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  dtd-version="1.2" article-type="abstract">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">IJPDS</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Population Data Science</journal-title>
        <abbrev-journal-title>IJPDS</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">2399-4908</issn>
      <publisher>
        <publisher-name>Swansea University</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.23889/ijpds.v10i3.3226</article-id>
      <article-id pub-id-type="publisher-id">10:3:202</article-id>
      <title-group>
        <article-title>Increased health utilisation before MS diagnosis: evidence from the SAIL
          Databank</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Witts</surname>
            <given-names initials="J">James</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Middleton</surname>
            <given-names initials="R">Rodden</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Nicholas</surname>
            <given-names initials="R">Richard</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>Swansea University, Swansea, United Kingdom</institution></aff>
      <aff id="affil-2"><label>2</label><institution>Imperial College London, London, United Kingdom</institution></aff>
      <pub-date>
        <day>01</day>
        <month>06</month>
        <year>2025</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2025</year>
      </pub-date>
      <volume>8</volume>
      <issue>4</issue>
      <elocation-id>3226</elocation-id>
      <permissions>
        <license license-type="open-access"
          xlink:href="https://creativecommons.org/licences/by/4.0/">
          <license-p>This work is licenced under a Creative Commons Attribution 4.0 International
            License.</license-p>
        </license>
      </permissions>
      <self-uri xlink:href="https://ijpds.org/article/view/3226">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3226</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>Using an algorithm to identify people with Multiple Sclerosis (pwMS) in routine healthcare
        data we determined if there was any evidence of an MS prodrome by looking at healthcare
        utilisation in Wales in those before the age of 16 (pre-16) and before the diagnosis of MS
        (pre-Dx) was made.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>Using the Secure Anonymised Information Linkage (SAIL) Databank of 4.6 Million people in
        Wales, we identified inpatient admissions (top 10), GP attendances (top 10) and
        prescriptions (top 20) in pwMS and separate propensity matched controls (by gender and year
        of birth) pre-16 and also pre-Dx. We identified entries unique to MS, excluding
        MS/demyelinating codes, and assessed whether entries common to both groups were
        significantly different.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>Pre-16 (N=313), admissions unique to MS included constipation (4.8%) and dental caries
        (3.5%); there was no significant difference in the 6/10 ICD-10 codes shared between
        pwMS/control cohorts. Pre-Dx (N=5,309), sensory symptoms (4.3%), paraesthesia (3.8%),
        headaches (3.7%) and urinary tract infections (3.6%) were unique to pwMS with the remainder
        4/10 not being different between pwMS/control cohorts.</p>
      <p>For GP attendances (pwMS N=4798 pre-16, N=9648 pre-Dx) there were higher rates of
        attendances but no unique causes for attendance. In pwMS versus controls pre-16 they had
        more respiratory infections (pwMS 14.2%, p&lt;0.001), consistent with this pre-16 they had
        higher rates of penicillin use. Pre-Dx they had more vaccinations and used more antibiotics,
        paracetamol, anti-inflammatories, hydrocortisone and PPI inhibitors.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>pwMS have higher healthcare utilisation pre-16 and pre-Dx. This requires further study but
        does imply a MS prodrome.</p>
    </sec>
  </body>
</article>