Frailty and resilience in an older population. The role of resilience during rehabilitation after orthopedic surgery in geriatric patients with multiple comorbidities.

Hip fracture is common in the elderly and it is usually associated with comorbidities and physiological changes which may have an impact on functioning and quality of life. The concept of resilience may explain why this impact varies among patients. The aim of this open, prospective cohort study was to explore the relationships between resilience, frailty and quality of life in orthopedic rehabilitation patients, and also to assess whether these factors might affect rehabilitation outcome. Eighty-one patients, older than 60 years, underwent a multidisciplinary assessment at the beginning and at the end of the rehabilitation period following orthopedic surgery to the lower limb. The assessments were performed using the Resilience Scale, the Multidimensional Prognostic Index (as a measure of frailty), the WHO Quality of Life-BRIEF, the Geriatric Depression Scale, and the Functional Independence Frailty and resilience in an older population. The role of resilience during rehabilitation after orthopedic surgery in geriatric patients with multiple comorbidities Measure (as a measure of the rehabilitation outcome). A negative correlation between disability and resilience emerged and this association interacted with frailty level. We also found that resilience and quality of life are positive predictors of functional status at discharge.

From Curves to Trees: A Tree-like Shapes Distance Using the Elastic Shape Analysis Framework.

Trees are a special type of graph that can be found in various disciplines. In the field of biomedical imaging, trees have been widely studied as they can be used to describe structures such as neurons, blood vessels and lung airways. It has been shown that the morphological characteristics of these structures can provide information on their function aiding the characterization of pathological states. Therefore, it is important to develop methods that analyze their shape and quantify differences between their structures. In this paper, we present a method for the comparison of tree-like shapes that takes into account both topological and geometrical information. This method, which is based on the Elastic Shape Analysis Framework, also computes the mean shape of a population of trees. As a first application, we have considered the comparison of axon morphology. The performance of our method has been evaluated on two sets of images. For the first set of images, we considered four different populations of neurons from different animals and brain sections from the NeuroMorpho.org open database. The second set was composed of a database of 3D confocal microscopy images of three populations of axonal trees (normal and two types of mutations) of the same type of neurons. We have calculated the inter and intra class distances between the populations and embedded the distance in a classification scheme. We have compared the performance of our method against three other state of the art algorithms, and results showed that the proposed method better distinguishes between the populations. Furthermore, we present the mean shape of each population. These shapes present a more complete picture of the morphological characteristics of each population, compared to the average value of certain predefined features.