Purpose: To identify gender differences in (1) the coronal alignment of functional knee phenotypes and (2) the JLCA (joint line convergence angle) in relation to the phenotype classification.Methods: This study is a retrospective data analysis, including 12,099 osteoarthritic knee computed tomography (5025 male, 7074 female) analysed by Medacta software for hip‐knee‐ankle angle (HKA), femoral mechanical angle (FMA), tibial mechanical angle (TMA) and JLCA. The data were grouped into genders and combined according to the Functional Knee Phenotypes Classification.Results: Out of 127 phenotypes for males and 131 for females, 17 common phenotypes were reported. The commonest four were similar for both genders with VARHKA177° NEUFMA93° NEUTMA87° (9.8% males, 9.50% females), followed by VARHKA174° NEUFMA93°VARTMA84° (7.1%) and VARHKA174°VARFMA90° NEUTMA87° (7.0%) for males and VARHKA174° NEUFMA93° NEUTMA87° (6.1%), VARHKA174° NEUFMA93°VARTMA84° (5.1%) for females. The commonest FMA and TMA (91.5° to 94.5° and 85.5° to 88.5°, respectively) were the same for both genders, however, the rest of the male population observed greater femoral varus than the female population (p < 0.001). JLCA values ranged from −28.4° to 8.2° in the overall study population. Males and females had a mean JLCA of −2.96° (±2.6° SD) and −2.66° (±2.8°7 SD), respectively, p < 0.001.Conclusions: Gender differences exist within the osteoarthritic knee phenotype. The male varus phenotype is influenced by FMA, while TMA values are similar across genders. JLCA variations show similarities to both TMA and FMA, suggesting JLCA is influenced by bone morphology more than by gender. These differences inform surgical decision‐making for the personalised approach to the primary TKA.Level of Evidence: Level III.

Robotic‐assisted total knee arthroplasty (RTKA) has gained widespread acceptance due to its demonstrated ability to improve surgical accuracy compared to conventional total knee arthroplasty (CTKA). While the precise impact of RTKA on postoperative patient‐reported outcome measures (PROMs) remains inconclusive, the increased accuracy in alignment and joint kinematics suggests potential improvements in patient satisfaction and functional outcomes. Two primary RTKA systems exist: image‐based, which uses preoperative CT scans for detailed 3D modeling, and image‐less, which relies on intra‐operative digitization of anatomical landmarks. Both systems aim to achieve accurate implant placement and soft‐tissue balancing, yet they differ in methodology and reliance on preoperative data.Despite RTKA's theoretical advantages, there is ongoing debate about whether accuracy alone is sufficient to achieve optimal postoperative outcomes, particularly concerning joint kinematics and alignment strategies. Literature reveals no significant difference in coronal plane alignment between image‐based and image‐less systems, though image‐less systems may be more prone to varus errors due to the reliance on intra‐articular landmarks. Additionally, image‐free systems may face challenges in replicating native knee anatomy, especially in the sagittal plane, leading to potential limitations in achieving ideal tibial slope reconstruction.The future of RTKA may lie in refining implant positioning strategies that minimize postoperative alterations to pre‐arthritic knee kinematics, particularly with standardized off‐the‐shelf implants. As robotic technology evolves, there is potential to enhance surgical outcomes by combining accuracy with personalized alignment approaches that better address individual patient anatomy. Further research is needed to assess the long‐term clinical benefits of RTKA and its capacity to improve patient‐specific functional outcomes.Level of evidence: level 5

Background: Robotic-assisted unicompartmental arthroplasty (rUKA) is gradually gaining more popularity than its conventional counterpart (cUKA). Current studies are highly heterogenic in terms of methodology and the reported results; therefore, establishing the optimal recommendation for patients becomes less straightforward. For this reason, this meta-analysis aims to provide an up-to-date evidence-based analysis on current evidence regarding clinical outcomes and complication rates following rUKA and cUKA. Methods: A meta-analysis was conducted following PRISMA guidelines. Five databases were searched, PubMed via MEDLINE, Epistemonikos, Cochrane Library, Web of Science, and Scopus. The relevant inclusion criteria were as follows: comparative clinical studies in which medial rUKA was compared to medial cUKA (prospective or retrospective designs), (2) human studies, (3) meta-analyses for cross-referencing, and (4) English language. The relevant extracted data were patient demographics, patient-reported outcome measures (PROMs), range of motion, and complications. A random-effects meta-analysis and subgroup analysis were conducted. The results include mean differences (MDs) and odds ratios (ORs), along with 95% confidence intervals (CIs) for continuous and binary variables, respectively. Results: rUKA showed a higher overall FJS-12 score compared to cUKA, with MD = 6.02 (95%CI: −0.07 to 12.1), p = 0.05. At 6 months postoperatively, the MD increased to 10.31 (95%CI: 5.14 to 15.49), p < 0.01. At a minimum 36-month follow-up, cUKA had a higher all-cause revision rate, with OR = 3.31 (95%CI: 1.25 to 8.8), p = 0.02, and at a minimum 60-month follow-up, a higher aseptic loosening rate, with OR = 3.86 (95%CI: 1.51 to 9.91), p < 0.01, compared to rUKA. Conclusions: rUKA provides better FJS-12 results compared to cUKA, as well as lower all-cause revision and aseptic loosening rates at 36- and 60-month follow-up, respectively. However, long-term follow-up is still pending.