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The Copenhagen Primary Care Differential Count (CopDiff) database.

Christen Lykkegaard Andersen1, Volkert Dirk Siersma2, Willy Karlslund2

  • 1The Research Unit for General Practice and Section of General Practice, Department of Public Health, University of Copenhagen, Copenhagen, Denmark ; Department of Hematology, Roskilde University Hospital, Copenhagen, Denmark.

Clinical Epidemiology
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PubMed
Summary
This summary is machine-generated.

This study describes the Copenhagen Primary Care Differential Count database, a valuable resource linking blood cell counts to health outcomes. The database aids research into disease associations and patient comorbidities.

Keywords:
differential leukocyte countnationwide health registersresearch

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Area of Science:

  • Clinical Medicine
  • Biostatistics
  • Public Health

Background:

  • Differential blood cell counts offer critical health insights.
  • Integrating blood tests with biochemical data reveals physiological and pathophysiological relationships.
  • Research databases are needed to link these parameters with comorbidities and future disease risks.

Purpose of the Study:

  • To review the methodological construction of the Copenhagen Primary Care Differential Count database.
  • To describe the characteristics of the population and variables within the database.
  • To provide examples of database utilization to encourage collaborative research.

Main Methods:

  • The Copenhagen Primary Care Differential Count database was established using results from the Copenhagen General Practitioners' Laboratory.
  • It includes over 1.3 million differential blood cell counts from July 2000 to January 2010.
  • The database is linked with Danish national health registries for comprehensive data.

Main Results:

  • The database covers approximately 1.2 million inhabitants.
  • It contains extensive differential blood cell count data and other blood analyses.
  • Data linkage includes cancer, patient, civil registration, and cause of death registries.

Conclusions:

  • The paper details the database's creation and data characteristics.
  • It highlights the potential for exploring associations between blood counts, comorbidities, and health outcomes.
  • Examples are provided to inspire collaborative research using this resource.