Patel, Bhavik H.

Background: In professional sports, injuries resulting in loss of playing time have serious implications for both the athlete and the organization. Efforts to quantify injury probability utilizing machine learning have been met with renewed interest, and the development of effective models has the potential to supplement the decision-making process of team physicians. Purpose/Hypothesis: The purpose of this study was to (1) characterize the epidemiology of time-loss lower extremity muscle strains (LEMSs) in the National Basketball Association (NBA) from 1999 to 2019 and (2) determine the validity of a machine-learning model in predicting injury risk. It was hypothesized that time-loss LEMSs would be infrequent in this cohort and that a machine-learning model would outperform conventional methods in the prediction of injury risk. Study Design: Case-control study; Level of evidence, 3. Methods: Performance data and rates of the 4 major muscle strain injury types (hamstring, quadriceps, calf, and groin) were compiled from the 1999 to 2019 NBA seasons. Injuries included all publicly reported injuries that resulted in lost playing time. Models to predict the occurrence of a LEMS were generated using random forest, extreme gradient boosting (XGBoost), neural network, support vector machines, elastic net penalized logistic regression, and generalized logistic regression. Performance was compared utilizing discrimination, calibration, decision curve analysis, and the Brier score. Results: A total of 736 LEMSs resulting in lost playing time occurred among 2103 athletes. Important variables for predicting LEMS included previous number of lower extremity injuries; age; recent history of injuries to the ankle, hamstring, or groin; and recent history of concussion as well as 3-point attempt rate and free throw attempt rate. The XGBoost machine achieved the best performance based on discrimination assessed via internal validation (area under the receiver operating characteristic curve, 0.840), calibration, and decision curve analysis. Conclusion: Machine learning algorithms such as XGBoost outperformed logistic regression in the prediction of a LEMS that will result in lost time. Several variables increased the risk of LEMS, including a history of various lower extremity injuries, recent concussion, and total number of previous injuries.

Background: Clinically significant outcomes (CSOs) connect patient-reported outcome measures data to patient-perceived benefit. Although investigators have established threshold values for various CSOs, the timeline to achieve these outcomes after isolated biceps tenodesis (BT) has yet to be defined. Purpose: To define the time-dependent nature of minimal clinically important difference (MCID), substantial clinical benefit (SCB), and Patient Acceptable Symptom State (PASS) achievement after isolated BT. Study Design: Case series; Level of evidence, 4. Methods: The American Shoulder and Elbow Surgeons score (ASES), the Single Assessment Numeric Evaluation, and the Constant-Murley score (CMS) were administered preoperatively and at 6 and 12 months postoperatively to patients undergoing isolated BT between 2014 and 2018 at our institution. Cumulative probabilities for achieving MCID, SCB, and PASS were calculated using Kaplan-Meier survival analysis. Weibull parametric regression evaluated the hazard ratios (HRs) of achieving earlier MCID, SCB, and PASS. Results: Overall cohort (N = 190) achievement rates ranged between 77.8% and 83.2% for MCID, between 42.2% and 80.2% for SCB, and between 59.7% and 62.9% for PASS. Median achievement time was 5.3 to 6.1 months for MCID, 5.9 to 6.4 months for SCB, and 6.07 to 6.1 months for PASS. Multivariate Weibull parametric regression identified older age, male sex, higher body mass index, preoperative thyroid disease, smoking history, and higher preoperative CMS as predictors of delayed CSO achievement (HR, 1.01-6.41), whereas normal tendon on arthroscopy, defined as absence of tenosynovitis or tendon tear on arthroscopy, predicted earlier CSO achievement (HR, 0.19-0.46). Location of tenodesis and worker compensation status did not significantly predict the time to achieve CSOs on multivariate analysis. Conclusion: After isolated BT, patients can expect to attain CSO by 13 months postoperatively, with most patients achieving this between 5 and 8 months. Patients tend to take longer to achieve PASS than MCID and SCB.

Purpose To review the literature on postoperative corticosteroid injections (CSIs) following primary rotator cuff repair (RCR) to evaluate efficacy and adverse effects. Methods A systematic review of the MEDLINE, EMBASE, and Cochrane databases were performed to identify all studies published within the last 15 years, which reported on outcomes of postoperative CSIs following RCR. Studies including patients who received only preoperative CSIs and revision RCRs were excluded. Included studies were evaluated for study methodology, patient demographics, outcome measures, physical examination parameters, results of imaging studies, and adverse effects or clinical complications. Results Seven studies comprising 5,528 patients satisfied inclusion criteria. Among included patients, 54.8% were female and mean age range from 52.3 ± 13.0 to 62.7 ± 6.6 years. Only 1 included investigation was a Level I study. Overall, 4 of 5 studies reported significant improvements in pain and outcome scores (Constant score, American Shoulder and Elbow Surgeons score) compared with controls. Across all studies, the majority of these effects were statistically significant at 3 months postoperatively but not beyond this time point. Five of the 6 included investigations reported no increased rate of retears after postoperative CSIs. One study did find an increase in retear in patients receiving postoperative CSIs but was unable to determine whether these retears were present before the patient received the CSI. Another investigation reported an increased rate of infection only if the CSI was administered in the first postoperative month. Conclusions Postoperative CSIs may improve pain and function for up to 3 months following primary RCR but not at later follow‐up time points. CSIs should be administered only after the first postoperative month to minimize the potential risk for adverse events. Level of Evidence Systematic review of level I‐IV studies.

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.

Background There is increased emphasis on properly allocating healthcare resources to optimize value within orthopedic surgery. Establishing time to maximal medical improvement (MMI) can inform clinical decision-making and practice guidelines. Purpose We sought (1) to evaluate the time to MMI as predicted by commonly used patient-reported outcome measures (PROMs) for evaluation of shoulder stabilization and (2) to evaluate typical time to return to sports and employment following surgery. Methods A systematic review of the Medline database was conducted to identify outcome studies reporting sequential follow-up at multiple time points, up to a minimum of 2 years after shoulder stabilization surgery. The included studies examined the outcomes of arthroscopic or open surgical techniques on anterior instability. Clinically significant improvements were evaluated utilizing the minimal clinically important difference specific to each PROM. Secondary outcomes included range of motion, return to sport/work, and recurrent instability. Results Ten studies comprising 590 surgically managed cases of anterior shoulder instability were included (78% arthroscopic, 22% open). Clinically significant improvements in PROMs were achieved up to 1 year post-operatively for Rowe, Western Ontario Instability Index (WOSI), American Shoulder and Elbow Surgeons (ASES), and Simple Shoulder Test (SST) scores. For the three most utilized tools (Rowe, WOSI, ASES), the majority of improvement occurred in the first 6 post-operative months. Clinically significant improvements in Constant Score and Oxford Shoulder Instability Score (OSIS) were achieved up to 6 months and 2 years after surgery, respectively. No clinically significant improvements were achieved on the Disabilities of the Arm, Shoulder, and Hand (DASH) tool. Conclusion Maximal medical improvement as determined by commonly utilized PROMs occurs by 1 year after operative management of anterior shoulder instability. The DASH tool does not appear to demonstrate a reliable time frame for clinically significant outcome improvement.

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