Abstract
Objectives:
The field of orthopaedic surgery continues to transition towards using patient-reported outcome measures (PROMs) to measure treatment success. Metrics such as the minimum clinically important difference (MCID) can help define treatment success, but there is no clear consensus on the methodology or application of scores in clinical medicine. MCID calculations can vary significantly based on cohort size, methodology (e.g. anchor-based versus distribution-based methods), follow-up time point, and patient-specific factors. Anterior cruciate ligament reconstruction (ACLR) is a highly prevalent procedure that provides high patient satisfaction according to PROMs such as the Knee Injury & Osteoarthritis Outcome Score (KOOS) and the Single Assessment Numerical Evaluation (SANE). Both scales have MCID values reported in the ACLR literature. The purpose of this study was to identify patients that reached the literature-reported MCID values for KOOS and SANE. The secondary aim was to identify if there were any differences in demographic, injury, and treatment characteristics among patients that reach MCID for KOOS and/or SANE and those that do not.
Methods:
The PROM database of a single ambulatory surgical center was queried for ACLR procedures from 2009-2016. Revision procedures, concomitant ligament repairs/reconstructions, and patients without outcome data at baseline and two-year follow-up were excluded from the study. Demographic, injury, and surgical characteristics were extracted via chart review. Demographics included age, sex, and diagnosis of anxiety and/or depression. Injury characteristics included acuity of injury (≥6 months considered chronic) and presence of meniscal injuries. Surgical characteristics included body mass index (BMI), operative time, American Society of Anesthesiologists (ASA) Score, graft type, implant type, and concomitant meniscal procedures. Outcomes evaluated were KOOS and SANE after two years of ACLR. Patients were grouped according to whether they did or did not meet literature-reported MCIDs for KOOS and/or SANE. One-way analysis of variance and chi-square tests were conducted to identify group differences, with p=0.05 set as the threshold for significance.
Results:
A total of 322 patients were included. Most were female (62.1%) and had an average age of 28. Average BMI and operative time were 25.3 and 108.3 minutes, respectively. Most patients had an ASA score of 1 (84.1%). A total of 20.5% of patients had a mental health diagnosis of anxiety and/or depression. Most patients received a bone-tendon-bone autograft (49.1%). Only 6.8% of patients presented with a chronic injury. The proportion of patients that achieved MCID at two years for KOOS and SANE were 73.6% and 45.7%, respectively (p<0.00001). The majority of patients achieving SANE MCID achieved KOOS MCID (89.8%), while just 55.7% of patients achieving KOOS MCID achieved SANE MCID. 41.0% of patients achieved MCID for both KOOS and SANE, while 21.7% of patients did not achieve MCID for any scale. Compared to patients that achieved MCID in at least one PROM, there was a significantly higher proportion of patients that underwent ACLR for chronic injuries among those that did not meet MCID (11.4% vs 5.6%, p=0.004). Surgical technique did not statistically differ among patients that achieved MCID and those that did not.
Conclusions:
The rates of achieving literature-reported MCID values for KOOS and SANE were significantly different within the same cohort of ACLR patients (73.6% for KOOS vs 45.7% for SANE). Only 41.0% of patients achieved MCID for both PROMs. A higher percentage of patients that did not meet MCID had chronic injuries compared to those that met at least one MCID. Treatment success in ACLR as determined by PROMs is thus a function of the tool employed and the injury/patient undergoing treatment rather than the surgery performed. This study particularly found that the timing from injury to presentation was associated with likelihood of achieving MCID. As orthopaedics continues to incorporate PROM data to determine treatment success as well as prior authorization and reimbursement policies, it is important to refine these PROMs and tailor them to patient-specific factors in order to adequately capture a successful treatment.
