The primary aim of this study was to assess if traumatic triangular fibrocartilage complex (TFCC) tears can be treated successfully with immobilization alone. Our secondary aims were to identify clinical factors that may predict a poor prognosis. This was a retrospective analysis of 89 wrists in 88 patients between January 2015 and January 2019. All patients were managed conservatively initially with either a short-arm or above-elbow custom-moulded thermoplastic splint for six weeks. Outcome measures recorded included a visual analogue scale for pain, Patient-Rated Wrist Evaluation, Disabilities of the Arm, Shoulder and Hand score, and the modified Mayo Wrist Score (MMWS). Patients were considered to have had a poor outcome if their final MMWS was less than 80 points, or if they required eventual surgical intervention. Univariate and logistic regression analyses were used to identify independent predictors for a poor outcome.Aims
Methods
The functional ante-inclination (AI) of the cup after total hip arthroplasty (THA) is a key component in the combined sagittal index (CSI) to predict joint stability after THA. To accurately predict AI, we deducted a mathematic algorithm between the radiographic anteversion (RA), radiographic inclincation (RI), pelvic tilting (PT), and AI. The current study aims (1) to validate the mathematic algorithm; (2) to convert the AI limits in the CSI index (standing AI ≤ 45°, sitting AI ≥ 41°) into coronal functional safe zone (CFSZ) and explore the influences of the stand-to-sit pelvic motion (PM) and pelvic incidence (PI) on CFSZ; (3) to locate a universal cup orientation that always fulfill the AI criteria of CSI safe zone for all patients or subgroups of PM(PM ≤ 10°, 10° < PM ≤ 30°, and PM > 30°) and PI (PI≤ 41°, 41°< PI ≤ 62°, and PI >62°), respectively. A 3D printed phantom pelvic model was designed to simulate changing PT values. An acetabular cup was implanted with different RA, RI, and PT settings using robot assisted technique. We enrolled 100 consecutive patients who underwent robot assisted THA from April, 2019 to June, 2019 in our hospital. EOS images before THA and at 6-month follow-up were collected. AI angles were measured on the lateral view radiographs as the reference method. Mean absolute error (MAE), Bland-Altman analysis and linear regression were conducted to assess the accuracy of the AI algorithm for both the phantom and patient radiographic studies. The 100 patients were classified into three subgroups by PM and PI, respectively. Linear regression and ANOVA analysis were conducted to explore the relationship between the size of CFSZ, and PM and PI, respectively. Intersection of the CFSZ was conducted to identify if any universal cup orientation (RA, RI) existed for the CSI index.Introduction
Methods
