Archives of orthopaedic and trauma surgery
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Arch Orthop Trauma Surg · Dec 2023
C-reactive protein of ≥ 20 mg/L and ultrasound finding of an effusion ≥ 7 mm has a high specificity and sensitivity in diagnosing paediatric hip septic arthritis.
Differentiating septic arthritis (SA) from transient synovitis (TS) in children remains a diagnostic challenge. Several algorithms have been developed to diagnose SA including Kocher's criteria and its subsequent modifications, but reports show variable efficacy. This study aims to examine the diagnostic utility of a novel method only using C-reactive protein (CRP) and ultrasound (US) findings of effusion in differentiating SA from TS, determine the optimal values for these predictors and validate this method against existing clinical predictors. ⋯ Our study showed that the novel method using CRP (≥ 20 mg/L) and US finding of effusion (≥ 7 mm) has a high specificity (97%) and sensitivity (71%) in diagnosing SA.
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Arch Orthop Trauma Surg · Dec 2023
The AMADEUS score is not a sufficient predictor for functional outcome after autologous chondrocyte implantation (ACI) of the knee: data from the German Cartilage Registry (KnorpelRegister DGOU).
The AMADEUS (Area Measurement And DEpth and Underlying Structures) score has advanced to a commonly used tool for MRI-based chondral defect severity grading prior to cartilage knee surgery. It was the intention of this study to assess the AMADEUS for a potential correlation with clinical data by patient-reported outcome measures (PROMs). ⋯ Study results suggest no correlative capacity of the AMADEUS with routinely used PROMs in patients undergoing ACI. Therefore, radiographically assessed cartilage defect characteristics poorly translate to pre- and postoperative patient-reported outcome data.
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Arch Orthop Trauma Surg · Dec 2023
Comparison of both lower leg bone mineral density in single limb knee osteoarthritis patients.
The relationship between knee osteoarthritis (OA), bone mineral density (BMD), and alignment has not yet been clarified. This study aimed to investigate the relationship between the two limbs in patients with single-limb knee OA. ⋯ The femoral neck BMD of the leg on the side with knee OA was lower than that on the side without OA. However, the alignment difference between the legs did not affect BMD. BMD was lowered because of OA and not because of alignment.
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Arch Orthop Trauma Surg · Dec 2023
Does the geriatric nutritional risk index predict complication rates and implant survivorship in revision total joint arthroplasty?
Malnutrition is associated with poorer outcomes after revision total joint arthroplasty (rTJA), though no universal metric for assessing malnutrition in rTJA patients has been reported. This study sought to determine if malnutrition as defined by the Geriatric Nutritional Risk Index (GNRI) can independently predict short-term complication rates and re-revision risk in patients undergoing rTJA. ⋯ Moderate and severe malnutrition, as defined by GNRI, independently predicted higher complication and revision rates in rTJA patients. This suggests that the GNRI may serve as an effective screening tool for nutritional status in patients undergoing rTJA.
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Arch Orthop Trauma Surg · Dec 2023
Can machine learning models predict prolonged length of hospital stay following primary total knee arthroplasty based on a national patient cohort data?
The total length of stay (LOS) is one of the biggest determinators of overall care costs associated with total knee arthroplasty (TKA). An accurate prediction of LOS could aid in optimizing discharge strategy for patients in need and diminishing healthcare expenditure. The aim of this study was to predict LOS following TKA using machine learning models developed on a national-scale patient cohort. ⋯ ANN demonstrated modest discrimination capacity and excellent performance in calibration and clinical utility for the prediction of prolonged LOS following TKA. Clinical application of the machine learning models has the potential to improve care coordination and discharge planning for patients at high risk of extended hospitalization after surgery. Incorporating more relevant patient factors may further increase the models' prediction strength.