Front Bioeng Biotechnol
November 2024
Bone has the capability to adapt its density in response to mechanical stimuli through a process known as bone remodeling, which has been simulated using various algorithms in several studies, with Strain Energy Density (SED) being a commonly used driving parameter. A spatial influence function has been introduced in addition to the remodeling algorithm, which accounts for the influence of neighboring regions on local mechanical stimuli, thereby reducing artificial mesh dependency and mimicking cellular communication in bone. However, no study has implemented the SED-driven algorithm with spatial influence function on a macroscopic 3D bone structure, and there is no physiological explanation on the value used in remodeling parameter.
View Article and Find Full Text PDFBackground: Direct skeletal fixation, a surgical technique enabling the attachment of an external prosthesis directly to the bone through a percutaneous implant, offers an enticing solution for patients with lower limb amputations facing socket-related issues. However, understanding of its impact on musculoskeletal function remains limited.
Methods: This study compares pre- and 1-year post-osseointegration surgery outcomes, focusing on patient-reported measures and musculoskeletal system function during level-ground walking.
Introduction: Dismounted blast has the potential to cause life-threatening injuries to multiple simultaneous casualties, including injury to the cervical spine (c-spine). Spinal immobilisation can be costly in terms of time and personnel required to apply and sustain it. C-spine 'clearing' tools frequently do not apply to the blast-injured casualty, so clinical judgement must be used to determine those requiring c-spine immobilisation.
View Article and Find Full Text PDFObjective: We aimed to describe the incidence, pathogens, and antimicrobial susceptibility of central line-associated bloodstream infections (CLABSI) in adult intensive care units (ICU).
Design: State surveillance data from 2011 to 2022 were analyzed to identify patient and device days and CLABSI events. Pathogen data were analyzed to determine the most common organisms and patterns of antimicrobial resistance grouped into 3-year time epochs.