Making sense of congenital cardiac disease with a research database: The Congenital Heart Surgeons' Society Data Center

Cardiol Young. 2008 Dec;18 Suppl 2:152-62. doi: 10.1017/S1047951108002849.


Background: Challenges inherent in researching rare congenital cardiac lesions led to creation of the Congenital Heart Surgeons' Society Data Center (Data Center) two decades ago. The Data Center pools experiences from up to 60 institutions, and over 4,700 children have been prospectively recruited within nine diagnostic inception cohorts. This report describes the operations of our research database, with particular focus on analytic strategies employed.

Methods and results: A procedural log is created of all investigations and interventions, and reports from enrolling institutions are subsequently obtained. Cross-sectional follow-up is undertaken annually by the Data Center. All data are linked to the individual child, and quality control mechanisms ensure that completeness and accuracy are maximised. Specific advantages of Data Center analytic approaches include multi-phase parametric hazard analysis, re-sampling techniques for reliable risk factor identification, competing risks methodology, and propensity-adjusted comparisons. Virtues of applying these techniques to a research database are illustrated by clinically pertinent questions that have been addressed in place of what would be difficult through randomised trials.

Conclusions: The Data Center is a cost-effective, versatile tool for researching congenital cardiac surgical outcomes. Research databases are ideally suited to in-depth investigations of survival and functional outcomes. Multi-center propensity-adjusted analyses represent efficient surrogates for randomised trials. Well-designed observational prospective studies should remain a principle mode of researching congenital cardiac disease.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Biomedical Research / statistics & numerical data*
  • Cardiac Surgical Procedures / statistics & numerical data*
  • Child
  • Databases, Factual*
  • Heart Defects, Congenital / surgery*
  • Humans
  • Reproducibility of Results
  • Societies, Medical*