The remarkable progress in data aggregation and deep learning algorithms has positioned artificial intelligence (AI) and machine learning (ML) to revolutionize the field of medicine. AI is becoming more and more prevalent in the healthcare sector, and its impact on orthopedic surgery is already evident in several fields. This review aims to examine the literature that explores the comprehensive clinical relevance of AI-based tools utilized before, during, and after anterior cruciate ligament (ACL) reconstruction. The review focuses on current clinical applications and future prospects in preoperative management, encompassing risk prediction and diagnostics; intraoperative tools, specifically navigation, identifying complex anatomic landmarks during surgery; and postoperative applications in terms of postoperative care and rehabilitation. Additionally, AI tools in educational and training settings are presented. Orthopedic surgeons are showing a growing interest in AI, as evidenced by the applications discussed in this review, particularly those related to ACL injury. The exponential increase in studies on AI tools applicable to the management of ACL tears promises a significant future impact in its clinical application, with growing attention from orthopedic surgeons.

(1) Background: Mobile health (mHealth) solutions can become a means of improving functional recovery and reducing the peri-operative burden and costs associated with arthroplasty procedures. The aim of this study is to explore the objectives, functionalities, and outcomes of a platform designed to provide personalized surgical experiences to qualified patients, along with the associated problems and opportunities. (2) Methods: A survey-based analysis was conducted on patients who were prescribed the use of a specific care management platform and underwent primary robotic total knee arthroplasty (rTKA) between January 2021 and February 2023. (3) Results: Patients registered on the platform who have undergone primary robotic TKA (rTKA) were considered. The mean age of registered patients is 68.6 years. The male (M)/female (F) ratio is 45.1%/54.9%. The patients interviewed were at an average distance of 485 days from the intervention, with a standard deviation of 187.5. The survey highlighted appreciation for the app and its features, but also limitations in its use and in its perception by the patients. All these data were evaluated according to the Wald principles and strategies to improve patient recruitment, enhance adherence, and create a comprehensive patient journey for optimized surgical experiences. (4) Conclusions: This patient care platform may have the potential to impact surgical experiences by increasing patient engagement, facilitating remote monitoring, and providing personalized care. There is a need to emphasize the importance of integrating the recruiting process, improving adherence strategies, and creating a comprehensive patient journey within the platform.

Since there is no consensus on the optimal perioperative analgesic method, the present article provides a brief and practical synthesis on current multimodal pre–postsurgery analgesia protocols for primary TKA (excluding intraoperative anesthetic techniques) reported especially in recent meta-analyses and reviews. The focus is not only on the traditional aims (pain scores and opioid sparing), but also the functional recovery and patient-reported outcomes. Multimodal analgesia (pre-emptive analgesia, local infiltration analgesia, peripheral nerve blocks, and specific systemic drugs) is considered the optimal regimen for perioperative pain management of TKA.

Background: Periprosthetic joint infection (PJI) represents a challenge following hip or knee arthroplasty, demanding immediate intervention to prevent implant failure and systemic issues. Bacterial biofilm development on orthopedic devices worsens PJI severity, resulting in recurrent hospitalizations and significant economic burdens. The objective of this retrospective cohort study is to evaluate the efficacy of this novel antiseptic solution, never previously evaluated in vivo, in managing early post-operative or acute hematogenous PJI following primary hip and knee joint replacements. Methods: The inclusion criteria consist of patients with total hip arthroplasty (THA) or knee arthroplasty diagnosed with acute PJI through preoperative and intraoperative investigations, in accordance with the MSIS ICM 2018 criteria. The minimum required follow-up was 12 months from the cessation of antibiotic therapy. This novel antiseptic lavage solution is composed of ethanol, acetic acid, sodium acetate, benzalkonium chloride and water. Data included demographic characteristics, diagnostic criteria, surgical techniques, post-operative treatment and follow-up outcomes. Results: A total of 39 patients treated with Debridement, Antibiotics Pearls and Retention of the Implant (DAPRI) procedures using this solution between May 2021 and April 2023 were analyzed. At a mean follow-up of 24.6 ± 6.4 months, infection recurrence-free survival rates were 87.2%, with no local allergic reactions or relevant systemic adverse effects detected. Persistent PJI necessitated two-stage revision surgery. Conclusions: This novel antiseptic lavage solution shows promise as an adjunctive tool in the treatment of PJI, demonstrating support in infection control while maintaining a favorable safety profile.

Knee arthroplasty, commonly performed to treat osteoarthritis, necessitates precise surgical techniques for optimal outcomes. The introduction of systems such as the Persona Knee System (Zimmer Biomet, Warsaw, IN, USA) has revolutionized knee arthroplasty, promising enhanced precision and better patient outcomes. This study investigates the application of robotic planning specifically in knee prosthetic surgeries, with a focus on Persona Knee System prostheses. We conducted a retrospective analysis of 300 patients who underwent knee arthroplasty using the Persona Knee System between January 2020 and November 2023, including demographic data, surgical parameters, and preoperative imaging. Robotic planning was employed to simulate surgical procedures. The planning process integrated preoperative imaging data from a specific program adopted for conducting digital preoperative planning, and statistical analyses were conducted to assess correlations between patient characteristics and surgical outcomes. Out of 300 patients, 85% presented with minor deformities, validating the feasibility of robotic planning. Robotic planning demonstrated precise prediction of optimal arthroplasty sizes and alignment, closely aligning with preoperative imaging data. This study highlights the potential benefits of robotic planning in knee arthroplasty surgeries, particularly in cases with minor deformities. By leveraging preoperative imaging data and integrating advanced robotic technologies, surgeons can improve precision and efficacy in knee arthroplasty. Moreover, robotic technology allows for a reduced level of constraint in the intraoperative choice between Posterior-Stabilized and Constrained Posterior-Stabilized liners compared with an imageless navigated procedure.