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.

This study was planned to reveal the relationship between coronal alignment parameters and patient-reported outcome measure (PROM) in the first year postoperatively after total knee arthroplasty (TKA). TKA for knee osteoarthritis between February 2019 and March 2023 were identified as potential candidates for the study. Patients who underwent TKA between February 2019 and March 2023 were retrospectively scanned. The exclusion criteria included ipsilateral total hip arthroplasty, history of surgery around the knee, preoperative tibial or femoral fracture, osteoarthritis due to rheumatic or traumatic causes, osteoarthritis due to valgus malalignment, bilateral TKA, and long-leg standing X-rays not taken with the appropriate acquisition technique. All patients were measured on full weight-bearing long leg X-rays taken 1 day before preoperatively and 1 year postoperatively. Hip and knee angle (HKA), lateral distal femoral angle (LDFA), and medial proximal tibial angle (MPTA) were measured in all patients. Preoperative and 1-year post-operative measurements were obtained for all patients. The relationship between changes in radiographic measurements and the Knee Injury and Osteoarthritis Outcome Score (KOOS), Visual Analog Score (VAS), and Oxford Knee Score was statistically evaluated. About 153 patients were included in the study. A total of 137 (89.5%) of these patients were female, and 16 (10.5%) were male. The mean age of the patients was 66.7 ± 5.12 years. Statistically significant improvement was found in all clinical scores in the postoperative period. A statistically significant negative correlation was found between preoperative HKA and preoperative Oxford score. The analysis of the relationship between changes in radiologic parameters and changes in clinical scores revealed no statistically significant correlation. Thus, there is no relationship between coronal plane parameters and postoperative first-year PROM in TKA patients.

Objective To quantify how sex, age, and region affect radiographic joint-line (JL) measurements and indices on standardized anteroposterior knee radiographs across ten countries, and to identify a demography-resistant metric set for reliable JL restoration. Methods Multicenter retrospective study of 3,000 AP knee radiographs obtained from ten countries. Standardized acquisition (SID 100 cm; AP, full extension, no rotation). Exclusions: prior peri-knee fracture/surgery, KL 3–4 OA, neurovascular deficit, septic arthritis, rheumatologic disease, BMI > 30, inadequate AP. Measurements: ATJL, FHJL, MEJL, LEJL, FW. Derived indices: literature-based ATJL/FW, FHJL/FW, MEJL/FW, LEJL/FW, JL1, JL2; newly defined JL-AF, JL-Combine, JL-Symmetry, JL-Ratio, JL3. Statistics: t-tests, one-/two-way ANOVA, multiple regression; effect sizes (Cohen’s d, η²); variability (CoV). α = 0. 05. Results Men showed higher FW (92. 83 ± 11. 15 vs 81. 38 ± 8. 54), ATJL (52. 16 ± 6. 31 vs 46. 07 ± 5. 46), FHJL (20. 74 ± 4. 05 vs 19. 13 ± 4. 04), MEJL (38. 22 ± 8. 96 vs 34. 62 ± 7. 67), and LEJL (35. 35 ± 8. 90 vs 32. 07 ± 7. 64); all p < 0. 001. With aging, FHJL, MEJL, and LEJL decreased (p < 0. 001); FW and ATJL showed no relevant age effect (p > 0. 05). Region strongly impacted all variables (largest η²: LEJL 0. 583, MEJL 0. 561, FW 0. 493). Among derived metrics, ATJL/FW (η² = 0. 016, CoV = 0. 228) and JL3 (η² = 0. 023, CoV = 0. 235) were the most stable across demographics. JL-AF (η² = 0. 036), JL-Combine (0. 028), and JL-Symmetry (0. 028) were low-dependency validators. FW-based JL1 (η² = 0. 899) and JL2 (0. 702) were demography-sensitive and unreliable as stand-alone predictors. Conclusion Basic anatomic distances are demography-dependent and poor single guides for JL restoration. A normalize-and-combine strategy—using ATJL/FW as the anchor and JL3 as the composite confirmatory index (optionally cross-checked by JL-AF/JL-Combine/JL-Symmetry)—provides robust, transferable radiographic estimation across centers. Avoid single-variable FW models (e. g., JL1) in routine planning. Larger, population-level datasets should support personalized thresholds.

Background: /aim: Traditional orthopedic disability assessment relies on complex guidelines and is prone to evaluator error and inefficiency. This study evaluated whether a retrieval-augmented generation (RAG) AI assistant (NotebookLM) improves accuracy and efficiency in guideline-based impairment rating compared with manual consultation. Materials and methods: In this prospective comparative study, 50 anonymized case-based clinical scenarios representing common musculoskeletal impairments were developed. Four orthopedic specialists evaluated all scenarios using two methods: manual guideline consultation and NotebookLM-assisted assessment restricted to the same regulation. The starting method was randomized, with each evaluator assessing 25 scenarios per method. The primary outcome was accuracy against an expert reference standard; the secondary outcome was time per scenario. Results: AI-assisted evaluation achieved higher accuracy than manual consultation (91% vs 68%; absolute difference, 23 percentage points, 95% CI 12.3 to 33.7; χ ² (1) = 14.849, p < .001). Generalized estimating equations confirmed an independent association between the AI-assisted method and correct ratings (adjusted OR 4.76, 95% CI 3.24–6.98, p < .001). Mean evaluation time decreased from 131 to 37 seconds per scenario (mean difference, 94.36 seconds, 95% CI 74.38 to 114.34; p < .001). Conclusion: A RAG-based AI assistant improved both accuracy and efficiency in orthopedic impairment rating under controlled conditions. These findings suggest meaningful clinical utility in structured, guideline-bound workflows, although further external validation in routine clinical practice is necessary before broader adoption can be recommended.