The aim of this study was to identify and characterise the association between the prevalence of pressure ulcers, spasticity levels, and advanced dementia in disable elderly patients. Data were obtained from the patient medical files. Patients were hospitalised in the geriatric skilled nursing department. A total of 40 frail elderly patients, bedbound and suffering from advanced chronic diseases, advanced dementia, and high‐grade pressure ulcers, were examined. Pressure ulcer grades and spasticity in advanced dementia versus non‐dementia patients were evaluated. Logistic regression indicated that only advanced dementia and spasticity were significantly associated with the development of pressure ulcers versus those without dementia or without spasticity. Patients with advanced dementia displayed a significantly higher prevalence of severe spasticity. In multivariate logistic regression analyses, spasticity was significantly associated with pressure ulcers. The strong association of spasticity with the onset of pressure ulcers in advanced dementia should encourage clinicians to implement preventative measures to delay the onset of pressure ulcers.

These findings add to previous reports suggesting that poorer outcome of anxiety disorders among cannabis users may be attributed mainly to differences in baseline factors and not cannabis use.

Background: EEG-driven research is paramount in cognitive-neuropsychological studies, as it provides a non-invasive window to the underlying neural mechanisms of cognition and behavior. A myriad collection of software and hardware frameworks has been developed to alleviate some of the technical barriers involved in EEG-driven research. Methods: we propose an integrated development environment which encompasses the entire technical ''data-collection pipeline'' of cognitive-neuropsychological research, including experiment design, data acquisition, data exploration and analysis in a state-of-the-art user interface. Our framework is based on a unique integration between a python-based web framework, time-oriented databases and object-based data schemes. Results: we demonstrated our framework with the recording and analysis of an n-Back task completed by 15 elderly (ages 50 to 80) participants. This case study demonstrates the highly utilized nature of our integrated framework with a challenging target population. Furthermore, our results may provide new insights into the correlation between brain activity and working memory performance in elderly people, who are prone to experience accelerated decline in executive prefrontal cortex functioning. Conclusion: our framework extends the range of EEG-driven experimental methods for assessing cognition available for cognitive-neuroscientists, allowing them to concentrate on the creative part of their work instead of technical aspects.

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