Cole, Brian J.

AbstractPurposeRecovery following elective knee arthroscopy can be compromised by prolonged postoperative opioid utilization, yet an effective and validated risk calculator for this outcome remains elusive. The purpose of this study is to develop and validate a machine‐learning algorithm that can reliably and effectively predict prolonged opioid consumption in patients following elective knee arthroscopy.MethodsA retrospective review of an institutional outcome database was performed at a tertiary academic medical centre to identify adult patients who underwent knee arthroscopy between 2016 and 2018. Extended postoperative opioid consumption was defined as opioid consumption at least 150 days following surgery. Five machine‐learning algorithms were assessed for the ability to predict this outcome. Performances of the algorithms were assessed through discrimination, calibration, and decision curve analysis.ResultsOverall, of the 381 patients included, 60 (20.3%) demonstrated sustained postoperative opioid consumption. The factors determined for prediction of prolonged postoperative opioid prescriptions were reduced preoperative scores on the following patient‐reported outcomes: the IKDC, KOOS ADL, VR12 MCS, KOOS pain, and KOOS Sport and Activities. The ensemble model achieved the best performance based on discrimination (AUC = 0.74), calibration, and decision curve analysis. This model was integrated into a web‐based open‐access application able to provide both predictions and explanations.ConclusionFollowing appropriate external validation, the algorithm developed presently could augment timely identification of patients who are at risk of extended opioid use. Reduced scores on preoperative patient‐reported outcomes, symptom duration and perioperative oral morphine equivalents were identified as novel predictors of prolonged postoperative opioid use. The predictive model can be easily deployed in the clinical setting to identify at risk patients thus allowing providers to optimize modifiable risk factors and appropriately counsel patients preoperatively.Level of evidenceIII.

Purpose To compare the performance of the Patient‐Reported Outcomes Measurement Information System (PROMIS) physical function (PF), pain interference (PIF), and depression computer adaptive tests (CAT) relative to legacy instruments in patients undergoing meniscal surgery. Methods Patients scheduled to undergo meniscal surgery completed legacy knee function PROMs (International Knee Documentation Committee [IKDC], Knee Injury and Osteoarthritis Outcome Score [KOOS] subscores), Marx Activity Rating Scale (MARS), Veterans‐Rand 12 (VR12), Short Form 12 (SF12), and the Brief Resilience Scale (BRS) alongside PROMIS PF, PIF, and Depression preoperatively. Spearman rank correlations were calculated, and score distributions were examined for floor and ceiling effects. Results 152 patients (46.6 ± 14.9 years, 67.1% male) completed PROMs for appropriate inclusion. PROMIS PF yielded high‐moderate to high correlations with the IKDC and KOOS subscales ( r = 0.61 to 0.73), demonstrating similar performance to the IKDC. PROMIS PIF demonstrated moderately high‐moderate to high correlations with the IKDC, KOOS subscales, VR‐12 Physical Component Score (PCS), and SF12 PCS ( r = 0.62 to 0.71), performing comparably to KOOS Pain ( r = 0.55 to 0.92). PROMIS Depression demonstrated moderate to high‐moderate correlations with the mental health legacies ( r = 0.46 to 0.66). Significant ceiling effects were observed for MARS (n = 29, 18.8%), and significant floor effects were exhibited by PROMIS Depression (n = 38, 25%) and MARS (n = 27, 17.6%). Conclusion The PROMIS PF, PIF CAT, and Depression instruments exhibit comparable performance profiles relative to legacy knee PROMs. PROMIS PF and PIF demonstrated no floor and ceiling effects, whereas PROMIS Depression exhibited a significant relative floor effect. PROMIS PF and PIF may be appropriately used to establish functional baselines preoperatively. Level of Evidence IV, diagnostic case series.

AbstractInfection is a rare occurrence after revision anterior cruciate ligament reconstruction (rACLR). Because of the low rates of infection, it has been difficult to identify risk factors for infection in this patient population. The purpose of this study was to report the rate of infection following rACLR and assess whether infection is associated with patient‐ and surgeon‐dependent risk factors. We reviewed two large prospective cohorts to identify patients with postoperative infections following rACLR. Age, sex, body mass index (BMI), smoking status, history of diabetes, and graft choice were recorded for each patient. The association of these factors with postoperative infection following rACLR was assessed. There were 1423 rACLR cases in the combined cohort, with 9 (0.6%) reporting postoperative infections. Allografts had a higher risk of infection than autografts (odds ratio, 6.8; 95% CI, 0.9–54.5; p = .045). Diabetes (odds ratio, 28.6; 95% CI, 5.5–149.9; p = .004) was a risk factor for infection. Patient age, sex, BMI, and smoking status were not associated with risk of infection after rACLR.

Purpose (1) To determine the area of posterior cruciate ligament (PCL) insertion sites on the lateral wall of the medial femoral condyle (LWMFC) that demonstrates the least amount of length change through full range of motion (ROM) and (2) to identify a range of flexion that would be favorable for graft tensioning for single‐bundle (SB) and double‐bundle (DB) PCL reconstruction. Methods Six fresh‐frozen cadaveric knees were obtained. Three‐dimensional computed tomography point‐cloud models were obtained from 0° to 135°. A point grid was placed on the LWMFC and the tibial PCL facet. Intra‐articular length was calculated for each point on the femur to the tibia at all flexion angles and grouped to represent areas for bone tunnels of SB and DB PCLR. Normalized length changes were evaluated. Results Femoral tunnel location and angle of graft fixation were significant contributors to mean, minimum, and maximum normalized length of the PCL (all p < .001). Tibial tunnel location was not significant in any case (all p < .22). A femoral tunnel in the location of the posteromedial bundle of the PCL resulted in the least length change at all tibial positions (maximum change 13%). Fixation of the anterolateral bundle in extension or at 30° flexion resulted in significant overconstraint of the PCL graft. The femoral tunnel location for a SB PCLR resulted in significant laxity at lower ranges of flexion. Conclusion PCL length was significantly dependent on femoral tunnel position and angle of fixation, whereas tibial tunnel position did not significantly contribute to observed differences. All PCL grafts demonstrated anisometry, with the anterolateral bundle being more anisometric than the posteromedial bundle. For DB PCLR, the posteromedial bundle demonstrated the highest degree of isometry throughout ROM, although no area of the LWMFC was truly isometric. The anterolateral bundle should be fixed at 90° to avoid overconstraint, and SB PCLR demonstrated significant laxity at lower ranges of flexion. Clinical Relevance Surgeons can apply the results of this investigation to surgical planning in PCLR to optimize isometry, which may ultimately reduce graft strain and the risk of graft failure. Additionally, DB PCLR demonstrated superiority compared with SB PCLR regarding graft isometry, as significant laxity was encountered at lower ranges of flexion in SB PCLRs. Fixation of the ALB at 90° flexion should be performed to avoid overconstraint in knee extension.

Purpose The purpose of this study is to define the impact of preoperative opioid use on postoperative opioid use, patient‐reported outcomes, and revision rates in a cohort of patients receiving arthroscopic shoulder surgery. Methods Patients who underwent shoulder arthroscopy were identified from an institutional database. Inclusion criteria were completion of preoperative and postoperative patient‐reported outcome measures (PROMs) at 1‐year follow‐up and completion of a questionnaire on use of opioids and number of pills per day. Outcomes assessed included postoperative PROM scores, postoperative opioid use, persistent pain, and achievement of the patient acceptable symptomatic state. A matched cohort analysis was performed to evaluate the impact of opioid use on achievement of postoperative outcomes, whereas a multivariate regression was performed to determine additional risk factors. Receiver operating characteristic curves were used to establish threshold values in oral morphine equivalents (OMEs) that predicted each outcome. Results A total of 184 (16.3%) patients were included in the opioid use (OU) group and 1,058 in the no opioid use (NOU) group. The OU and NOU groups showed statistically significant differences in both preoperative and postoperative scores across all PROMs ( P < .001). Multivariate logistic regression identified preoperative opioid use as a significant predictor of reduced achievement of the patient acceptable symptomatic state (odds ratio [OR], 0.69, 95% confidence interval [CI], 0.29‐0.83, P = .008), increased likelihood of endorsing persistent pain (OR, 1.73, 95% CI, 1.17‐2.56, P = .006), and increased opioid use at 1 year (OR, 21.3, 95% CI, 12.2‐37.2, P < .001). Consuming a high dosage during the perioperative period increased risk of revision surgery (OR, 8.59, 95% CI, 2.12‐34.78, P < .003). Results were confirmed by matched cohort analysis. Receiver operating characteristic analysis found that total OME >1430 mg/d in the perioperative period (area under the curve, 0.76) and perioperative daily OME >32.5 predicted postoperative opioid consumption (area under the curve, 0.79). Conclusions Patients with a history of preoperative opioid use can achieve significant improvements in patient‐reported outcomes after arthroscopic shoulder surgery. However, preoperative opioid use negatively impacts patients’ level of satisfaction and is a significant predictor of pain and continued opioid usage. Level of evidence Level III, retrospective cohort study

Objective To analyze the topography of the opposite condyle to treat focal femoral condyle articular defects with an osteochondral allograft (OCA). Design Three groups were created: Group 1, same condyle with same width; Group 2, opposite condyle with same width; Group 3, opposite condyle with different width. Computed tomography (CT) of 22 cadaveric femoral hemi-condyles was used to create 3-dimensional CT models that were exported into point-cloud models. Three zones of the donor condyle (anterior, middle, and posterior) were quantified. Four defect sizes were created (15, 18, 23, 25 mm) at the weight-bearing region. The defect was moved throughout each donor condyle zone and the least distance was calculated, defined as the shortest distance between the defect and the donor condyle. Results The mean least distance increased with larger defect size in all groups, yet there was a less than 0.2 mm difference in the least distance among defect sizes. The 15, 18, and 23 mm defect models in Group 1 exhibited greater least distances at the anterior than middle and posterior zones. The 15 mm defect model exhibited greater least distance at the anterior zone than posterior zone in Group 3. However, there was a less than 0.05 mm difference in the mean least distance between zones. There was no significant difference in the least distance between groups. Conclusion OCAs from opposite condyles yield similar topographic matching to OCAs from the same condyles, suggesting that opposite condyles can be utilized. Clinical correlation and outcomes are necessary.

Objectives: The purpose of this study is to investigate the ability of competitive athletes to remain at a high level of competition following osteochondral allograft transplantation (OCA) of the knee. Methods: A retrospective review was performed to identify all competitive athletes (high school, collegiate, professional) who underwent an isolated femoral condyle OCA between 2004 and 2012. Patient reported outcome (PRO) questionnaires (Lysholm, International Knee Documentation Committee (IKDC), Knee Injury and Osteoarthritis Outcome Score (KOOS), Western Ontario and McMasters Universities Arthritis Index (WOMAC), Short Form-12 (SF-12), Tegner, and Marx) and custom return-to-sport surveys were administered. All subsequent reoperations were documented. Results: A total of 13 (7 male, 6 female) athletes were identified with an average follow-up of 5.9 ± 2.5 years. Four athletes competed at an intercollegiate level, while 9 played high-level high-school sports. Seven athletes returned to competitive sport (54%) at an average of 7.9 ± 3.5 months, five of whom were returned to pre-injury levels of play. Of the eight athletes who either did not return to sport or failed to sustain their high level of play, the most common reasons cited were a change in life circumstances, such as graduation, or a fear of re-injury (Figure 1). At final follow-up, regardless of return-to-play, all athletes had significant improvements in all PRO scores except for KOOS-Sport, WOMAC-Stiffness, and SF-12 Mental subscales. Tegner Activity scores dropped significantly from pre-injury to final follow-up (8.2 ± 2.4, 4.5 ± 2.1, p < 0.01). There were three reoperations and zero instances of graft failure. Conclusion: OCAs provide acceptable rates of return-to-play and excellent long-term outcomes for high-level athletes with large osteochondral defects. Social factors are three times more likely than persistent pain to prevent return to sport.