Aims. To assess if older symptomatic children with club foot deformity differ in perceived disability and foot function during gait, depending on initial treatment with Ponseti or surgery, compared to a control group. Second aim was to investigate correlations between foot function during gait and perceived disability in this population. Methods. In all, 73 children with idiopathic club foot were included: 31 children treated with the Ponseti method (mean age 8.3 years; 24 male; 20 bilaterally affected, 13 left and 18 right sides analyzed), and 42 treated with primary surgical correction (mean age 11.6 years; 28 male; 23 bilaterally affected, 18 left and 24 right sides analyzed). Foot function data was collected during walking gait and included Oxford Foot Model kinematics (Foot Profile Score and the range of movement and average position of each part of the foot) and plantar pressure (peak pressure in five areas of the foot). Oxford Ankle Foot Questionnaire, Disease Specific Index for club foot, Paediatric Quality of Life Inventory 4.0 were also collected. The gait data were compared between the two club foot groups and compared to control data. The gait data were also correlated with the data extracted from the questionnaires. Results. Our findings suggest that symptomatic children with club foot deformity present with similar degrees of gait deviations and perceived disability regardless of whether they had previously been treated with the Ponseti Method or surgery. The presence of sagittal and coronal plane hindfoot deformity and coronal plane forefoot deformity were associated with higher levels of perceived disability, regardless of their initial treatment. Conclusion. This is the first paper to compare outcomes between Ponseti and surgery in a symptomatic older club foot population seeking further treatment. It is also the first paper to correlate foot function during gait and perceived disability to establish a link between deformity and subjective outcomes. Cite this article: Bone Joint Open 2020;1-7:384–391

Aims. The use of technology to assess balance and alignment during total knee surgery can provide an overload of numerical data to the surgeon. Meanwhile, this quantification holds the potential to clarify and guide the surgeon through the surgical decision process when selecting the appropriate bone recut or soft tissue adjustment when balancing a total knee. Therefore, this paper evaluates the potential of deploying supervised machine learning (ML) models to select a surgical correction based on patient-specific intra-operative assessments. Methods. Based on a clinical series of 479 primary total knees and 1,305 associated surgical decisions, various ML models were developed. These models identified the indicated surgical decision based on available, intra-operative alignment, and tibiofemoral load data. Results. With an associated area under the receiver-operator curve ranging between 0.75 and 0.98, the optimized ML models resulted in good to excellent predictions. The best performing model used a random forest approach while considering both alignment and intra-articular load readings. Conclusion. The presented model has the potential to make experience available to surgeons adopting new technology, bringing expert opinion in their operating theatre, but also provides insight in the surgical decision process. More specifically, these promising outcomes indicated the relevance of considering the overall limb alignment in the coronal and sagittal plane to identify the appropriate surgical decision

Aims

The aticularis genu (AG) is the least substantial and deepest muscle of the anterior compartment of the thigh and of uncertain significance. The aim of the study was to describe the anatomy of AG in cadaveric specimens, to characterize the relevance of AG in pathological distal femur specimens, and to correlate the anatomy and pathology with preoperative magnetic resonance imaging (MRI) of AG.