Background/Objectives: In patients with varus knee osteoarthritis, compensatory changes occur in the foot and ankle joints to compensate for the varus deformity of the knee. The aim of the study was to investigate the changes in the ankle of patients whose knee alignment was corrected with total knee arthroplasty (TKA) and to explore the clinical implications of these findings. Methods: In this retrospective observational study, we analyzed 204 knees of 179 patients who had regular follow-ups out of 431 patients who underwent TKA for varus knee osteoarthritis between January 2019 and July 2021. Patient demographics, body mass index, follow-up time, and radiographs were studied. The hip–knee–ankle (HKA) angle, joint line convergence angle (JLCA), talar tilt (TT) angle, ground talar dome (GT) angle, ground tibia plafond (GP) angle, and the American Orthopaedic Foot & Ankle Society (AOFAS) score were assessed preoperatively and at the last follow-up. Results: A total of 204 knees of 179 patients with a mean follow-up time of 32.50 ± 6.68 months were evaluated. It was found that the change in the HKA had a positive effect on the AOFAS score and a negative effect on the TT, GT, and GP angles. While the clinical score improved in 82 patients, it worsened in 8 patients. The age difference between the groups whose AOFAS score improved and worsened was statistically significant. Conclusions: The correction of the varus malalignment in the knee was shown to also improve the compensatory valgus in the foot and ankle over the mid-term, with a statistically significant improvement in the patients’ clinical ankle scores.

Background: Rapid and accurate fracture detection is critical in emergency departments (EDs), where high patient volume and time pressure increase the risk of diagnostic error, particularly in radiographic interpretation. Multimodal large language models (LLMs) with image-recognition capability have recently emerged as general-purpose tools for clinical decision support, but their diagnostic performance within routine emergency department imaging workflows in orthopedic trauma remains unclear. Methods: In this retrospective diagnostic accuracy study, we included 1136 consecutive patients referred from the ED to orthopedics between 1 January and 1 June 2025 at a single tertiary center. Given the single-center, retrospective design, the findings should be interpreted as hypothesis-generating and may not be fully generalizable to other institutions. Emergency radiographs and clinical data were processed by a multimodal LLM (2025 version) via an official API using a standardized, deterministic prompt. The model’s outputs (“Fracture present”, “No fracture”, or “Uncertain”) were compared with final diagnoses established by blinded orthopedic specialists, which served as the reference standard. Diagnostic agreement was analyzed using Cohen’s kappa (κ), sensitivity, specificity, accuracy, and 95% confidence intervals (CIs). False-negative (FN) cases were defined as instances where the LLM reported “no acute fracture” but the specialist identified a fracture. The evaluated system is a general-purpose multimodal LLM and was not trained specifically on orthopedic radiographs. Results: Overall, the LLM showed good diagnostic agreement with orthopedic specialists, with concordant results in 808 of 1136 patients (71.1%; κ = 0.634; 95% CI: 68.4–73.7). The model achieved balanced performance with sensitivity of 76.9% and specificity of 66.8%. The highest agreement was observed in knee trauma (91.7%), followed by wrist (78.8%) and hand (69.6%). False-negative cases accounted for 184 patients (16.2% of the total cohort), representing 32.4% of all LLM-negative assessments. Most FN fractures were non-displaced (82.6%), and 17.4% of FN cases required surgical treatment. Ankle and foot regions showed the highest FN rates (30.4% and 17.4%, respectively), reflecting the anatomical and radiographic complexity of these areas. Positive predictive value (PPV) and negative predictive value (NPV) were 69.4% and 74.5%, respectively, with likelihood ratios indicating moderate shifts in post-test probability. Conclusions: In an emergency department-to-orthopedics consultation cohort reflecting routine clinical workflow, a multimodal LLM demonstrated moderate-to-good diagnostic agreement with orthopedic specialists, broadly within the range reported in prior fracture-detection AI studies; however, these comparisons are indirect because model architectures, training strategies, datasets, and endpoints differ across studies. However, its limited ability to detect non-displaced fractures—especially in anatomically complex regions like the ankle and foot—carries direct patient safety implications and confirms that specialist review remains indispensable. At present, such models may be explored as hypothesis-generating triage or decision-support tools, with mandatory specialist confirmation, rather than as standalone diagnostic systems. Prospective, multi-center studies using high-resolution imaging and anatomically optimized algorithms are needed before routine clinical adoption in emergency care.

Background/Objectives: Periprosthetic joint infection (PJI) is a severe complication following both total knee arthroplasty (TKA) and unicompartmental knee arthroplasty (UKA). While the microbiological profile of TKA PJI has been well characterized, limited data exist regarding UKA PJIs. This study aimed to compare the causative microorganisms and surgical treatment outcomes in PJI cases following UKA and TKA. Methods: This retrospective cohort study included 82 patients (71 TKA and 11 UKA) who underwent surgical treatment for PJI between January 2017 and May 2024. PJI was diagnosed based on the Musculoskeletal Infection Society (MSIS) criteria. Treatment strategies included debridement, antibiotics, and implant retention (DAIR) or two-stage revision arthroplasty. Microbiological data were extracted from intraoperative cultures. Fisher’s exact test and the Mann–Whitney U test were used for statistical comparisons. Results: Gram-positive organisms, primarily Staphylococcus aureus and coagulase-negative staphylococci, were isolated in all UKA PJIs. In contrast, the TKA group demonstrated greater microbial diversity, including Gram-negative bacilli, polymicrobial infections, and a higher rate of culture-negative cases (33.8% vs. 18.2%). DAIR was performed more frequently in UKA cases (72.7% vs. 28.2%, p = 0.002). Recurrence rates following DAIR were similar in both groups (12.5% in UKA, 20.0% in TKA, p = 1.000). Two-stage revision resulted in no recurrence in UKA and a 9.8% recurrence rate in TKA patients. Conclusions: UKA PJIs appear to be microbiologically less complex than TKA PJI cases, with Gram-positive organisms predominating. Despite these differences, the outcomes of surgical treatment—both DAIR and two-stage revision—were comparable between groups. Standard PJI treatment principles may be applicable to both arthroplasty types; however, larger prospective studies are needed to confirm these findings.