[Influencing fracture healing by specific osteoporosis medications].

Background: Osteoporosis is a widespread disease defined by a reduction in bone mass and structure, thereby increasing the risk of fragility fractures. Treatment typically involves specific medications, which either inhibit bone resorption (antiresorptive) or stimulate bone formation (anabolic) and may potentially influence the healing of osteoporotic fractures. On the other hand, metabolic disorders, immune system dysfunctions or circulatory problems can impair fracture healing.

[Secondary fracture prevention/Update osteoporosis guidelines 2023 of the Umbrella Organization Osteology].

The S3 guidelines on the prophylaxis, diagnostics and treatment of osteoporosis 2023 were completely revised and updated between 2021 and 2023 in accordance with the Association of the Scientific Medical Societies of Germany (AWMF) regulations. The guideline committee consisted of delegates from the 20 specialist societies of the Umbrella Organization Osteology (Dachverband Osteologie, DVO) as well as delegates from the German Society of General Medicine and Family Medicine (DEGAM), the German Society for Nephrology (DGfN) and the Federal Self-help Association for Osteoporosis (BfO).The guidelines focus on preventive measures, diagnostic procedures and treatment approaches for osteoporosis in men aged 50 years and over and postmenopausal women.

Development of a Machine Learning-Based Model to Predict Timed-Up-and-Go Test in Older Adults.

Introduction: The measurement of physical frailty in elderly patients with orthopedic impairments remains a challenge due to its subjectivity, unreliability, time-consuming nature, and limited applicability to uninjured individuals. Our study aims to address this gap by developing objective, multifactorial machine models that do not rely on mobility data and subsequently validating their predictive capacity concerning the Timed-up-and-Go test (TUG test) in orthogeriatric patients.

Methods: We utilized 67 multifactorial non-mobility parameters in a pre-processing phase, employing six feature selection algorithms.