Frailty is a geriatric multidimensional syndrome characterized by a loss of physiologic reserves and disproportionate vulnerability to external stressors and associated with increased risk of multiple negative health outcomes. Since frailty can be prevented, controlled, and even reverted in its early stages, identifying the main factors involved in its development is crucial to implement preventive and/or restorative interventions. The aim of this study was to assess the impact of a broad range of parameters, including host factors, lifestyle, diet, and environmental and occupational conditions, on the development of frailty in later life. A cross-sectional study was conducted on 221,896 individuals aged 60 and over classified as non-frail (119,332, 53.8%), pre-frail (93,180, 42.0%), and frail (9384, 4.2%) according to the frailty phenotype. Using principal component analysis and machine learning to streamline the data, significant associations were found between frailty risk and air quality, diet, smoking, working conditions, and heavy alcohol consumption. Early-life factors, including breastfed as a baby and maternal smoking around birth, also emerged as predictors of frailty, which was further characterized by clinical indicators like polypharmacy, levels of C-reactive protein and other biomarkers of inflammageing. This study provided robust and original evidence on the association between a large battery of potential risk factors, from early to later stages of life, and the occurrence of frailty in older age. These results will contribute to the development of effective prevention strategies and facilitate the early detection of individuals at high risk of developing frailty.

Background: Clinical assessment of balance and postural disorders is usually carried out through several common practices including tests such as the Subjective Visual Vertical (SVV) and Limit of Stability (LOS). Nowadays, several cutting-edge technologies have been proposed as supporting tools for stability evaluation. Extended Reality (XR) emerges as a powerful instrument. This proof-of-concept study aims to assess the feasibility and potential clinical utility of a novel MR-based framework integrating HoloLens 2, Wii Balance Board, and Azure Kinect for multimodal balance assessment. An innovative test is also introduced, the Innovative Dynamic Balance Assessment (IDBA), alongside an MR version of the SVV test and the evaluation of their performance in a cohort of healthy individuals. Results: All participants reported SVV deviations within the clinically accepted ±2° range. The IDBA results revealed consistent sway and angular profiles across participants, with statistically significant differences in posture control between opposing target directions. System outputs were consistent, with integrated parameters offering a comprehensive representation of postural strategies. Conclusions: The MR-based framework successfully delivers integrated, multimodal measurements of postural control in healthy individuals. These findings support its potential use in future clinical applications for balance disorder assessment and personalized rehabilitation.

Background: Occupational therapy (OT) is an essential component of patient care, and it is especially beneficial if focused on meaningful activities. For ataxic patients, traditional procedures are currently the most efficient, although without specific guidelines and suggestions for virtual reality integration. In this context, this study proposes Hybrid Smart Rehabilitation (HSR) based on mixed reality (MR) as an aid in overcoming limitations of the traditional OT procedures. Methods: MR-HSR is designed specifically for ataxic patients and developed in Unity with the Holographic Remoting setting for run-time intervention on the scene. The subject reaches a book and grabs it with their hand inside a holographic guide with audio-visive feedback. Hand trajectories acquired from eight ataxic patients and eight healthy subjects were compared and new variables were analyzed to evaluate the performance. The Trust in Automation questionnaire was submitted to assess the opinion of the patients. Results: Patients confirmed their trust in the developer and in the improvement that this system can bring to their rehabilitation. The “total time” and “sway area” of the trajectory were statistically significant and, together with the deviation of the trajectory from the main axis of the guide, although not statistically significant, made it possible to build a classifier. Conclusions: The patient-specific MR-HSR can be considered as an integrative tool for assessing the subject’s condition by analyzing new quantitative variables which, if matched to the Scale for the Assessment and Rating of Ataxia (SARA), could be the basis of a new index to assess the progressiveness of ataxia.

Objectives: The introduction of a new healthcare technology within the technological facilities of a hospital is a complex action that must go through the mandatory decision-making process of health technology assessment (HTA). Nowadays, developing a universal HTA model poses a significant challenge within the current landscape. This paper describes the proposal of a novel supporting healthcare technology evaluation toolbox, aligned with the principles of the European Network for Health Technology Assessment (EUnetHTA) shared by the Regulation (EU) 2021/2282 on Health Technology Assessment (HTAR). Methods: The proposed toolbox relies on a MATLAB-based multicriteria algorithm that mirrors the evaluative procedure following the hierarchical framework of the analytic hierarchy process. The evaluation framework involves clinical and non-clinical aspects leading to the choice of the best alternative, among the evaluated technologies, to be introduced in the technological infrastructure of the hospital. Moreover, the toolbox incorporates robust economic analysis capabilities, crucial for determining the requisite number of annual hospital procedures to ensure economic equilibrium and mitigate financial risks. Additionally, it computes the payback period, essential for evaluating the economic feasibility of technology investments. HTA evaluations at San Giovanni Addolorata Hospital demonstrate its application. Results: The toolbox exemplifies its efficacy in supporting informed decision-making processes, regarding the adoption of technologies like robotic systems for neurosurgery and angiographic systems, in terms of economic sustainability and clinical effectiveness. Conclusions: This study underscores the toolbox’s role in advancing HTA methodologies and enhancing the efficiency and sustainability of healthcare technology integration.