Paper 62: Predictors of Return to Activity at 2 Years After Anterior Cruciate Ligament Reconstruction Among Patients with High Baseline Pre-Injury Marx Activity Level

• Published in: Orthopaedic journal of sports medicine 2023-07, Vol.11 (7_suppl3)
• Main Authors: Jin, Yuxuan, Huston, Laura, Spindler, Kurt, Sheean, Andrew
• Format: Article
• Language: English
• Subjects: Cartilage; Education; Females; Gender; Injuries; Risk factors; Variables
• ISSN: 2325-9671; 2325-9671
• DOI: 10.1177/2325967123S00087

Objectives: Multiple authors have observed that preinjury activity level is a strong predictor of activity level after anterior cruciate ligament (ACL) reconstruction (ACLR.) However, among subjects with a relatively high baseline activity level, predictors for a successful return to preinjury activity level after ACLR remain poorly understood. The purpose of this study was to employ multivariable modeling to identify predictors of return to preinjury level of activity after ACLR among patients with high pre- injury activity scores (Marx activity scores 12-16) that have been prospectively enrolled in the Multicenter Orthopaedic Outcomes Network (MOON) cohort. We hypothesized that age, gender, preoperative activity level, and concurrent articular cartilage injuries would predict return to baseline, preinjury activity level 2 years after ACLR. Methods: All unilateral ACL reconstructions from 2002-2008 enrolled in the MOON cohort performed in subjects with baseline preinjury Marx activity scores ranging from 12 to 16 were evaluated with specific focus on return to preinjury activity level at 2 years postoperative. Continuous variables such as age, BMI, education level, baseline Short Form-36 mental component survey (MCS), baseline Marx activity were summarized using median and interquartile ranges. Categorical variables such as sex, race, smoking status, reconstruction type (primary/revision), graft type etc. were displayed using counts and percentages. The primary outcome of interest was return to activity, which was defined as a raw difference of ≥ -2 between Marx activity score at 2-year minus baseline Marx activity. This means that anyone who had a ≥ -2 difference in Marx activity was considered returned to activity; otherwise, he/she was not considered able to return to activity. To identify predictors and possible risk factors contributing to return to activity, a multivariable logistic regression model was built. Multivariable modeling was performed to identify risk factors for subjects’ inability to return to baseline, preinjury activity level. The relative importance of each predictor was ranked according to the increase in Akaike information criterion (AIC) upon removal from the full model; the importance rankings are presented in descending order; only positive values are presented in the graphs. AIC quantifies the amount of information explained by the covariates, while penalizing variables for the number of degrees of freedom they use. An AIC-inc