Shared Decision-Making to Improve Health-Related Outcomes for Adults with Stroke Disease

Stroke is one of the leading causes of disability and death worldwide, a severe medical condition for which new solutions for prevention, monitoring, and adequate treatment are needed. This paper proposes a SDM framework for the development of innovative and effective solutions based on artificial intelligence in the rehabilitation of stroke patients by empowering patients to make decisions about the use of devices and applications developed in the European project ALAMEDA. To develop a predictive tool for improving disability in stroke patients, key aspects of stroke patient data collection journeys, monitored health parameters, and specific variables covering motor, physical, emotional, cognitive, and sleep status are presented. The proposed SDM model involved the training and consultation of patients, medical staff, carers, and representatives under the name of the Local Community Group. Consultation with LCG members, consists of 11 representative people, physicians, nurses, patients and caregivers, which led to the definition of a methodological framework to investigate the key aspects of monitoring the patient data collection journey for the stroke pilot, and a specific questionnaire to collect stroke patient requirements and preferences. A set of general and specific guidelines specifying the principles by which patients decide to use wearable sensing devices and specific applications resulted from the analysis of the data collected using the questionnaire. The preferences and recommendations collected from LCG members have already been implemented in this stage of ALAMEDA system design and development.

Mobile App Interventions for Parkinson's Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review

Central nervous system diseases (CNSDs) lead to significant disability worldwide. Mobile app interventions have recently shown the potential to facilitate monitoring and medical management of patients with CNSDs. In this direction, the characteristics of the mobile apps used in research studies and their level of clinical effectiveness need to be explored in order to advance the multidisciplinary research required in the field of mobile app interventions for CNSDs. A systematic review of mobile app interventions for three major CNSDs, i.e., Parkinson's disease (PD), multiple sclerosis (MS), and stroke, which impose significant burden on people and health care systems around the globe, is presented. A literature search in the bibliographic databases of PubMed and Scopus was performed. Identified studies were assessed in terms of quality, and synthesized according to target disease, mobile app characteristics, study design and outcomes. Overall, 21 studies were included in the review. A total of 3 studies targeted PD (14%), 4 studies targeted MS (19%), and 14 studies targeted stroke (67%). Most studies presented a weak-to-moderate methodological quality. Study samples were small, with 15 studies (71%) including less than 50 participants, and only 4 studies (19%) reporting a study duration of 6 months or more. The majority of the mobile apps focused on exercise and physical rehabilitation. In total, 16 studies (76%) reported positive outcomes related to physical activity and motor function, cognition, quality of life, and education, whereas 5 studies (24%) clearly reported no difference compared to usual care. Mobile app interventions are promising to improve outcomes concerning patient's physical activity, motor ability, cognition, quality of life and education for patients with PD, MS, and Stroke. However, rigorous studies are required to demonstrate robust evidence of their clinical effectiveness.

Differential expression of the K-2 opioid receptor protein under the effect of opioid agonists in embryonic chick neurons in vitro

Neuronal cells cultured from 7-day-old chick embryos and differentiated under the chronic effect of opioid drugs were studied for kappa-opioid receptor expression. Plasma-membrane integrated receptors were measured by radioligand ([3H]-naloxone 1 nM, [3H]-ethylketocyclazocine, 4 nM) binding to intact neurons. These data were compared to the results of k-opioid receptor immunostaining (mAb KA8, Maderspach et al., 1991). The chronic presence of kappa-selective opioid agonist dynorphin1-13 (10(-6)-10(-7) M) or bremazocine (10(-7)-10(-8) M) between cultivation days 2-4 resulted in the significant (80%) down-regulation of the membrane integrated binding sites in concentration dependent fasion. Antagonists naloxone (10(-5) M) and norbinaltorphimine (10(-8) M) alone were ineffective, however, they essentially balanced the changes caused by the agonists. Mu ligand morphine was without effect while kappa-1 selective U 50488 H caused moderate decrease only at high concentrations. Interestingly, mAb KAB also caused down-regulation indicating that it has some agonist character. The down-regulation became measurable in short time (58% within 24 hours) and persisted during the three-day presence of the agonists. Kappa-receptor immunostaining of the neurons was not significantly influenced by the agonists. We suppose that the chronic opioid treatment may influence the intracellular traffic of the receptor protein.