Total Joint Arthroplasty in Patients with Inflammatory Rheumatic Diseases

CB2 regulates oxidative stress and osteoclastogenesis through NOX1-dependent signaling pathway in titanium particle-induced osteolysis

Periprosthetic osteolysis (PPO) induced by wear particles at the interface between the prosthesis and bone is a crucial issue of periprosthetic bone loss and implant failure. After wear and tear, granular material accumulates around the joint prosthesis, causing a chronic inflammatory response, progressive osteoclast activation and eventual loosening of the prosthesis. Although many studies have been conducted to address bone loss after joint replacement surgeries, they have not fully addressed these issues. Focusing on osteoclast activation induced by particles has important theoretical implications. Cannabinoid type II receptor (CB2) is a seven-transmembrane receptor that is predominantly distributed in the human immune system and has been revealed to be highly expressed in bone-associated cells. Previous studies have shown that modulation of CB2 has a positive effect on bone metabolism. However, the exact mechanism has not yet been elucidated. In our experiments, we found that NOX1-mediated ROS accumulation was involved in titanium particle-stimulated osteoclast differentiation. Furthermore, we confirmed that CB2 blockade alleviated titanium particle-stimulated osteoclast activation by inhibiting the NOX1-mediated oxidative stress pathway. In animal experiments, downregulation of CB2 alleviated the occurrence of titanium particle-induced cranial osteolysis by inhibiting osteoclasts and scavenging intracellular ROS. Collectively, our results suggest that CB2 blockade may be an attractive and promising therapeutic scheme for particle-stimulated osteoclast differentiation and preventing PPO.

Machine learning can accurately predict risk factors for all-cause reoperation after ACLR: creating a clinical tool to improve patient counseling and outcomes

PURPOSE

Identifying predictive factors for all-cause reoperation after anterior cruciate ligament reconstruction could inform clinical decision making and improve risk mitigation. The primary purposes of this study are to (1) determine the incidence of all-cause reoperation after anterior cruciate ligament reconstruction, (2) identify predictors of reoperation after anterior cruciate ligament reconstruction using machine learning methodology, and (3) compare the predictive capacity of the machine learning methods to that of traditional logistic regression.

METHODS

A longitudinal geographical database was utilized to identify patients with a diagnosis of new anterior cruciate ligament injury. Eight machine learning models were appraised on their ability to predict all-cause reoperation after anterior cruciate ligament reconstruction. Model performance was evaluated via area under the receiver operating characteristics curve. To explore modeling interpretability and radiomic feature influence on the predictions, we utilized a game-theory-based method through SHapley Additive exPlanations.

RESULTS

A total of 1400 patients underwent anterior cruciate ligament reconstruction with a mean postoperative follow-up of 9 years. Two-hundred and eighteen (16%) patients experienced a reoperation after anterior cruciate ligament reconstruction, of which 6% of these were revision ACL reconstruction. SHapley Additive exPlanations plots identified the following risk factors as predictive for all-cause reoperation: diagnosis of systemic inflammatory disease, distal tear location, concomitant medial collateral ligament repair, higher visual analog scale pain score prior to surgery, hamstring autograft, tibial fixation via radial expansion device, younger age at initial injury, and concomitant meniscal repair. Pertinent negatives, when compared to previous studies, included sex and timing of surgery. XGBoost was the best-performing model (area under the receiver operating characteristics curve of 0.77) and outperformed logistic regression in this regard.

CONCLUSIONS

All-cause reoperation after anterior cruciate ligament reconstruction occurred at a rate of 16%. Machine learning models outperformed traditional statistics and identified diagnosis of systemic inflammatory disease, distal tear location, concomitant medial collateral ligament repair, higher visual analog scale pain score prior to surgery, hamstring autograft, tibial fixation via radial expansion device, younger age at initial injury, and concomitant meniscal repair as predictive risk factors for reoperation. Pertinent negatives, when compared to previous studies, included sex and timing of surgery. These models will allow surgeons to tabulate individualized risk for future reoperation for patients undergoing anterior cruciate ligament reconstruction.

LEVEL OF EVIDENCE

III.

Hyaluronic Acid Injections in the Treatment of Osteoarthritis Secondary to Primary Inflammatory Rheumatic Diseases: A Systematic Review and Qualitative Synthesis

The purpose of this study is to review the current literature on the use of hyaluronic acid (HA) specifically applied to the treatment of osteoarthritis (OA) secondary to primary inflammatory rheumatic diseases. Osteoarthritis should be carefully considered because it has potentially devastating effects on health-related quality of life. Locally injected HA seems to be an effective treatment for OA but it is not clear how to place this treatment in the context of inflammatory rheumatic disorders. To retrieve relevant articles, we conducted the search through MEDLINE, EMBASE and Cochrane Databases performing the PICO strategy. We finally selected four randomized clinical trials and six observational studies and grouped them in accordance with its main objective within three focuses: the clinical effect of HA therapy in joints without any signs of inflammation, the clinical effects of HA therapy in joints with active synovitis, and the involvement and changes of synovial fluid in the treatment of secondary OA. Our qualitative analysis clearly showed that the current literature is marked by high levels of heterogeneity and therefore difficult to interpret. Therefore, our hypothesis that viscosupplementation should be considered as a treatment for chronic moderate symptomatic OA secondary to inflammatory rheumatic diseases, and not for flares with joint swelling, cannot be definitely supported. Well-designed studies are necessary to definitively clarify the range of application of intra-articular HA injections in the treatment of inflammatory rheumatic disorders.

Rheumatology science and practice in India

The practice of rheumatology in a country like India presents its own unique challenges, including the need to manage patients in a cost-constrained setting, where the lack of uniform government funding for healthcare merits the need to optimize the use of cheaper medicines, as well as devise innovative strategies to minimize the use of costlier drugs such as biologic disease-modifying agents. Use of immunosuppressive agents is also associated with increased risks of infectious complications, such as the reactivation of tuberculosis. In this narrative review, we provide a flavor of such challenges unique to Rheumatology practice in India, and review the published literature on the management of common rheumatic diseases from India. In addition, we critically review existing guidelines for the management of rheumatic diseases from this part of the world. We also discuss infectious etiologies of rheumatic complaints, such as leprosy, tuberculosis, and Chikungunya arthritis, which are often encountered here, and pose a diagnostic as well as therapeutic challenge for clinicians. There remains a need to identify and test more cost-effective strategies for Indian patients with rheumatic diseases, as well as the requirement for more government participation to enhance scant facilities for the treatment of such diseases as well as foster the development of healthcare services such as specialist nurses, occupational therapists and physiotherapists to enable better management of these conditions.