Abstract
INTRODUCTION: Anterior cruciate ligament (ACL) surgeries are among the most common orthopaedic surgeries performed globally. The quoted failure rates of ACL surgery are approximately 10-15%, which is unacceptably high. The likely cause of failure is multi-factorial and the ability to predict a high-risk patient pre-operatively will allow surgeons to be better decision makers. The aim of the present study was to assess risk factors for failure and develop a score to help predict failure in ACLR. MATERIALS AND METHODS: A retrospective case-control study (n=112 patients) was carried out over a period of two years at a tertiary referral centre. Patients with ACLR failure were grouped into Group 1 (n=56) and patients with a successful ACLR at one year follow-up with no objective or subjective instability AND return to sport were age matched to group 2 (n=56). Risk factor regression analysis was carried out to develop a scoring system (MATS score) and ROC curve analysis was used to generate a cut-off score to predict failure risk. RESULTS: The frequency mapping data showed a high level of prevalence of risk factors in the test group versus the control group. We found an average MATS score of 4.1 in the control group versus 5.9 in the test group. ROC curve analysis showed that a cut off value of 5.5 may be taken with a good sensitivity and specificity, and good inter-observer reliability. CONCLUSION: Based on our assessment of risk factors in the study population we developed the MATS score to aid in clinical decision making. Patients with a score of less than or equal to 5 can be classified as low risk of failure. Patients with a score of 6 or more are considered high risk for ACLR failure.