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Related Experiment Video

Updated: Apr 11, 2026

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Contemporary cardiac surgery outcomes databases: Data sources, variables, and applications.

Irbaz Hameed1,2, Sriharsha Talapaneni1, Asad Saulat Fatimi1

  • 1Division of Cardiac Surgery, Department of Surgery, Yale School of Medicine, New Haven, Conn.

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|April 10, 2026
PubMed
Summary

This study identifies key databases for cardiac surgery research, highlighting their varied characteristics. Understanding these large-scale multicenter databases is crucial for generating reliable clinical evidence.

Keywords:
administrative datacardiac surgeryclinical registrieshealth data systemslongitudinal datamortality follow-upoutcomes research

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Area of Science:

  • Cardiovascular Surgery
  • Health Informatics
  • Clinical Research Methodology

Background:

  • Large-scale multicenter databases are essential for robust observational research in cardiac surgery.
  • These databases facilitate analysis of clinical outcomes, practice patterns, and population trends.

Purpose of the Study:

  • To characterize the databases most frequently utilized in contemporary cardiac surgery outcomes research.
  • To evaluate the specific characteristics of the top 16 most frequently used databases.

Main Methods:

  • A systematic review of retrospective observational studies published between January 2019 and August 2025 in 7 high-impact journals.
  • Identification of 905 eligible articles and 217 distinct databases, with further evaluation of the top 16.

Main Results:

  • The 16 most frequently used databases included clinical registries (e.g., STS, EUPCR), administrative claims (e.g., Medicare, NHIRD), and linkage-based sources (e.g., NDI).
  • Databases exhibited significant variation in procedural detail, national coverage, patient follow-up, population scoring, and data completeness.

Conclusions:

  • This study provides a comprehensive characterization of common large databases in cardiac surgery outcomes research.
  • Understanding database alignment with research questions is vital for generating meaningful and generalizable clinical evidence to inform practice.