The Patient Acceptable Symptomatic State in Primary Anterior Cruciate Ligament Reconstruction: Predictors of Achievement.
Academic Article
Overview
abstract
PURPOSE: To identify thresholds for patient acceptable symptomatic state (PASS) achievement in a cohort of primary anterior cruciate ligament reconstruction (ACLR) recipients, and to identify factors predictive of PASS achievement. METHODS: A prospective clinical registry was queried for primary ACLR patients from January 2014 to April 2017 with serial patient-reported outcome measure (PROM) completion at 6, 12, and 24 months. Exclusion criteria included significant concomitant procedures. Knee-based PROMs included the International Knee Documentation Committee (IKDC) score and Knee Injury and Osteoarthritis Outcome Score (KOOS) subscores. PASS threshold values were calculated using receiver operating characteristic (ROC) curves with area under the curve (AUC) analysis. A stepwise multivariate regression identified preoperative and operative predictors of PASS achievement. RESULTS: A total of 144 primary ACLR patients (30.86 ± 12.78 years, body mass index 25.51 ± 4.64, 41.0% male) were included in the analysis. PASS threshold values were established using ROC curve analysis, all of which exceeded 0.7 on AUC analysis (0.742 to 0.911). Factors impacting odds of PASS achievement in the ACLR cohort included preoperative exercises (odds ratio [OR] 2.95 to 4.74, P = .003 to .038), worker's compensation status (OR 0.25 to 0.28, P = .014 to .033), preoperative scores (OR 1.03 to 1.07, P = .005 to <.001), iliotibial band tenodesis (OR 11.08, P = .010), and anteromedial approach (OR 18.03 to 37.05, P < .001). CONCLUSION: Factors predictive of PASS achievement in recipients of primary ACLR include functional status (e.g., preoperative exercise, preoperative KOOS Sport/Recreation score), worker's compensation status, technique (e.g., anteromedial) and preoperative PROMs. The results of our study are important in better informing shared decision-making models and improving evidence-based guidelines to optimize patient outcomes.
