Orthop J Sports Med
November 2024
Background: As machine learning becomes increasingly utilized in orthopaedic clinical research, the application of machine learning methodology to cohort data from the Multicenter ACL Revision Study (MARS) presents a valuable opportunity to translate data into patient-specific insights.
Purpose: To apply novel machine learning methodology to MARS cohort data to determine a predictive model of revision anterior cruciate ligament reconstruction (rACLR) graft failure and features most predictive of failure.
Study Design: Cohort study; Level of evidence, 3.
Am J Sports Med
November 2024
Background: Revision anterior cruciate ligament (ACL) reconstruction has been documented to have inferior outcomes compared with primary ACL reconstruction. The reasons why remain unknown.
Purpose: To determine whether surgical factors performed at the time of revision ACL reconstruction can influence a patient's outcome at 6-year follow-up.
This work is focused on designing an easy-to-use novel perfusion system for articular cartilage (AC) tissue engineering and using it to elucidate the mechanism by which interstitial shear upregulates matrix synthesis by articular chondrocytes (AChs). Porous chitosan-agarose (CHAG) scaffolds were synthesized and compared to bulk agarose (AG) scaffolds. Both scaffolds were seeded with osteoarthritic human AChs and cultured in a novel perfusion system with a medium flow velocity of 0.
View Article and Find Full Text PDFBackground: Meniscal and chondral damage is common in the patient undergoing revision anterior cruciate ligament (ACL) reconstruction.
Purpose: To determine if meniscal and/or articular cartilage pathology at the time of revision ACL surgery significantly influences a patient's outcome at 6-year follow-up.
Study Design: Cohort study; Level of evidence, 3.