2021 ISAKOS Biennial Congress Paper
Validation of a Risk Calculator to Personalize Graft Choice and Reduce Rupture Rates for Anterior Cruciate Ligament Reconstruction
Hana Marmura, BSc, London, ON CANADA
Alan Getgood, MD, FRCS(Tr&Orth), DipSEM, London, ON CANADA
Kurt Paul Spindler, MD, Hillsboro Beach, FL UNITED STATES
Michael W Kattan, PhD, Cleveland, Ohio UNITED STATES
Isaac Briskin, MA, Cleveland, Ohio UNITED STATES
Dianne M. Bryant, PhD, London, ON CANADA
University of Western Ontario, London, Ontario, CANADA
FDA Status Not Applicable
Summary
Validation of an ACL autograft risk calculator appropriate for shared decision making and clinical practice.
Abstract
Background
Anterior cruciate ligament reconstructions (ACLR) fail at an alarmingly high rate in young active individuals. The Multicenter Orthopaedic Outcomes Network (MOON) knee group has developed an autograft risk calculator that uses characteristics of the patient and their lifestyle to predict the probability of graft rupture if the surgeon uses a hamstring tendon (HT) or a bone patellar tendon bone (BPTB) graft to reconstruct the ligament. If validated, this risk calculator can be used during the shared decision-making process to make optimal ACLR autograft choices and reduce rupture rates. The STABILITY 1 randomized clinical trial offers a large, rigorously collected dataset of similar young active patients, who received HT autograft with or without lateral extra-articular tenodesis (LET) for ACLR for validation.
Purpose
To validate the ACLR graft rupture risk calculator in a large external dataset, and to investigate the utility of both BPTB and LET for ACLR.
Methods
The model predictors for the risk calculator include age, sex, body mass index, sport played at the time of injury, Marx activity score, pre-operative knee laxity, and graft type. The STABILITY 1 trial dataset was used for external validation. Discriminative ability, calibration, and diagnostic test validity of the model were assessed. Finally, predictor strength in the initial and validation samples were compared.
Results
The model showed acceptable discriminative ability (AUC = 0.73), calibration (Brier score = 0.07), and specificity (85.3%) to detect patients who will suffer a graft rupture. Age, high-grade pre-operative knee laxity and graft type are significant predictors of graft rupture in young active patients. Both BPTB and the addition of LET to HT are protective against graft rupture versus HT autograft alone.
Conclusion
The MOON risk calculator is a valid predictor of ACLR graft rupture appropriate for clinical practice. This study provides further evidence supporting the idea that isolated HT autografts should be avoided for young active patients undergoing ACLR.