Surgeon Performance as a Predictor for Patient-Reported Outcomes After Arthroscopic Partial Meniscectomy.

Background: Surgeon performance has been investigated as a factor affecting patient outcomes after orthopaedic procedures to improve transparency between patients and providers. Purpose/Hypothesis: The purpose of this study was to identify whether surgeon performance influenced patient-reported outcomes (PROMs) 1 year after arthroscopic partial meniscectomy (APM). It was hypothesized that there would be no significant difference in PROMs between patients who underwent APM from various surgeons. Study Design: Case-control study; Level of evidence, 3. Methods: A prospective cohort of 794 patients who underwent APM between 2018 and 2019 were included in the analysis. A total of 34 surgeons from a large multicenter health care center were included. Three multivariable models were built to determine whether the surgeon-among demographic and meniscal pathology factors-was a significant variable for predicting the Knee injury and Osteoarthritis Outcome Score (KOOS)-Pain subscale, the Patient Acceptable Symptom State (PASS), and a 10-point improvement in the KOOS-Pain at 1 year after APM. Likelihood ratio (LR) tests were used to determine the significance of the surgeon variable in the models. Results: The 794 patients were identified from the multicenter hospital system. The baseline KOOS-Pain score was a significant predictor of outcome in the 1-year KOOS-Pain model (odds ratio [OR], 2.1 [95% CI, 1.77-2.48]; P < .001), the KOOS-Pain 10-point improvement model (OR, 0.57 [95% CI, 0.44-0.73), and the 1-year PASS model (OR, 1.42 [95% CI, 1.15-1.76]; P = .002) among articular cartilage pathology (bipolar medial cartilage) and patient-factor variables, including body mass index, Veterans RAND 12-Item Health Survey-Mental Component Score, and Area Deprivation Index. The individual surgeon significantly impacted outcomes in the 1-year KOOS-Pain mixed model in the LR test (P = .004). Conclusion: Patient factors and characteristics are better predictors for patient outcomes 1 year after APM than surgeon characteristics, specifically baseline KOOS-Pain, although an individual surgeon influenced the 1-Year KOOS-Pain mixed model in the LR test. This finding has key clinical implications; surgeons who wish to improve patient outcomes after APM should focus on improving patient selection rather than improving the surgical technique. Future research is needed to determine whether surgeon variability has an impact on longer-term patient outcomes.

Do Patellar Tendon Repairs Have Better Outcomes than Quadriceps Tendon Repairs? A Prospective Cohort Analysis.

Patellar tendon (PT) and quadriceps tendon (QT) ruptures represent significant injuries and warrant surgical intervention in most patients. Outcome data are predominantly retrospective analyses with low sample sizes. There are also minimal data comparing QT and PT repairs and the variables impacting patient outcomes. The level of evidence of the study is level II (prognosis). From the prospective OME cohort, 189 PT or QT repairs were performed between February 2015 and October 2019. Of these, 178 were successfully enrolled (94.2%) with 1-year follow-up on 141 (79.2%). Baseline demographic data included age, sex, race, BMI, years of education, smoking status, and baseline VR-12 MCS score. Surgical and follow-up data included surgeon volume, fixation technique, baseline, and 1-year Knee Injury and Osteoarthritis Outcome Score-Pain (KOOS-Pain), Knee Injury and Osteoarthritis Outcome Score-Physical Function (KOOS-PS), and 1-year Patient Acceptable Symptom State (PASS) scores and complications. Multivariable regression analysis was utilized to identify prognosis and significant risk factors for outcomes-specifically, whether KOOS-Pain or KOOS-PS were different between QT versus PT repairs. There were 59 patients in the PT cohort and 82 patients in QT cohort. Baseline demographic data demonstrated that PT cohort was younger (45.1 vs. 59.5 years, p <0.001), included significantly fewer patients of White race (51.7 vs. 80.0%, p = 0.001), lesser number of years of education (13.9 vs. 15.2 years, p = 0.020), a higher percentage of "high" surgeon volume (72.9% vs. 43.9%, p = 0.001) and 25.4% of PT repairs had supplemental fixation (QT had zero, p <0.001). Multivariable analysis identified gender (female-worse, p = 0.001), years of education (higher-better, p = 0.02), and baseline KOOS-Pain score (higher-better, p <0.001) as the risk factors that significantly predicted KOOS-Pain score. The risk factors that significantly predicted KOOS-PS were gender (female worse, p = 0.033), race (non-White-worse, p <0.001), baseline VR-12 MCS score (higher-better, p <0.001), and baseline KOOS-PS score (higher better, p = 0.029). KOOS-Pain and KOOS-PS scores improved after both QT and PT repairs. Patient reported pain and function at 1 year were similar between PT and QT repairs after adjusting for known risk factors. Multivariable analysis identified female gender and low baseline KOOS scores as predictors for worse outcomes.

Agreement between intraoperative and magnetic resonance imaging assessments of rotator cuff pathology and 2 magnetic resonance imaging-based assessments of supraspinatus muscle atrophy.

Background: Magnetic resonance imaging (MRI)-based rotator cuff assessment is often qualitative and subjective; few studies have tried to validate such preoperative assessments. This study investigates relationships of preoperative MRI assessments made by conventional approaches to intraoperative findings of tear type, location, and size or MRI-assessed muscle occupation ratio. Methods: Intraoperatively, surgeons assessed tear type, location, anterior-posterior (AP) width, and medial-lateral length in 102 rotator cuff repair patients. Two musculoskeletal radiologists independently assessed the preoperative MRI scans for these same parameters and supraspinatus muscle atrophy by both Warner classification and quantitative occupation ratio. Exact agreement proportions, kappa statistics, and correlation coefficients were used to quantify agreement relationships. Results: Agreement between MRI readers' and surgeons' observations of tear status averaged 93% with κ = 0.38, and that of tear location averaged 77% with κ = 0.50. Concordance correlations of MRI and intraoperative measures of anterior-posterior and medial-lateral tear length averaged 0.59 and 0.56 across readers, respectively. Despite excellent interrater agreement on Warner classification (exact agreement proportion 0.91) and occupation ratio (concordance correlation 0.93) separately, correlations between these 2 measures were -0.54 and -0.64 for the 2 readers, respectively. Patients with Warner grade 0 had occupation ratios ranging from 0.5 to 1.5. Conclusion: Correlations of preoperative MRI tear dimensions and muscle atrophy assessed by conventional approaches with intraoperatively measured tear dimensions and quantitative occupation ratio, respectively, were only fair. Since tear size and muscle atrophy are known strong predictors of outcomes following rotator cuff repair that may influence treatment decisions, surgeons need to be aware of the limitations of MRI methods. Continued development and validation of quantitative preoperative imaging methods to accurately assess these parameters are needed to improve surgical planning and prognosis.

Evaluation of Health Care Disparities in Patients With Anterior Cruciate Ligament Injury: Does Race and Insurance Matter?

Background: It is unknown whether race- or insurance-based disparities in health care exist regarding baseline knee pain, knee function, complete meniscal tear, or articular cartilage damage in patients who undergo anterior cruciate ligament reconstruction (ACLR). Hypothesis: Black patients and patients with Medicaid evaluated for ACLR would have worse baseline knee pain, worse knee function, and greater odds of having a complete meniscal tear. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A cohort of patients (N = 1463; 81% White, 14% Black, 5% Other race; median age, 22 years) who underwent ACLR between February 2015 and December 2018 was selected from an institutional database. Patients who underwent concomitant procedures and patients of undisclosed race or self-pay status were excluded. The associations of race with preoperative Knee injury and Osteoarthritis Outcome Score (KOOS) Pain subscale, KOOS Function subscale, and intraoperatively assessed complete meniscal tear (tear that extended through both the superior and the inferior meniscal surfaces) were determined via multivariate modeling with adjustment for age, sex, insurance status, years of education, smoking status, body mass index (BMI), meniscal tear location, and Veterans RAND 12-Item Health Survey Mental Component Score (VR-12 MCS). Results: The 3 factors most strongly associated with worse KOOS Pain and KOOS Function were lower VR-12 MCS score, increased BMI, and increased age. Except for age, the other two factors had an unequal distribution between Black and White patients. Univariate analysis demonstrated equal baseline median KOOS Pain scores (Black, 72.2; White, 72.2) and KOOS Function scores (Black, 68.2; White, 68.2). After adjusting for confounding variables, there was no significant difference between Black and White patients in KOOS Pain, KOOS Function, or complete meniscal tears. Insurance status was not a significant predictor of KOOS Pain, KOOS Function, or complete meniscal tear. Conclusion: There were clinically significant differences between Black and White patients evaluated for ACLR. After accounting for confounding factors, no difference was observed between Black and White patients in knee pain, knee function, or complete meniscal tear. Insurance was not a clinically significant predictor of knee pain, knee function, or complete meniscal tear.