Acta Orthopaedica (Apr 2024)

Enhancing the data capture of periprosthetic joint infections in the Danish Knee Arthroplasty Registry: validity assessment and incidence estimation

  • Marie Anneberg,
  • Eskild Bendix Kristiansen,
  • Anders Troelsen,
  • Per Gundtoft,
  • Henrik Toft Sørensen,
  • Alma B Pedersen

DOI
https://doi.org/10.2340/17453674.2024.40358
Journal volume & issue
Vol. 95

Abstract

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Background and purpose: Revisions due to periprosthetic joint infection (PJI) are underestimated in national arthroplasty registries. Our primary objective was to assess the validity in the Danish Knee Arthroplasty Register (DKR) of revisions performed due to PJI against the Healthcare-Associated Infections Database (HAIBA). The secondary aim was to describe the cumulative incidences of revision due to PJI within 1 year of primary total knee arthroplasty (TKA) according to the DKR, HAIBA, and DKR/HAIBA combined. Methods: This longitudinal observational cohort study included 56,305 primary TKAs (2010–2018), reported in both the DKR and HAIBA. In the DKR, revision performed due to PJI was based on pre- and intraoperative assessment disclosed by the surgeon immediately after surgery. In HAIBA, PJI was identified from knee-related revision procedures coinciding with 2 biopsies with identical microbiological pathogens. We calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of revision due to PJI in the DKR (vs. HAIBA, within 1 year of TKA) with 95% confidence intervals (CI). Cumulative incidences were calculated using the Kaplan–Meier method. Results: The DKR‘s sensitivity for PJI revision was 58% (CI 53–62) and varied by TKA year (41%–68%) and prosthetic type (31% for monoblock; 63% for modular). The specificity was 99.8% (CI 99.7–99.8), PPV 64% (CI 62–72), and NPV 99.6% (CI 99.6–99.7). 80% of PJI cases not captured by the DKR were caused by non-reporting rather than misclassification. 33% of PJI cases in the DKR or HAIBA were culture-negative. Considering potential misclassifications, the best-case sensitivity was 64%. The cumulative incidences of PJI were 0.8% in the DKR, 0.9% in HAIBA, and 1.1% when combining data. Conclusion: The sensitivity of revision due to PJI in the DKR was 58%. The cumulative incidence of PJI within 1 year after TKA was highest (1.1%) when combining the DKR and HAIBA, showing that incorporating microbiology data into arthroplasty registries can enhance PJI validity.