
        "British Heart Foundation Data Science Centre, Health Data Research UK, London, UK"
      ],
      "name": "Mike Molete"
    },
    {
      "affiliations": [
        "British Heart Foundation Data Science Centre, Health Data Research UK, London, UK",
        "Barts Heart Centre, St Bartholomew’s Hospital, London, UK",
        "NIHR Barts Biomedical Research Centre, William Harvey Research Institute, London, UK"
      ],
      "name": "Steffen E Petersen"
    },
    {
      "affiliations": [
        "Lay Advisory Group, Kidney Research UK, Peterborough, UK"
      ],
      "name": "Miranda Scanlon"
    },
    {
      "affiliations": [
        "British Heart Foundation Data Science Centre, Health Data Research UK, London, UK"
      ],
      "name": "Anna Stevenson"
    },
    {
      "affiliations": [
        "Centre for Nephrology, University College London, London, UK"
      ],
      "name": "David C Wheeler"
    },
    {
      "affiliations": [
        "British Heart Foundation Data Science Centre, Health Data Research UK, London, UK",
        "Division of Population Health and Genomics, University of Dundee, Dundee, UK"
      ],
      "name": "Samira Bell"
    }
  ],
  "title": "Delphi approach to prioritising research in cardiovascular and kidney disease using routinely collected data",
  "uid": "38ae3166-d953-5da6-83a4-06f10f4b220e"
}