{
  "abstract": "Background The relevance of covert cerebrovascular disease (CCD) in practice is uncertain, partly because estimation of risk in whole clinical populations is difficult. Studies have had success extracting CCD from clinical text using natural language processing (NLP), though they have been limited to specific CCD phenotypes. Here, we used NLP to measure multiple clinically-reported CCD phenotypes in a large clinical cohort and estimated subsequent disease risk in health record data.Methods From all people with brain imaging in Scotland (2010–2018), we selected people with no prior hospitalisation for neurological disease (n=367 988). NLP of imaging reports identified: white matter hypoattenuation or hyperintensities (WMH), lacunes, cortical infarcts and cerebral atrophy. Adjusted HRs (aHRs) were estimated between each phenotype and stroke, dementia and Parkinson’s disease (conditions previously associated with CCD), epilepsy and colorectal cancer (control conditions).Results For each phenotype, the aHR of stroke was WMH 1.4 (95% CI 1.3–1.4), lacunes 1.6 (1.5–1.6), cortical infarct 1.8 (1.7–1.9) and cerebral atrophy 1.1 (1.0–1.1). The aHR of dementia was WMH 1.3 (1.3–1.3), lacunes 1.0 (0.9–1.0), cortical infarct 1.1 (1.1–1.2) and cerebral atrophy 1.7 (1.7–1.8). The aHR of Parkinson’s disease was WMH 1.1 (1.0–1.2), lacunes 1.1 (0.9–1.2), cortical infarct 0.7 (0.6–0.9) and cerebral atrophy 1.4 (1.3–1.5). The aHRs between CCD phenotypes and epilepsy and colorectal cancer were around the null.Conclusion CCD and atrophy have implications for future disease risk and can be identified at scale using NLP of clinical reports. Prevention of neurological disease in people with CCD should be a priority for healthcare policy makers.",
  "authors": [
    {
      "affiliations": [
        "Institute for Neuroscience and Cardiovascular Research, The University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Matthew Henry Iveson"
    },
    {
      "affiliations": [
        "Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK",
        "Kellogg College, University of Oxford, Oxford, UK"
      ],
      "name": "Mome Mukherjee"
    },
    {
      "affiliations": [
        "Institute for Neuroscience and Cardiovascular Research, The University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Emma M Davidson"
    },
    {
      "affiliations": [
        "Centre for Clinical Informatics, The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK"
      ],
      "name": "Huayu Zhang"
    },
    {
      "affiliations": [
        "Institute for Neuroscience and Cardiovascular Research, The University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Laura Sherlock"
    },
    {
      "affiliations": [
        "Institute for Neuroscience and Cardiovascular Research, The University of Edinburgh, Edinburgh, UK",
        "Centre for Medical Informatics, The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK"
      ],
      "name": "Emily L Ball"
    },
    {
      "affiliations": [
        "Institute for Neuroscience and Cardiovascular Research, The University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Grant Mair"
    },
    {
      "affiliations": [
        "Institute for Neuroscience and Cardiovascular Research, The University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Alice Hosking"
    },
    {
      "affiliations": [
        "Institute for Neuroscience and Cardiovascular Research, The University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Heather Whalley"
    },
    {
      "affiliations": [
        "Institute for Neuroscience and Cardiovascular Research, The University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Michael T C Poon"
    },
    {
      "affiliations": [
        "Institute for Neuroscience and Cardiovascular Research, The University of Edinburgh, Edinburgh, UK",
        "UK Dementia Research Institute, Edinburgh, UK"
      ],
      "name": "Joanna M Wardlaw"
    },
    {
      "affiliations": [
        "Graduate School of Biomedical Sciences, Tufts University, Medford, Massachusetts, USA"
      ],
      "name": "David M Kent"
    },
    {
      "affiliations": [
        "School of Informatics, The University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Richard Tobin"
    },
    {
      "affiliations": [
        "School of Informatics, The University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Claire Grover"
    },
    {
      "affiliations": [
        "School of Literatures, Languages and Cultures, The University of Edinburgh, Edinburgh, UK",
        "Advanced Care Research Centre, The University of Edinburgh, Edinburgh, UK"
      ],
      "name": "Beatrice Alex"
    },
    {
      "affiliations": [
        "Institute for Neuroscience and Cardiovascular Research, The University of Edinburgh, Edinburgh, UK",
        "British Heart Foundation Data Science Centre, HDR UK, London, UK"
      ],
      "name": "William Whiteley"
    }
  ],
  "title": "Clinically reported covert cerebrovascular disease and risk of neurological disease: a whole-population cohort of 367 988 people using natural language processing",
  "uid": "e0675e61-f425-5475-b08d-c1a1f968646f"
}