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The Transition to an Anterior-Based Muscle Sparing Approach Improves Early Postoperative Function but is Associated with a Learning Curve
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Factors Associated With Outcome Response Frequency in a Knee Replacement Registry.

Amr Kaadan1, Janine Molino, Roy Aaron

  • 1From the Department of Orthopaedic Surgery, Warren Alpert Medical School of Brown University, Providence, RI (Kaadan, Molino, and Aaron), and the BERDI: Biostatistics, Epidemiology, Research Design, and Informatics, Brown University Health, Providence, RI (Molino).

The Journal of the American Academy of Orthopaedic Surgeons
|April 3, 2026
PubMed
Summary

Persistent follow-up is crucial for arthroplasty registries. Identifying patient characteristics associated with nonresponse helps reduce bias and improve data quality for total knee arthroplasty outcomes.

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Area of Science:

  • Orthopedic surgery
  • Biostatistics
  • Health services research

Background:

  • Nonresponse in arthroplasty registries can bias outcome data, affecting validity and generalizability.
  • Patient-reported outcome measures (PROMs) are vital for total knee arthroplasty (TKA) outcomes but can be skewed by nonresponse.
  • This study examines factors linked to 12-month nonresponse after TKA and the impact of multimodal follow-up.

Purpose of the Study:

  • Investigate sociodemographic and clinical factors associated with 12-month nonresponse in TKA patients.
  • Evaluate the effectiveness of comprehensive multimodal follow-up methods on response rates.
  • Identify strategies to mitigate selection bias and enhance the utility of arthroplasty registries.

Main Methods:

  • Prospective cohort analysis of 2,508 TKA patients in the Function and Outcomes Research for Comparative Effectiveness registry (2018-2023).
  • Collection of preoperative sociodemographic and clinical data.
  • Application of hierarchical cluster analysis and logistic regression to identify nonresponse characteristics and validate findings.

Main Results:

  • A 29% nonresponse rate (735/2,508) was observed at 12 months.
  • Nonresponders (cluster 5) were more likely to be female, non-White, Hispanic/Latino, less educated, publicly insured, with greater comorbidity and lower PROMs.
  • The highest response rate (76.9%, cluster 1) was among well-educated males with private insurance and lower BMI.

Conclusions:

  • Multimodal follow-up (email, mail, phone) is essential to exceed 60% response rates, surpassing international standards.
  • Understanding patient characteristics linked to nonresponse enables targeted strategies to reduce bias.
  • Improved response rates enhance data collection, reduce selection bias, and increase the long-term value of arthroplasty registries.