Krych, Aaron J.

Background: While patients may report painful or prominent hardware after tibial tubercle osteotomy (TTO), little is known about the frequency, associated factors, and outcomes after removal of symptomatic hardware. Purpose/Hypothesis: The purpose was to investigate the incidence of hardware removal after TTO due to pain or complications, factors associated with hardware removal, and postoperative outcomes after removal. It was hypothesized that clinical outcomes would be similar between patients who underwent TTO without hardware removal and those who underwent TTOs and subsequently hardware removal. Study Design: Case-control study; Level of evidence, 3. Methods: A retrospective analysis was performed on patients who underwent TTO at a single institution from 2000 to 2023. Age at the time of the index surgery, sex, race, body mass index, number and size of screws, tibial tubercle–trochlear groove distance, and reason for hardware removal were collected retrospectively. Knee radiographs were reviewed for measurement of soft tissue–hardware distance. Patients were contacted via email to capture final patient-reported outcome measures (PROMs). A univariate logistic regression model was used to determine factors associated with hardware removal. Results: A total of 152 patients representing 171 knees were included. Of the overall cohort, 38 knees (22.2%) in 32 patients underwent TTO with subsequent hardware removal. The most common reason for hardware removal was anterior knee pain (79%). Compared with patients aged 11 to 20 years, patients aged 21 to 30 years demonstrated higher odds of undergoing hardware removal (OR, 3.67; 95% CI, 1.51-9.44; P = .009). Compared with a soft tissue–hardware distance of 0 to 4.9 mm, a distance of 10.0 to 14.9 mm demonstrated lower odds of hardware removal (OR, 0.24; 95% CI, 0.07-0.84; P = .027). Visual analog scale scores (0-10 scale) improved by a mean of 3.6 points after hardware removal ( P = .003). In patients undergoing hardware removal for pain, no difference in final PROMs was found compared with patients who underwent TTO without hardware removal. Conclusion: Hardware removal in patients undergoing TTO was mainly attributed to hardware-related pain/irritation. On average, pain scores improved after hardware removal. There was no difference in final PROMs between patients who had their hardware removed due to pain (eg, without any clinically relevant concomitant pathology) and patients who did not require hardware removal. Size and number of screws were not associated with a subsequent hardware removal procedure. The thickness of the soft tissue envelope overlying implanted hardware was inconsistently associated with lower odds of hardware removal.

Abstract Hip arthroscopy is a technically demanding procedure that can require a substantial volume of irrigation fluid. Techniques should be explored to optimize fluid use while ensuring satisfactory surgical instrumentation and labral repair. In this technical note, we present a method for performing a dry arthroscopic labral repair. This technique can be used in the treatment of a variety of labral pathologies, including primary labral repair with knotless or hand‐tied anchors, revision labral repair, and labral reconstruction, without the need for irrigation fluid. Additionally, we discuss supplemental techniques that can be used during other portions of the arthroscopic hip procedure to limit irrigation fluid use. Technique Video video See video under supplementary data.

Abstract The standard of care for hip labral tears is arthroscopic repair, with labral reconstruction performed more commonly for irreparable tears in order to avoid isolated labral debridement. However, labral reconstruction can be technically demanding. We provide a concise step‐by‐step guide for performing labral reconstruction or augmentation using a modified retrograde pull‐through technique, including tips, tricks, and surgeon pearls, and pitfalls. Despite the procedure's technically challenging nature, we believe our technique highlights several important steps to improve the practicality and efficiency of the case and produce satisfactory patient outcomes. Technique Video video See video under supplementary data.

Background: Nonoperative and operative management techniques after anterior cruciate ligament (ACL) injury are both appropriate treatment options for selected patients. However, the subsequent development of posttraumatic knee osteoarthritis (PTOA) remains an area of active study. Purpose: To compare the risk of PTOA between patients treated without surgery and with ACL reconstruction (ACLR) after primary ACL disruption using a machine learning causal inference model. Study Design: Cohort study; Level of evidence, 3. Methods: A geographic database identified patients undergoing ACLR between 1990 and 2016 with minimum 7.5-year follow-up. Variables collected include age, sex, body mass index, activity level, occupation, relevant comorbid diagnoses, radiographic findings, injury characteristics, and clinical course. Treatment effects of ACLR on the development of PTOA and progression to total knee arthroplasty (TKA) were analyzed with machine learning models (MLMs) in a causal inference estimator (targeted maximum likelihood estimation, TMLE), while controlling for confounders. Results: The study included 1194 patients with a minimum follow-up of 7.5 years, among whom 974 underwent primary reconstruction and 220 underwent nonoperative treatment. A total of 215 (22%) patients developed symptomatic PTOA in the ACLR group compared with 140 (64%) in the nonoperative treatment group ( P < .001), whereas 25 (3%) patients underwent TKA in the ACLR group compared with 50 (23%) in the nonoperative treatment group ( P < .001). Patients in the ACLR group had delayed TKA compared with patients in the nonoperative treatment group (193.4 vs 166.0 months, respectively; P = .02). TMLE evaluation revealed that reconstruction decreased the risk of PTOA by 11% (95% CI, 8%-13%; P < .001) compared with nonoperative treatment but did not demonstrate a significant effect on the rate of progression to TKA. Survival analysis with random forest algorithm demonstrated significant delay to the onset of PTOA as well as time to progression of TKA in patients undergoing ACLR. Additional risk factors for the development of PTOA, irrespective of treatment, included older age at injury, greater body mass index, total number of arthroscopic knee surgeries, and residual laxity at follow-up. Conclusion: MLMs in a causal inference estimator found ACLR to exert a significant treatment effect in reducing the rate of development of PTOA by 11% compared with nonoperative treatment. ACLR also delayed the onset of PTOA and progression to TKA.

Background: Recent biomechanical evidence for adjustable suture anchor (ASA)–based posterior medial meniscus root (PMMR) fixation has shown promising results compared with conventional transtibial pull-out repair (TPOR). However, ASA fixation has not been evaluated in human tissue to 100,000 cycles. Hypothesis: ASA repair would lead to increased primary fixation strength and less cyclic displacement than conventional TPORs. Study Design: Controlled laboratory study. Methods: A total of 32 human medial menisci were used, 8 of which were intact specimens and served as native controls. For the others, PMMR tears were created and repaired using 3 different techniques (n = 8 group). Two conventional PMMR repairs were prepared consisting of two No. 2 simple sutures (TSS) and two No. 2 sutures in a Mason-Allen (MA) configuration, all tied over a cortical button. The knotless ASA repair was fixed in MA with repair sutures tensioned at 120 N (MA-120). The repairs’ initial force, stiffness, and relief displacement from the tensioned state toward repair unloading (2 N) were measured after fixation. All repair constructs were loaded for 100,000 cycles, with displacement and stiffness measured, and finally were pulled to failure. Results: The TPORs demonstrated similar primary fixation and cyclic loading behavior except for initial cyclic displacement (cycle 10). The ASA repair provided a higher initial repair load ( P < .001) and stiffness ( P < .001) with relief displacement similar to conventional TPORs. Lower initial cyclic displacement ( P < .011; cycle 10) with overall higher repair stiffness ( P < .011) resulted in significantly lower displacement ( P < .001) throughout testing for ASA repair. Although both TPORs were completely loose after 100,000 cycles, the ASA repair achieved near-native dynamic meniscal stabilization. The TSS repair had lower overall ultimate load ( P < .001) and ultimate stiffness ( P < .023) compared with the ASA repair. All repairs had lower ultimate stiffness and loads than the native meniscus ( P < .001). Conclusion: The ASA repair resulted in improved primary PMMR fixation that was stiffer with less cyclic displacement than conventional TPORs and approached that of the human meniscal function after 100,000 load cycles in a cadaveric model. However, all repair techniques had lower ultimate strength than the native human PMMR. Clinical Relevance: Knotless ASA meniscus root fixation resulted in higher tissue compression and less displacement in a cadaveric model; however, future clinical series with surveillance imaging will define the overall significance of healing rates.

Abstract Purpose Developing large‐scale, standardized radiographic registries for anterior cruciate ligament (ACL) injuries with artificial intelligence (AI) tools can enhance personalized orthopaedics. We propose deploying Artificial Intelligence for Knee Imaging Registration and Analysis (AKIRA), a trio of deep learning (DL) algorithms, to automatically classify and annotate radiographs. We hypothesize that algorithms can efficiently organize radiographs based on laterality, projection, identify implants and classify osteoarthritis (OA) grade. Methods A collection of 20,836 knee radiographs from all time points of treatment (mean orthopaedic follow‐up 70.7 months; interquartile range [IQR]: 6.8–172 months) were aggregated from 1628 ACL‐injured patients (median age 26 years [IQR: 19–42], 57% male). Three DL algorithms (EfficientNet, YOLO [You Only Look Once] and Residual Network) were employed. Radiograph laterality and projection (anterior‐posterior [AP], lateral, sunrise, posterior‐anterior, hip–knee–ankle and Camp‐Coventry intercondylar [notch]) were labelled by a DL model. Manually provided labels of metal fixation implants were used to develop a DL object detection algorithm. The degree of OA, both as measured by specific Kellgren–Lawrence (KL) grades, as well as based on a binarized label of OA (defined as KL Grade ≥2), on standing AP radiographs were classified using a DL algorithm. Individual model performances were evaluated on a subset of images prior to the deployment of AKIRA to registry construction using all ACL radiographs. Results The classification algorithms showed excellent performance in classifying radiographic laterality (F1 score: 0.962–0.975) and projection (F1 score: 0.941–1.0). The object detection algorithm achieved high precision–recall (area under the precision‐recall curve: 0.695–0.992) for identifying various metal fixations. The KL classifier reached concordances of 0.39–0.40, improving to 0.81–0.82 for binary OA labels. Sequential deployment of AKIRA following internal validation processed and labelled all 20,836 images with the appropriate views, implants, and the presence of OA within 88 min. Conclusion AKIRA effectively automated the classification and object detection in a large radiograph cohort of ACL injuries, creating an AI‐enabled radiographic registry with comprehensive details on laterality, projection, implants and OA. Study Design Cross‐sectional study. Level of Evidence Level IV.

Background: Anterior cruciate ligament reconstruction (ACLR) is one of the most common orthopaedic procedures and one of the most well studied. Despite extensive research dedicated to ACLR, there is limited understanding of how chronic inflammatory systemic diseases (CIDs) such as rheumatoid arthritis and systemic lupus erythematosus affect outcomes. Purpose: To compare the outcomes of ACLR in cohorts of patients with and without CID. Study Design: Cohort study; Level of evidence, 3. Methods: A retrospective query of a regional data set was conducted for all patients who underwent ACLR from 1990 to 2021 for traumatic ACL rupture. All patients with CID were identified and propensity matched to non-CID controls. Baseline characteristics and clinical outcomes were identified through retrospective chart review, and patients were contacted for subjective outcomes. Results: A total of 30 patients with ACLR and a diagnosis of CID were identified. These patients were propensity matched to 120 non-CID controls. Baseline demographic and surgical characteristics demonstrated no statistical differences. Follow-up duration was similar between the CID and non-CID groups (mean, 14.6 vs 14.2 years; P = .868). The CID cohort had a higher arthrofibrosis rate (16.7% vs 4.3%; P = .031), higher osteoarthritis rate (33.3% vs 16.7%; P = .041), higher total knee arthroplasty (TKA) rate (16.7% vs 3.3%; P = .016), and earlier time to TKA (14.7 vs 23.5 years; P = .032). Knee range of motion, infection rate, retear rate, time to retear, and time to osteoarthritis were not statistically different between the cohorts. The CID cohort had higher visual analog scale pain scores (mean, 2.00 vs 1.20; P = .043) but slightly higher satisfaction (mean, 3.92 vs 3.39; P = .043). There were no differences in preinjury Tegner, postoperative Tegner, change in Tegner, or IKDC score. In a univariate Cox regression model, the CID cohort had a retear hazard ratio of 1.43 (95% CI, 0.46-4.51; P = .537). Kaplan-Meier survival revealed no significant differences in retear-free survival between the CID and non-CID cohorts at 25 years (85.7% vs 87.3%; P = .53). The CID cohort had a TKA hazard ratio of 3.94 (95% CI, 1.05-14.8; P = .042). Kaplan-Meier survival demonstrated significantly decreased TKA-free survival at 25 years in the CID cohort (64.9% vs 91.2%; P = .029). Conclusion: CID increases the incidence of arthrofibrosis, osteoarthritis, and TKA in those undergoing ACLR. Patients with CID also undergo TKA significantly sooner than non-CID counterparts. Notably, the majority of patient-reported outcome measures are no worse in patients who have a CID diagnosis. Thus, ACLR constructs themselves may not necessarily fare worse in patients with CID. Nonetheless, these patients need to be cautiously counseled on the clinical outlook after their ACLR.

ABSTRACTPurposeDouble‐level osteotomies (DLOs) have shown promising results for knee joint preservation, however, most ultimately progress in terms of degenerative disease resulting in conversion to total knee arthroplasty (TKA). Therefore, the purpose of this study was to examine the time to TKA conversion, long‐term clinical outcomes and revision rates of patients who have undergone TKA after prior ipsilateral DLO.MethodsPatients who underwent simultaneous or staged DLO and subsequently underwent conversion to TKA at a single academic institution from 1997 to 2022 were evaluated. The type of osteotomy performed (opening‐ vs. closing‐wedge), osteotomy hardware fixation, when and if osteotomy hardware was removed, implanted TKA components and revision rates were recorded. Postoperative outcomes, including Forgotten Joint Score‐12 (FJS‐12), Tegner Activity Scale score and subjective knee preference were also obtained.ResultsA total of 22 patients (24 knees) underwent TKA following DLO and were followed for an average of 26.1 ± 7.7 years. The average time from DLO to TKA conversion was 14.1 ± 6.5 years, with 70.8% of knees converting to TKA more than 10 years after DLO. The mean follow‐up after conversion to TKA was 12.0 ± 7.7 years. Only 12.5% of patients received a varus‐valgus or hinged‐constrained TKA. At the final follow‐up, the mean FJS‐12 was 75.8 ± 23.1, while the mean Tegner Activity Scale score was 2.5 ± 1.1. Seventy‐seven percent of patients had no subjective knee preference or preferred their DLO‐TKA knee. Only two knees (7.4%) underwent subsequent revision after index arthroplasty at a mean of 9.3 years postoperatively.ConclusionsA majority of DLOs (70.8%) converted to TKA after more than a decade. Subsequent TKA function was favorable as most patients had either no subjective knee preference or preferred their DLO‐TKA knee. This study demonstrates both long‐term joint preservation and uncompromised TKA function after prior DLO.Level of EvidenceLevel IV.

Background: Bucket-handle meniscal tears (BHMTs) are a common subtype of meniscal tears that represent a clinical challenge. Arthroscopic inside-out repair has been considered the gold standard in treatment; however, an all-inside approach has gained widespread popularity, with limited long-term evidence. Purpose/Hypothesis: The purpose of this study was to (1) compare long-term clinical outcomes and rates of failure after surgical repair of BHMTs using the all-inside versus inside-out technique, and 2) identify risk factors for failure at long-term follow-up. It was hypothesized that clinical outcomes and rates of failure would be similar between the 2 techniques. Study Design: Cohort study; Level of evidence, 3. Methods: Patients who had undergone surgical repair of BHMTs between 2003 and 2013 at a single institution were identified. Patient-reported outcome measures (PROMs) were assessed preoperatively and at the latest follow-up using the Tegner scale, International Knee Documentation Committee questionnaire, and visual analog scale pain at rest and with activity. A univariate Cox proportional hazards model was used to identify predictors for repair failure, defined as revision meniscal surgery and/or documented meniscal retear. Results: In total, 63 patients were included (37 with inside-out repair, 26 with all-inside repair). At a mean follow-up of 11.2 years, the survival rate for BHMT repair was 63% overall, 70% for all-inside repairs, and 60% for inside-out repairs ( P = .37). The mean time to failure was 2.6 years for all-inside repairs and 2.5 years for inside-out repairs ( P = .98). PROM scores were not significantly different between the 2 repair groups ( P > .22). Univariate Cox proportional hazards model for failure demonstrated that increasing age at surgery was associated with lower failure rates (hazard ratio, 0.91 change per 1-year increase in age; 95% CI, 0.84-0.98) and medial meniscus repair was associated with higher failure rates (hazard ratio, 3.12; 95% CI, 1.14-8.77). Conclusion: Long-term follow-up of BHMT repair demonstrated satisfactory clinical outcomes and failure rates. In appropriately selected patients, the all-inside technique did not compromise outcome as compared with the inside-out repair techniques. For both methods, older age was associated with lower failure rates and medial meniscus repair was associated with increased failure.

Background: There are limited evidence-based guidelines to predict which osteochondritis dissecans (OCD) lesions will heal with nonoperative treatment. Purpose: To train a set of classification algorithms to predict nonoperative OCD healing while identifying new clinically meaningful predictors. Study Design: Case-control study; Level of evidence, 3. Methods: Patients with OCD of the knee with open physes undergoing nonoperative management were prospectively queried from the Research on OCD of the Knee (ROCK) cohort ( https://kneeocd.org ) in April 2022. Patients were included if they met the study criteria for nonoperative treatment success or failure. Nonoperative treatment success was defined as complete healing on magnetic resonance imaging (MRI) and total return to sports participation. Failure was defined as the crossover from nonoperative management to surgery at any point at or beyond the 3-month follow-up. If a patient did not meet one of these criteria, they were not included. Normalized lesion size, lesion location, patient characteristics, and symptoms were used as clinically relevant predictors. Results: A total of 64 patients were included, of whom 24 (37.5%) patients successfully healed with nonoperative management. Multivariate logistic regression revealed that a 1% increase in normalized lesion width was associated with an increase in the likelihood of nonoperative failure (odds ratio [OR], 1.41 [95% CI, 1.17-1.81]; P < .01). By contrast, lesions in the posterior sagittal zone (OR, 0.08 [95% CI, 0.009-0.43]; P < .01) or the medial-most coronal zone (for lesions of the medial femoral) and lateral-most coronal zone (for lesions of the lateral femoral condyle) on MRI (OR, 0.05 [95% CI, 0.004-0.44]; P < .01) were associated with a decrease in the likelihood of nonoperative treatment failure. Support vector machines had a cross-validated area under the receiver operating characteristic curve of 0.89 and a classification accuracy of 83.3%. Conclusion: Lesion location in the posterior aspect of the condyle on sagittal MRI and lesion location in the medial-most or lateral-most locations on coronal MRI were identified as statistically significant predictors of increased nonoperative treatment success on multivariate analysis. Machine learning models can predict which OCD lesions will heal with nonoperative management with superior accuracy compared with previously published models.