Donor-recipient age- or sex-mismatched osteochondral allografts do not adversely affect cumulative graft survival rates after transplantation in the knee

Background: Osteochondral allograft transplantation (OCAT) can be performed without the need for blood-type matching or anti-rejection medications. However, other donor- recipient mismatch variables could influence outcomes. Therefore, it is critical to examine the impacts of sex and age mismatching on functional OCA survival. Methods: Prospectively collected data for patients undergoing primary knee OCAT enrolled in a lifelong outcomes registry were analyzed for functional OCA survival based on sex- and age-matched and-mismatched cohorts. Treatment failure was defined as the need for OCAT revision surgery or knee arthroplasty. Results: 162 donor-recipient pairs were analyzed; 57 (35.2%) were sex-mismatched and 89 (54.9%) were age-mismatched. Sex-mismatched OCATs were not associated with a significantly different cumulative graft survival rate when compared to sex-matched OCATs (78.9% vs 75.2% p = 0.324). Age-mismatched OCATs were not associated with a significantly different cumulative graft survival rate when compared to age-matched OCATs (71.6% vs 81.5% p = 0.398). When adjusting for sex, BMI, concomitant procedures, and surgery type, age-mismatched and sex-mismatched OCATs were not significantly associated with higher likelihood for treatment failure. Conclusion: By analyzing functional graft survival rates for donor-recipient sex- or age- mismatched OCAs following primary OCAT, the results of the present study support current donor-recipient matching protocols for OCA transplantation in the knee. Based on current evidence, donor-recipient blood-type, sex-, and age-matching are not required for safe and effective primary OCAT in the knee. However, further studies are imperative for defining modifiable variables that further optimize safety and outcomes while maximizing donor tissue quality, availability, access, and use. (c) 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.