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Purpose To compare the clinical outcomes of operative and nonoperative management, identify risk factors for recurrent instability, and identify risk factors for progression to surgery after failed nonoperative management for patients with first‐time anterior shoulder dislocation after the age of 50 years. Methods An established geographic medical record system was used to identify patients who experienced a first‐time anterior shoulder dislocation after the age of 50 years. Patient medical records were reviewed to identify treatment decisions and outcomes of interest, including rates of frozen shoulder and nerve palsy, progression to osteoarthritis, recurrent instability, and progression to surgery. Outcomes were evaluated using Chi‐square tests and survivorship curves were generated using Kaplan‐Meier methods. A Cox model was developed to evaluate for potential risk factors of recurrent instability and progression to surgery after an initial trail of at least 3 months of nonoperative treatment. Results 179 patients were included with a mean follow‐up of 11 years. 14% ( n = 26) underwent early surgery within 3 months and 86% ( n = 153) were initially treated nonoperatively. Mean age (59 years), was similar for both groups, but those that underwent early surgery had an increased rate of full‐thickness rotator cuff tears (82% vs 55%; P = .01), labral tears (24% vs 8.0%; P = .01), and humeral head fracture (23% vs 8.5%; P = .03). When comparing the early surgery group to the nonoperative group, there were similar rates of persistent moderate‐severe pain (19% vs 17%; P = .78) and frozen shoulder (8 vs 9%, respectively; P = .87) at final follow‐up. Although nerve palsy (19% vs 8%; P = .08) and progression to osteoarthritis (20% vs 14%; P = .40) were more common in surgical patients, they experienced lower rates of recurrent instability after surgical intervention (0% vs 15%; P = .03) compared to nonoperatively treated patients. Increasing number of instability events prior to presentation was the greatest risk factor for recurrent instability (HR 232; P < .01). Fourteen percent ( n = 21) failed initial nonoperative treatment and proceeded to surgical intervention at an average of 4.6 years after the initial instability event, and the greatest risk factors for progression to surgery were recurrent instability (HR 3.41; P < .01). Conclusions Although the majority of patients >50 years that experience ASI are treated nonoperatively, those that require surgery tend to have more significant injury pathology, a lower risk of recurrent instability after surgery, but a higher progression to osteoarthritis compared to patients that do not require surgical intervention. There was no difference in pain severity at final follow‐up, rates of frozen shoulder or nerve palsy between patients who underwent initial nonoperative treatment after instability and those who underwent surgery. A history of multiple instability episodes prior to presentation was the greatest predictor of recurrent instability and failure of nonoperative treatment and progression to surgery. Level of Evidence Level III, retrospective cohort study.

Purpose To evaluate the outcomes of arthroscopic superior capsular reconstruction (SCR) and arthroscopy‐assisted lower trapezius tendon transfer (LTT) for posterosuperior irreparable rotator cuff tears (IRCTs). Methods Over an almost 6‐year period (October 2015 to March 2021), all patients who underwent IRCT surgery with a minimum 12‐month follow‐up period were identified. For patients with a substantial active external rotation (ER) deficit or lag sign, LTT was preferentially selected. Patient‐reported outcome scores included the visual analog scale (VAS) pain score, strength score, American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form (ASES) score, Single Assessment Numeric Evaluation (SANE) score, and Quick Disabilities of the Arm, Shoulder and Hand (QuickDASH) score. Results We included 32 SCR patients and 72 LTT patients. Preoperatively, LTT patients had more advanced teres minor fatty infiltration (0.3 vs 1.1, P = .009), a higher global fatty infiltration index (1.5 vs 1.9, P = .035), and a higher presence of the ER lag sign (15.6% vs 48.6%, P < .001). At a mean follow‐up of 2.9 ± 1.3 years (range, 1.0‐6.3 years), no differences in patient‐reported outcome scores were observed. Postoperatively, SCR patients had a lower VAS score (0.3 vs 1.1, P = .017), higher forward elevation (FE) (156° vs 143°, P = .004), and higher FE strength (4.8 vs 4.5, P = .005) and showed greater improvements in the VAS score (6.8 vs 5.1, P = .009), FE (56° vs 31°, P = .004), and FE strength (1.0 vs 0.4, P < .001). LTT patients showed greater improvement in ER (17° vs 29°, P = .026). There was no statistically significant between‐cohort difference in complication rate (9.4% vs 12.5%, P = .645) or reoperation rate (3.1% vs 10%, P = .231). Conclusions With adequate selection criteria, both SCR and LTT provided improved clinical outcomes for posterosuperior IRCTs. Additionally, SCR led to better pain relief and restoration of FE whereas LTT provided more reliable improvement in ER. Level of Evidence Level III, treatment study with retrospective cohort comparison.

Background: Baseball pitching injuries are on the rise. Inertial measurement units (IMUs) provide immediate feedback to players and coaches, allowing for collection outside of the traditional laboratory setting with real-world application. The 4D Motion system provides kinematics throughout the pitching motion and may be beneficial for individualized programs in the throwing athlete. A systematic analysis of these sensors has not been completed. Purpose: To evaluate the validity of the 4D Motion IMU system for analyzing the baseball pitching motion compared with marker-based motion capture, and evaluate the internal reliability and consistency of the device. Study Design: Controlled laboratory study. Methods: Ten high school pitchers participated in this study (10 male; 9 right-hand dominant; mean age, 16.6 ± 1.3 years; mean body mass index, 24.1 ± 3.9). Participants were simultaneously outfitted with six 4D Motion IMU sensors and retroreflective markers. The pitchers threw fastballs at maximum effort off a mound at the standard height and distance. A comparison was made between the IMUs and corresponding motion capture values for shoulder external rotation, elbow flexion, chest extension, pelvis and chest rotation velocity, and rotation acceleration. Results: Significant differences were found for 5 of 7 metrics analyzed. The IMU overreported most metrics, except for elbow flexion and pelvis rotation angular acceleration, where both positive and negative errors were observed. The root mean square error and percentage errors indicated smaller discrepancies for chest extension (4°± 5°) and pelvis (38 ± 19 deg/s) and chest (96 ± 42 deg/s) rotation velocity, with elbow flexion having the largest variance (21°± 9°). Conclusion: The values of the 4D Motion IMU system should not be considered equivalent when compared with marker-based motion capture studies. The system lacked internal consistency and reliability, with angular velocities being the most consistent. Caution should be used when using the metrics provided by an IMU-based system for individualized monitoring. Clinical Relevance: If found valid and reliable, IMUs could be used for longitudinal workload monitoring, individualized throwing and rehabilitation programs, and ultimately injury prevention. This study demonstrates that the data obtained from a 4D Motion system using Gen 3 sensors are not equivalent to the data obtained from a marker-based motion capture system.

Background: Distal biceps tendon ruptures commonly present in the middle-aged population resulting in deficits of strength and endurance. Operative management has shown improved functional outcome; however, there is not a clear consensus on an ideal surgical method. Indications: Distal biceps tendon repair is indicated for patients with clinical evidence and supporting magnetic resonance imaging confirmation of complete or partial rupture of the biceps tendon. Ideally, surgery is performed within 1 to 2 weeks of the injury to minimize the amount of scar tissue that is formed and the severity of the tendon retraction. Technique Description: A single incision is created on the volar surface of the forearm approximately 15 mm distal to the main flexor crease. After dissection to and retrieval of the biceps tendon, a #2 FiberTag stitch is placed distally and secured in a standard looped, locking fashion. An anchor is then placed in the most proximal aspect of the radial tuberosity and preliminarily placed around the tendon. An all-suture intramedullary cortical button is then placed in the distal aspect of the radial tuberosity. The FiberTag sutures are then shuttled through the button and tightened to anatomically reduce the distal biceps. The sutures on the proximal anchor are then used as supplemental fixation. Results: An anterior, single incision technique provides exposure necessary for dual anchor fixation and anatomic restoration of the distal biceps tendon. Utilizing this approach, patients are found to have improved flexion and pronation at 1 year, lower rates of heterotopic ossification, and lower rates of reoperation. Conclusion: Distal biceps tendon repair through an anterior, single incision provides excellent exposure for surgical repair. Utilizing a dual anchor technique, the distal button allows for anatomic fixation while the proximal suture anchor provides secondary fixation and increases the bone-tendon interface. Patient Consent Disclosure Statement: The author(s) attests that consent has been obtained from any patient(s) appearing in this publication. If the individual may be identifiable, the author(s) has included a statement of release or other written form of approval from the patient(s) with this submission for publication.

Objectives: Osteochondritis dissecans (OCD) of the humeral capitellum is an often painful condition that typically affects the adolescent athlete. There is little consensus on treatment and a scarcity of long-term outcomes data. The purpose of this study was to (1) report the long-term outcomes associated with both operative and non-operative management of capitellar OCD, (2) identify factors associated with failure of non-operative management, and (3) determine whether delay in surgery affects final outcomes. Methods: All patients diagnosed with OCD of the capitellum from 1995-2020 within a defined geographic cohort were included. Medical records, imaging studies, and operative reports were manually reviewed to record demographic data, treatment strategies, and outcomes. Surgical treatment was considered delayed if it occurred more than 6 months after symptom onset. Results: A total of 50 elbows with a mean follow-up of 9.4 years were included. Of these, 7 (14%) were treated non-operatively and never underwent surgery during follow-up, while 43 (86%) underwent surgical intervention: 27 had early surgery and 16 underwent delayed surgery after ≥ 6 months of non-operative treatment. When compared to non-operative management, surgical management resulted in superior MEPI scores (90 vs 83, p=0.05), decreased persistence of mechanical symptoms (9% vs 50%, p<0.01), and better elbow flexion (141° vs 131°, p=0.01) at long-term follow up. Older patients had a trend toward increased failure of non-operative management (p=0.06). The presence of an intra-articular loose body strongly predicted failure of non-operative management (p=0.01; OR 13). Plain radiography and MRI had poor sensitivities for identifying loose bodies (27% and 40%, respectively). Differences in outcomes following early versus delayed surgical management were not demonstrated. Conclusions: Patients with capitellar OCD initially treated nonoperatively failed nonoperative management 70% of the time. Elbows that did not undergo surgery had slightly increased symptoms and decreased functional outcomes compared to those treated surgically. In this cohort, the greatest predictors for failure of non-operative treatment were older age and presence of a loose body; however, an initial trial of non-operative treatment did not adversely impact the success of future surgery at long term follow-up. [Table: see text][Table: see text][Table: see text][Table: see text]

Background: Various metrics have emerged for assessing scientific impact, most of which are based on complex calculations and, in many cases, are not freely available. Moreover, most of these metrics are not intended for assessing the scientific impact of research groups. Cumulative group metrics are proposed as an efficient and cost-effective strategy for measuring group scientific impact. Materials and methods: The authors collected peer-reviewed output in 2020 from two academic orthopedic surgery departments [University of Michigan (UM) and Mayo Clinic Rochester (MC)] and one medical device research department [Arthrex Inc. (AI)]. The sites evaluated the Cumulative Group Number of Publications (CGNP), Cumulative Journal Impact Factor (CJIF), Cumulative CiteScore (CCS), Cumulative SCImago Journal Rank (CSJR), and Cumulative Source Normalized Impact per Paper (CSNIP) for the three institutions. Results: In 2020, UM published 159 peer-reviewed studies, MC published 347 peer-reviewed studies, and AI supported 141 publications. The UM publications achieved a CJIF of 513, a CCS of 891, a CSJR of 255, and a CSNIP of 247. The MC publications achieved a CJIF of 956, a CCS of 1568, a CSJR of 485, and a CSNIP of 508. AI-supported publications achieved a CJIF of 314, a CCS of 598, a CSJR of 189, and a CSNIP of 189. Conclusion: The presented cumulative group metrics are an effective tool to assess the scientific impact of a research group. The cumulative submetrics can further evaluate research groups compared with other departments due to field normalization. Department leadership and funding agencies can utilize these metrics to evaluate research output quantitatively and qualitatively.

Purpose To evaluate the cost‐effectiveness of 3 isolated meniscal repair (IMR) treatment strategies: platelet‐rich plasma (PRP)–augmented IMR, IMR with a marrow venting procedure (MVP), and IMR without biological augmentation. Methods A Markov model was developed to evaluate the baseline case: a young adult patient meeting the indications for IMR. Health utility values, failure rates, and transition probabilities were derived from the published literature. Costs were determined based on the typical patient undergoing IMR at an outpatient surgery center. Outcome measures included costs, quality‐adjusted life‐years (QALYs), and the incremental cost‐effectiveness ratio (ICER). Results Total costs of IMR with an MVP were $8,250; PRP‐augmented IMR, $12,031; and IMR without PRP or an MVP, $13,326. PRP‐augmented IMR resulted in an additional 2.16 QALYs, whereas IMR with an MVP produced slightly fewer QALYs, at 2.13. Non‐augmented repair produced a modeled gain of 2.02 QALYs. The ICER comparing PRP‐augmented IMR versus MVP‐augmented IMR was $161,742/QALY, which fell well above the $50,000 willingness‐to‐pay threshold. Conclusions IMR with biological augmentation (MVP or PRP) resulted in a higher number of QALYs and lower costs than non‐augmented IMR, suggesting that biological augmentation is cost‐effective. Total costs of IMR with an MVP were significantly lower than those of PRP‐augmented IMR, whereas the number of additional QALYs produced by PRP‐augmented IMR was only slightly higher than that produced by IMR with an MVP. As a result, neither treatment dominated over the other. However, because the ICER of PRP‐augmented IMR fell well above the $50,000 willingness‐to‐pay threshold, IMR with an MVP was determined to be the overall cost‐effective treatment strategy in the setting of young adult patients with isolated meniscal tears. Level of Evidence Level III, economic and decision analysis.

Purpose To (1) report the long‐term outcomes associated with both operative and nonoperative management of capitellar osteochondritis dissecans (OCD), (2) identify factors associated with failure of nonoperative management, and (3) determine whether delay in surgery affects final outcomes. Methods All patients who received a diagnosis of capitellar OCD from 1995‐2020 within a geographic cohort were included. Medical records, imaging studies, and operative reports were manually reviewed to record demographic data, treatment strategies, and outcomes. The cohort was divided into 3 groups: (1) nonoperative management, (2) early surgery, and (3) delayed surgery. Delayed surgery (surgery ≥6 months after symptom onset) was considered failure of nonoperative management. Results Fifty elbows with a mean follow‐up period of 10.5 years (median, 10.3 years; range, 1‐25 years) were studied. Of these, 7 (14%) were definitively treated nonoperatively, 16 (32%) underwent delayed surgery after at least 6 months of failed nonoperative treatment, and 27 (54%) underwent early surgical intervention. When compared with nonoperative management, surgical management resulted in superior Mayo Elbow Performance Index pain scores (40.1 vs 33, P = .04), fewer mechanical symptoms (9% vs 50%, P < .01), and better elbow flexion (141° vs 131°, P = .01) at long‐term follow‐up. Older patients trended toward increased failure of nonoperative management ( P = .06). The presence of an intra‐articular loose body predicted failure of nonoperative management ( P = .01; odds ratio, 13). Plain radiography and magnetic resonance imaging had poor sensitivities for identifying loose bodies (27% and 40%, respectively). Differences in outcomes after early versus delayed surgical management were not observed. Conclusions Nonoperative management of capitellar OCD failed 70% of the time. Elbows that did not undergo surgery had slightly more symptoms and decreased functional outcomes compared with those treated surgically. The greatest predictors of failure of nonoperative treatment were older age and presence of a loose body; however, an initial trial of nonoperative treatment did not adversely impact the success of future surgery. Level of Evidence Level III, retrospective cohort study.

» Lateral epicondylitis (LE) or tennis elbow is a common cause of elbow pain in the general population, especially women in the fourth and fifth decades of life who participate in repetitive forceful movements involving the wrist and forearm. » The pathogenesis of this overuse injury is believed to start from an overload event leading to a microtear in or near the origin of the extensor carpi radialis brevis that is subsequently prone to additional injury and structural weakness over time. » Treatment of LE often begins with a wide variety of nonoperative modalities including rest, nonsteroidal anti-inflammatory drugs, bracing, and physical therapy. For recalcitrant symptoms, additional nonoperative therapies are implemented; however, there remains a lack of comparative efficacy between these adjunct treatments. » In this article, we examine the available literature regarding nonoperative management of LE and provide supplementary insight into the effectiveness of current modalities.

AbstractDeep learning has the potential to be one of the most transformative technologies to impact orthopedic surgery. Substantial innovation in this area has occurred over the past 5 years, but clinically meaningful advancements remain limited by a disconnect between clinical and technical experts. That is, it is likely that few orthopedic surgeons possess both the clinical knowledge necessary to identify orthopedic problems, and the technical knowledge needed to implement deep learning‐based solutions. To maximize the utilization of rapidly advancing technologies derived from deep learning models, orthopedic surgeons should understand the steps needed to design, organize, implement, and evaluate a deep learning project and its workflow. Equipping surgeons with this knowledge is the objective of this three‐part editorial review. Part I described the processes involved in defining the problem, team building, data acquisition, curation, labeling, and establishing the ground truth. Building on that, this review (Part II) provides guidance on pre‐processing and augmenting the data, making use of open‐source libraries/toolkits, and selecting the required hardware to implement the pipeline. Special considerations regarding model training and evaluation unique to deep learning models relative to “shallow” machine learning models are also reviewed. Finally, guidance pertaining to the clinical deployment of deep learning models in the real world is provided. As in Part I, the focus is on applications of deep learning for computer vision and imaging.