In trauma surgery, the development of biomaterial-associated infections (BAI) is one of the most common complications affecting trauma patients, requiring prolonged hospitalization and the intensive use of antibiotics. Following the attachment of bacteria on the surface of the biomaterial, the biofilm-forming bacteria could initiate a chronic implant-related infection. Despite the use of conventional local and systemic antibiotic therapies, persistent biofilms involve various resistance mechanisms that contribute to therapeutic failures. The development of In the first model, biofilms were formed following an incubation period (up to 7 days) in the CDC Biofilm Reactor (CBR, BioSurface Technologies). Then, after implantation of the pre-incubated K-wire in the larvae, rifampicin (80 mg/kg) was injected and the survival of the larvae was monitored. In the second model, biofilm formation was achieved after an incubation period (up to 7 days) inside the larvae and then, after removing the K-wires from the host, Aim
Method
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
