Archives of orthopaedic and trauma surgery
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Arch Orthop Trauma Surg · Jan 2025
Can robotic arm-assisted total knee arthroplasty be applied to valgus deformity.
Total knee arthroplasty (TKA) in valgus knees is challenging. Optimal ligament balance, implant neutral or moderate valgus alignment are crucial but conventional instrumentations usually lead to outliers. Robotic arm assisted TKA (RATKA) advantages could answer this challenge. Objectives were to assess RATKA frontal alignment accuracy for valgus knees, rotational femoral component reliability, revision surgery rate and functional outcomes for this population. ⋯ RATKA can be applicable in valgus knee, offering high precision in component positioning with very few outliers. It also facilitates component rotation positioning, providing excellent functional results and ROM.
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Arch Orthop Trauma Surg · Jan 2025
Return to work following traumatic hip dislocation: a prognostic outcome study.
Traumatic hip dislocations are associated with high morbidity and overall limitations of daily living activities. Residual disability inhibits returning to work after severe injuries and minimizes financial independence and social involvement, which are both related to well-being and good health. The aim of this study was to analyze epidemiological and socioeconomic status following traumatic hip dislocations to identify predictors for return to work. ⋯ Traumatic hip dislocations are associated with high rates of work-related injury and unsatisfactory low rates of return to previous work. Younger age, lower BMI, higher Patient reported outcome measures and lower pain levels may predict a successful return to previous job and a reduced risk of reduction in earning capacity. Understanding the predictive factors is crucial to identify patients at risk of not returning to work and to develop strategies that may help improve their chances of successfully returning to their previous employment.
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Arch Orthop Trauma Surg · Jan 2025
Machine learning to predict periprosthetic joint infections following primary total hip arthroplasty using a national database.
Periprosthetic joint infection (PJI) following total hip arthroplasty (THA) remains a devastating complication for patients and surgeons. Given the implications of these infections and the current paucity of risk calculators utilizing machine learning (ML), this study aimed to develop an ML algorithm that could accurately identify risk factors for developing a PJI following primary THA using a national database. ⋯ This study developed a highly specific ML model that could predict patient-specific PJI development following primary THA. Considering the feature importance of the top predictors of infection, surgeons should counsel at-risk patients to optimize resource utilization and potentially improve surgical outcomes.