Aims Failure of irrigation and debridement (I&D) for prosthetic joint infection (PJI) is influenced by numerous host, surgical, and pathogen-related factors. We aimed to develop and validate a practical, easy-to-use tool based on machine learning that may accurately predict outcome following I&D surgery taking into account the influence of numerous factors. Methods This was an international, multicentre retrospective study of 1,174 revision total hip (THA) and knee arthroplasties (TKA) undergoing I&D for PJI between January 2005 and December 2017. PJI was defined using the Musculoskeletal Infection Society (MSIS) criteria. A total of 52 variables including demographics, comorbidities, and clinical and laboratory findings were evaluated using random forest machine learning analysis. The algorithm was then verified through cross-validation. Results Of the 1,174 patients that were included in the study, 405 patients (34.5%) failed treatment. Using random forest analysis, an algorithm that provides the probability for failure for each specific patient was created. By order of importance, the ten most important variables associated with failure of I&D were serum CRP levels, positive blood cultures, indication for index arthroplasty other than osteoarthritis, not exchanging the modular components, use of immunosuppressive medication, late acute (haematogenous) infections, methicillin-resistant Staphylococcus aureus infection, overlying skin infection, polymicrobial infection, and older age. The algorithm had good discriminatory capability (area under the curve = 0.74). Cross-validation showed similar probabilities comparing predicted and observed failures indicating high accuracy of the model. Conclusion This is the first study in the orthopaedic literature to use machine learning as a tool for predicting outcomes following I&D surgery. The developed algorithm provides the medical profession with a tool that can be employed in clinical decision-making and improve patient care. Future studies should aid in further validating this tool on additional cohorts. Cite this article: Bone Joint J 2020;102-B(7 Supple B):11–19.

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Background:A substantial number of orthopaedic surgeons apply for sports medicine fellowships after residency completion. The Internet is one of the most important resources applicants use to obtain information about fellowship programs, with the program website serving as one of the most influential sources. The American Orthopaedic Society for Sports Medicine (AOSSM), San Francisco Match (SFM), and Arthroscopy Association of North America (AANA) maintain databases of orthopaedic sports medicine fellowship programs. A 2013 study evaluated the content and accessibility of the websites for accredited orthopaedic sports medicine fellowships.Purpose:To reassess these websites based on the same parameters and compare the results with those of the study published in 2013 to determine whether any improvement has been made in fellowship website content or accessibility.Study Design:Cross-sectional study.Methods:We reviewed all existing websites for the 95 accredited orthopaedic sports medicine fellowships included in the AOSSM, SFM, and AANA databases. Accessibility of the websites was determined by performing a Google search for each program. A total of 89 sports fellowship websites were evaluated for overall content. Websites for the remaining 6 programs could not be identified, so they were not included in content assessment.Results:Of the 95 accredited sports medicine fellowships, 49 (52%) provided links in the AOSSM database, 89 (94%) in the SFM database, and 24 (25%) in the AANA database. Of the 89 websites, 89 (100%) provided a description of the program, 62 (70%) provided selection process information, and 40 (45%) provided a link to the SFM website. Two searches through Google were able to identify links to 88% and 92% of all accredited programs.Conclusion:The majority of accredited orthopaedic sports medicine fellowship programs fail to utilize the Internet to its full potential as a resource to provide applicants with detailed information about the program, which could help residents in the selection and ranking process. Orthopaedic sports medicine fellowship websites that are easily accessible through the AOSSM, SFM, AANA, or Google and that provide all relevant information for applicants would simplify the process of deciding where to apply, interview, and ultimately how to rank orthopaedic sports medicine fellowship programs for the Orthopaedic Sports Medicine Fellowship Match.

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Purpose: To report changes in outcomes for these 3 treatment options for meniscal root tears. Methods: We systematically searched databases including PubMed, SCOPUS, and ScienceDirect for relevant articles. Criteria from the National Heart, Lung, and Blood Institute was used for a quality assessment of the included studies. A meta-analysis was performed to analyze changes in outcomes for meniscal repair. Results: Nineteen studies, 12 level III and 7 level IV, were included in this systematic review, with a total of 1086 patients. Conversion to total knee arthroplasty (TKA) following partial meniscectomy ranged from 11% to 54%, 31% to 35% for nonoperative, conservative treatment, and 0% to 1% for meniscal repair. Studies comparing repair with either meniscectomy or conservative treatment found greater improvement and slower progression of KellgreneLawrence grade with meniscal repair. A meta-analysis of the studies included in the systematic review using forest plots showed repair to have the greatest mean difference for functional outcomes (International Knee Documentation Committee and Lysholm Activity Scale) and the lowest change in follow-up joint space. Conclusions: In patients who experience meniscal root tears, meniscal repair may provide the greatest improvement in function and lowest risk of conversion to TKA when compared with partial meniscectomy or conservative methods. Partial meniscectomy appears to provide no benefit over conservative treatment, placing patients at a high risk of requiring TKA in the near future. However, future high-quality studiesdboth comparative studies and randomized trialsdare needed to draw further conclusions and better impact treatment decision-making. Level of Evidence: Level IV, systematic review of level III and level IV evidence