In order to release the contracture band completely without damaging normal tissues (such as the sciatic nerve) in the surgical treatment of gluteal muscle contracture (GMC), we tried to display the relationship between normal tissue and contracture bands by magnetic resonance neurography (MRN) images, and to predesign a minimally invasive surgery based on the MRN images in advance. A total of 30 patients (60 hips) were included in this study. MRN scans of the pelvis were performed before surgery. The contracture band shape and external rotation angle (ERA) of the proximal femur were also analyzed. Then, the minimally invasive GMC releasing surgery was performed based on the images and measurements, and during the operation, incision lengths, surgery duration, intraoperative bleeding, and complications were recorded; the time of the first postoperative off-bed activity was also recorded. Furthermore, the patients’ clinical functions were evaluated by means of Hip Outcome Score (HOS) and Ye et al’s objective assessments, respectively.Aims
Methods
Although low-intensity pulsed ultrasound (LIPUS) combined with disinfectants has been shown to effectively eliminate portions of biofilm in vitro, its efficacy in vivo remains uncertain. Our objective was to assess the antibiofilm potential and safety of LIPUS combined with 0.35% povidone-iodine (PI) in a rat debridement, antibiotics, and implant retention (DAIR) model of periprosthetic joint infection (PJI). A total of 56 male Sprague-Dawley rats were established in acute PJI models by intra-articular injection of bacteria. The rats were divided into four groups: a Control group, a 0.35% PI group, a LIPUS and saline group, and a LIPUS and 0.35% PI group. All rats underwent DAIR, except for Control, which underwent a sham procedure. General status, serum biochemical markers, weightbearing analysis, radiographs, micro-CT analysis, scanning electron microscopy of the prostheses, microbiological analysis, macroscope, and histopathology evaluation were performed 14 days after DAIR.Aims
Methods
