Delayed multiligament PCL reconstruction is associated with a higher prevalence of intraarticular injury and may influence treatment.

BACKGROUND: The aim of this study was to investigate differences in concomitant injury patterns and their treatment in patients undergoing early (≤ 12 weeks) and delayed (> 12 weeks) primary multiligament posterior cruciate ligament (PCL) reconstruction (PCL-R). METHODS: This study was a retrospective chart review of patients undergoing primary multiligament PCL-R at a single institution between 2008 and 2020. Multiligament PCL-R was defined as PCL-R and concurrent surgical treatment of one or more additional knee ligament(s). Exclusion criteria included isolated PCL-R, PCL repair, and missing data for any variable. Patients were dichotomized into early (≤ 12 weeks) and delayed (> 12 weeks) PCL-R groups based on the time elapsed between injury and surgery. Between-group comparison of variables were conducted with the Chi-square, Fisher's exact, and independent samples t-tests. RESULTS: A total of 148 patients were eligible for analysis, with 57 (38.5%) patients in the early and 91 (61.1%) patients in the delayed multiligament PCL-R groups. Concomitant LCL/PLC reconstruction (LCL-R/PLC-R) was performed in 55 (60%) of delayed multiligament PCL-Rs and 23 (40%) of early PCL-Rs (p = 0.02). Despite similar rates of meniscus injury, concomitant meniscus surgery was significantly more prevalent in the early (n = 25, 44%) versus delayed (n = 19, 21%) multiligament PCL-R group (p = 0.003), with a significantly greater proportion of medial meniscus surgeries performed in the early (n = 16, 28%) compared to delayed (n = 13, 14%) PCL-R group (p = 0.04). The prevalence of knee cartilage injury was significantly different between the early (n = 12, 24%) and delayed (n = 41, 46%) multiligament PCL-R groups (p = 0.01), with more frequent involvement of the lateral (n = 17, 19% vs. n = 3, 5%, respectively; p = 0.04) and medial (n = 31, 34% vs. n = 6, 11%, respectively; p = 0.005) femoral condyles in the delayed compared to the early PCL-R group. CONCLUSIONS: Given higher rates of chondral pathology and medial meniscus surgery seen in delayed multiligament PCL-R, early management of PCL-based multiligament knee injury is recommended to restore knee stability and potentially prevent the development of further intraarticular injury. LEVEL OF EVIDENCE: Level III.

Sports activity and quality of life improve after isolated ACL, isolated PCL, and combined ACL/PCL reconstruction.

PURPOSE: To compare patient-reported outcomes following isolated anterior cruciate ligament reconstruction (ACL-R), isolated posterior cruciate ligament reconstruction (PCL-R), and combined ACL-R and PCL-R (ACL/PCL-R), at a minimum follow-up of 2 years. METHODS: This was a prospective observational registry cohort study based on the Swedish National Knee Ligament Registry. Patients undergoing isolated ACL-R, isolated PCL-R, and combined ACL/PCL-R between 2005 and 2019 were eligible for inclusion. Demographic characteristics as well as injury- and surgery-related data were queried from the SNKLR. To evaluate functional outcomes, the Knee Injury and Osteoarthritis Outcome Score (KOOS) was collected preoperatively and at 1- and 2-year follow-ups and compared between the treatment groups. RESULTS: In total, 45,169 patients underwent isolated ACL-R, 192 patients isolated PCL-R, and 203 patients combined ACL/PCL-R. Preoperatively, and at the 1- and 2-year follow-ups, KOOS subscales were highest for the isolated ACL-R group, followed by the isolated PCL-R, and lowest for the combined ACL/PCL-R groups. Significant improvements were observed across all treatment groups in the majority of KOOS subscales between the preoperative, and 1- and 2-year follow-ups. All treatment groups showed the greatest improvements between the preoperative and 2-year follow-ups in the knee-related quality of life (mean improvement: isolated ACL-R, + 28 points; isolated PCL-R, + 23 points; combined ACL/PCL-R, + 21 points) and the function in sport and recreation (mean improvement: isolated ACL-R, + 26 points; isolated PCL-R, + 20 points; combined ACL/PCL-R, + 19 points) subscales. CONCLUSION: Clinically relevant improvements in knee function can be expected after isolated ACL-R, isolated PCL-R, and combined ACL/PCL-R. Functional improvements were particularly pronounced in the KOOS function in sport and recreation subscale, indicating the importance of knee stability for sports activity. This study facilitates more comprehensive patient education about functional expectations after surgical treatment of isolated and combined ACL and PCL injuries. LEVEL OF EVIDENCE: Level 2.

Different patient and activity-related characteristics result in different injury profiles for patients with anterior cruciate ligament and posterior cruciate ligament injuries.

PURPOSE: To compare patient characteristics including patient sex, age, body mass index (BMI), activities at the time of injury and injury profiles in patients with anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) injuries. METHODS: Data were obtained from the Swedish National Knee Ligament Registry. Two study groups were created: (1) index ACL reconstruction (ACL group) and (2) index PCL reconstruction (PCL group). Between-group differences were investigated using Fisher's exact test and Fisher's non-parametric permutation test for dichotomous variables and continuous variables, respectively. RESULTS: Of 39,010 patients, 38,904 were ACL injuries. A larger proportion of patients with combined injuries to the PCL, meniscus and cartilage were female, aged > 25 years and with a BMI of > 35 kg/m2 compared with patients with combined injuries to the ACL, meniscus and cartilage. An isolated ACL injury was more commonly found in males, while all other injury profiles of ACL, including combined injuries with meniscus, cartilage and collateral ligament injuries, were more frequently observed in females. The PCL injuries were sustained either during pivoting sports, non-pivoting sports or were traffic-related. CONCLUSION: Different patient characteristics (BMI, age and sex), and activities at the time of injury (sport- versus traffic-related activities), resulted in distinct injury profiles for the ACL and PCL groups. These findings provide valuable information of the way specific injury patterns of cruciate ligament injuries occur, and subsequently may help clinicians with the diagnostic process of ACL and PCL injuries. LEVEL OF EVIDENCE: III.

Different injury patterns exist among patients undergoing operative treatment of isolated PCL, combined PCL/ACL, and isolated ACL injuries: a study from the Swedish National Knee Ligament Registry.

PURPOSE: To compare demographic characteristics and concomitant injury patterns in patients undergoing primary isolated posterior cruciate ligament reconstruction (PCL-R) and combined posterior cruciate ligament (PCL) and anterior cruciate ligament (ACL) reconstruction (PCL-R/ACL-R) with isolated ACL reconstruction (ACL-R) as a reference using data from the Swedish National Knee Ligament Registry (SNKLR). METHODS: This cohort study based on the SNKLR comprised patients undergoing either PCL-R, ACL-R, or combined PCL-R/ACL-R between January 1, 2005 and December 31, 2019 in Sweden. Demographic and surgery-related data with regards to injury mechanism, concomitant intraarticular lesions and their treatment, neurovascular damage, and concomitant ligamentous injuries were extracted. Exclusion criteria included concomitant fractures of the femur, fibula, patella or tibia, and quadriceps or patellar tendon injury. RESULTS: A total of 45,564 patients were included in this study. Isolated PCL-R, combined PCL-R/ACL-R, and isolated ACL-R were performed in 192 (0.4%), 203 (0.5%) and 45,169 (99.1%) patients, respectively. Sports were identified as the cause of 64% of PCL-Rs, 54% of PCL-R/ACL-Rs, and 89% of ACL-Rs, while a traffic-related mechanism was identified in 20% of PCL-Rs, 27% of PCL-R/ACL-Rs and 2% of ACL-Rs. Meniscus injury prevalence was 45% in ACL-Rs, 31% in PCL-R/ACL-Rs and 16% in isolated PCL-Rs (p < 0.001). Cartilage injuries were more common in PCL-R (37%) and PCL-R/ACL-R patients (40%) compared to ACL-R patients (26%, p < 0.001). Concomitant knee ligament injury was identified in 28-44% of PCL-R/ACL-R patients. Neurovascular injuries were present in 9% of PCL-R/ACL-Rs, 1% of PCL-Rs, and 0.3% of ACL-Rs (p < 0.001). CONCLUSION: Differences in injury mechanisms among patient groups confirm that operatively treated PCL tears are frequently caused by both traffic and sports. Cartilage and ligament injuries were more frequent in patients with PCL-R compared to ACL-R. Consequently, combined PCL and ACL tears should raise suspicion for concomitant knee lesions with clinical relevance during the operative treatment of these complex injuries. LEVEL OF EVIDENCE: III.

Timing of Anterior Cruciate Ligament Surgery.

This narrative review examines the current literature for the influence of the surgical timing in the setting of anterior cruciate ligament (ACL) reconstruction on various outcomes. Although the exact definition of early and delayed ACL reconstruction (ACLR) is a subject of controversy, surgical timing influences arthrofibrosis and postoperative stiffness, quadriceps strength, postoperative knee function, and the incidence of intra-articular injuries to the menisci and cartilage. Additionally, there is a shortage of evidence regarding the role of ACLR timing in the setting of multiligament knee injury and when concurrent procedures are performed during the operative treatment of the ACL-injured knee.

A practical guide to the implementation of artificial intelligence in orthopaedic research-Part 2: A technical introduction.

Recent advances in artificial intelligence (AI) present a broad range of possibilities in medical research. However, orthopaedic researchers aiming to participate in research projects implementing AI-based techniques require a sound understanding of the technical fundamentals of this rapidly developing field. Initial sections of this technical primer provide an overview of the general and the more detailed taxonomy of AI methods. Researchers are presented with the technical basics of the most frequently performed machine learning (ML) tasks, such as classification, regression, clustering and dimensionality reduction. Additionally, the spectrum of supervision in ML including the domains of supervised, unsupervised, semisupervised and self-supervised learning will be explored. Recent advances in neural networks (NNs) and deep learning (DL) architectures have rendered them essential tools for the analysis of complex medical data, which warrants a rudimentary technical introduction to orthopaedic researchers. Furthermore, the capability of natural language processing (NLP) to interpret patterns in human language is discussed and may offer several potential applications in medical text classification, patient sentiment analysis and clinical decision support. The technical discussion concludes with the transformative potential of generative AI and large language models (LLMs) on AI research. Consequently, this second article of the series aims to equip orthopaedic researchers with the fundamental technical knowledge required to engage in interdisciplinary collaboration in AI-driven orthopaedic research. Level of Evidence: Level IV.

A practical guide to the implementation of AI in orthopaedic research - part 1: opportunities in clinical application and overcoming existing challenges.

Artificial intelligence (AI) has the potential to transform medical research by improving disease diagnosis, clinical decision-making, and outcome prediction. Despite the rapid adoption of AI and machine learning (ML) in other domains and industry, deployment in medical research and clinical practice poses several challenges due to the inherent characteristics and barriers of the healthcare sector. Therefore, researchers aiming to perform AI-intensive studies require a fundamental understanding of the key concepts, biases, and clinical safety concerns associated with the use of AI. Through the analysis of large, multimodal datasets, AI has the potential to revolutionize orthopaedic research, with new insights regarding the optimal diagnosis and management of patients affected musculoskeletal injury and disease. The article is the first in a series introducing fundamental concepts and best practices to guide healthcare professionals and researcher interested in performing AI-intensive orthopaedic research studies. The vast potential of AI in orthopaedics is illustrated through examples involving disease- or injury-specific outcome prediction, medical image analysis, clinical decision support systems and digital twin technology. Furthermore, it is essential to address the role of human involvement in training unbiased, generalizable AI models, their explainability in high-risk clinical settings and the implementation of expert oversight and clinical safety measures for failure. In conclusion, the opportunities and challenges of AI in medicine are presented to ensure the safe and ethical deployment of AI models for orthopaedic research and clinical application. Level of evidence IV.

Scoping Review on ACL Surgery and Registry Data.

PURPOSE OF REVIEW: To present an overview of registry-based anterior cruciate ligament (ACL) research, as well as provide insight into the future of ACL registries. RECENT FINDINGS: During the past decades, the ACL registries have had an important role in increasing our understanding of patients with ACL injuries and their treatment. The registry data has deepened our understanding of factors that have been associated with an increased risk of sustaining an ACL injury and for evaluation of treatment factors and their impact on patient-related outcomes. Recently, registry-based ACL research using artificial intelligence (AI) and machine learning (ML) has shown potential to create clinical decision-making tools and analyzing outcomes. Thus, standardization of collected data between the registries is needed to facilitate the further collaboration between registries and to facilitate the interpretation of results and subsequently improve the possibilities for implementation of AI and ML in the registry-based research. Several studies have been based on the current ACL registries providing an insight into the epidemiology of ACL injuries as well as outcomes following ACL reconstruction. However, the current ACL registries are facing future challenges, and thus, new methods and techniques are needed to ensure further good quality and clinical applicability of study findings based on ACL registry data.