Robots sociales y animales en la terapia de personas con demencia avanzada

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Medicina. Fecha de lectura: 20-04-201

Micronutrient Deficiencies in Patients with Decompensated Liver Cirrhosis

Cirrosi descompensada; Deficiència de micronutrients; DesnutricióCirrosis descompensada; Deficiencia de micronutrientes; DesnutriciónDecompensated cirrhosis; Micronutrient deficiency; MalnutritionPatients with cirrhosis often develop malnutrition and micronutrient deficiencies, leading to a worse prognosis and increased mortality. Our main goal was to assess the prevalence of micronutrient deficiencies in patients with decompensated cirrhosis. This was a prospective single-center study including 125 consecutive patients hospitalized for acute decompensation of cirrhosis (mostly of alcoholic etiology). A blood test including trace elements and vitamins was performed on admission. The main micronutrient deficiencies observed were vitamin D (in 94.5%), vitamin A (93.5%), vitamin B6 (60.8%) and zinc (85.6%). Patients in Child-Pugh class C had lower levels of vitamin A (p < 0.0001), vitamin E (p = 0.01) and zinc (p < 0.001), and higher levels of ferritin (p = 0.002) and vitamin B12 (p < 0.001) than those in Child-Pugh class A and B. Patients with a higher model of end-stage liver disease (MELD) score had lower levels of vitamin A (p < 0.0001), vitamin E (p < 0.001), magnesium (p = 0.01) and zinc (p = 0.001), and higher levels of ferritin (p = 0.002) and vitamin B12 (p < 0.0001). Severe hepatic insufficiency correlated with lower levels of zinc, vitamin E and vitamin A, and higher levels of vitamin B12 and ferritin

Micronutrient Deficiencies in Patients with Decompensated Liver Cirrhosis

Patients with cirrhosis often develop malnutrition and micronutrient deficiencies, leading to a worse prognosis and increased mortality. Our main goal was to assess the prevalence of micronutrient deficiencies in patients with decompensated cirrhosis. This was a prospective single-center study including 125 consecutive patients hospitalized for acute decompensation of cirrhosis (mostly of alcoholic etiology). A blood test including trace elements and vitamins was performed on admission. The main micronutrient deficiencies observed were vitamin D (in 94.5%), vitamin A (93.5%), vitamin B6 (60.8%) and zinc (85.6%). Patients in Child-Pugh class C had lower levels of vitamin A (p < 0.0001), vitamin E (p = 0.01) and zinc (p < 0.001), and higher levels of ferritin (p = 0.002) and vitamin B12 (p < 0.001) than those in Child-Pugh class A and B. Patients with a higher model of end-stage liver disease (MELD) score had lower levels of vitamin A (p < 0.0001), vitamin E (p < 0.001), magnesium (p = 0.01) and zinc (p = 0.001), and higher levels of ferritin (p = 0.002) and vitamin B12 (p < 0.0001). Severe hepatic insufficiency correlated with lower levels of zinc, vitamin E and vitamin A, and higher levels of vitamin B12 and ferritin

Using XAI in the Clock Drawing Test to reveal the cognitive impairment pattern.

he prevalence of dementia is currently increasing worldwide. This syndrome produces a deteriorationin cognitive function that cannot be reverted. However, an early diagnosis can be crucial for slowing itsprogress. The Clock Drawing Test (CDT) is a widely used paper-and-pencil test for cognitive assessmentin which an individual has to manually draw a clock on a paper. There are a lot of scoring systems forthis test and most of them depend on the subjective assessment of the expert. This study proposes acomputer-aided diagnosis (CAD) system based on artificial intelligence (AI) methods to analyze the CDTand obtain an automatic diagnosis of cognitive impairment (CI). This system employs a preprocessingpipeline in which the clock is detected, centered and binarized to decrease the computational burden.Then, the resulting image is fed into a Convolutional Neural Network (CNN) to identify the informativepatterns within the CDT drawings that are relevant for the assessment of the patient’s cognitive status.Performance is evaluated in a real context where patients with CI and controls have been classified byclinical experts in a balanced sample size of 3282 drawings. The proposed method provides an accuracyof 75.65% in the binary case-control classification task, with an AUC of 0.83. These results are indeedrelevant considering the use of the classic version of the CDT. The large size of the sample suggests thatthe method proposed has a high reliability to be used in clinical contexts and demonstrates the suitabilityof CAD systems in the CDT assessment process. Explainable artificial intelligence (XAI) methods areapplied to identify the most relevant regions during classification. Finding these patterns is extremelyhelpful to understand the brain damage caused by CI. A validation method using resubstitution withupper bound correction in a machine learning approach is also discusseThis work was supported by the MCIN/ AEI/10.13039/501100011033/ and FEDER “Una manera de hacer Europa” under the RTI2018- 098913-B100 project, by the Consejeria de Economia, Innovacion, Ciencia y Empleo (Junta de An765 dalucia) and FEDER under CV20-45250, A-TIC080-UGR18, B-TIC-586-UGR20 and P20-00525 projects, and by the Ministerio de Universidades under the FPU18/04902 grant given to C. JimenezMesa and the Margarita-Salas grant to J.E. Arco

Study of the Photodegradation of PBDEs in Water by UV-LED Technology

Polybrominated diphenyl ethers (PBDEs) are persistent organic pollutants that can arrive to water bodies from their use as flame retardants in a wide range of applications, such as electric and electronic devices or textiles. In this study, the photodegradation of PBDEs in water samples when applying UV-LED radiation was studied. Irradiation was applied at three different wavelengths (255 nm, 265 nm and 285 nm) and different exposure times. The best degradation conditions for spiked purified water samples were at 285 nm and 240 min, resulting in degradations between 67% and 86%. The optimized methodology was applied to real water samples from different sources: river, marine, wastewater (effluent and influent of treatment plants) and greywater samples. Real water samples were spiked and exposed to 4 hours of irradiation at 285 nm. Successful photodegradation of PBDEs ranging from 51% to 97% was achieved for all PBDE congeners in the different water samples with the exception of the marine one, in which only a 31% of degradation was achieved

Robots in therapy for dementia patients

This paper presents the application developed for humanoid robots which are used in therapy of dementia patients, as a cognitive stimulation tool. It has been created using BICA, a component oriented framework for programming robot applications, which is also described. The developed robotherapy application includes the control software onboard the robot and some tools like the visual script generator or several monitoring tools to supervise the robot behavior along the sessions. The behavior of the robot along the therapy sessions is visually programmed in a session script that allows music playing, physical movements (dancing, exercises...), speech synthesis and interaction with the human monitor. The monitoring tools allow the therapist interaction with the robot through its buttons, a tablet or a Wiimote device. Experiments with real dementia patients have been performed in collaboration with a research center in neurological diseases. Initial results show a slight (or mild) improvement in neuropsychiatric symptoms over other traditional therapy methods.This work was supported by the project S2009/DPI-1559, RoboCity2030-II, from the Comunidad de Madrid, by the project PI10/02567 from the Spanish Ministry of Science and Innovation and project 231/2011 from IMSERSO

ACM/IEEE International Conference on Human-Robot Interaction

Several studies have been reported on the use of social robots for dementia care. These robots have been used for diverse tasks such as for companionship, as an exercise coach, and as daily life assistant. However, most of these studies have assessed impact on participants only at the time when the interaction takes place rather than their medium or long-term effects. In this work, we report on a nine-week study conducted in a nursing home in which a autonomous social robot, called Eva, acts as facilitator of a cognitive stimulation therapy (CST). During the study, eight persons with dementia interacted with the robot in a group session which included elements of music therapy, reminiscence, cognitive games, and relaxation. Using the Neuropsychiatric Inventory-Nursing Home version (NPI-NH), we analyzed the impact of the therapy guided by the robot. The results show a statistically significant decrease in the total score of NPI-NH. Also, three dementia-related symptoms: Delusions, agitation/aggression, and euphoria/exaltation, show a statistically significant decrease after the intervention. In addition, a qualitative analysis on interviews conducted with caregivers shows that all participants exhibits positive short-term effects after the session and provides insights on why some changes in behavior prevailed beyond the therapy sessions. Our results provide evidence that a social robot could play a role in improving the quality of life of persons with dementia

Development of an Environmental Decision Support System for Enhanced Coagulation in Drinking Water Production

Drinking water production is subject to multiple water quality requirements such as minimizing disinfection byproducts (DBPs) formation, which are highly related to natural organic matter (NOM) content. For water treatment, coagulation is a key process for removing water pollutants and, as such, is widely implemented in drinking water treatment plants (DWTPs) facilities worldwide. In this context, artificial intelligence (AI) tools can be used to aid decision making. This study presents an environmental decision support system (EDSS) for coagulation in a Mediterranean DWTP. The EDSS is structured hierarchically into the following three levels: data acquisition, control, and supervision. The EDSS relies on influent water characterization, suggesting an optimal pH and coagulant dose. The model designed for the control level is based on response surface methodology (RSM), targeted to optimize removal for the response variables (turbidity, total organic carbon (TOC), and UV254). Results from the RSM model provided removal percentages for turbidity (64.6%), TOC (21.9%), and UV254 (30%), which represented an increase of 4%, 33%, and 28% as compared with the DWTP water sample. Regarding the entire EDSS, 62%, 21%, and 25% of turbidity, TOC, and UV254 removal were fixed as the optimization criteria. Supervision rules (SRs) were included at the top of the architecture to intensify process performance under specific circumstances

Clinical Relevance of Specific Cognitive Complaints in Determining Mild Cognitive Impairment from Cognitively Normal States in a Study of Healthy Elderly Controls

Introduction: Subjective memory complaints in the elderly have been suggested as an early sign of dementia. This study aims at investigating whether specific cognitive complaints are more useful than others to discriminate Mild Cognitive Impairment (MCI) by examining the dimensional structure of the Everyday Memory Questionnaire (EMQ).Material and Methods: A sample of community-dwelling elderly individuals was recruited (766 controls and 78 MCI). The Everyday Memory Questionnaire (EMQ) was administered to measure self-perception of cognitive complaints. All participants also underwent a comprehensive clinical and neuropsychological battery. Combined exploratory factor analysis and item response theory were performed to identify the underlying structure of the EMQ. Furthermore, logistic regression analyses were conducted to study whether single cognitive complaints were able to predict MCI.Results: A suitable five-factor solution was found. Each factor focused on a different cognitive domain. Interestingly, just three of them, namely forgetfulness of immediate information, executive functions and prospective memory proved to be effective in distinguishing between cognitively healthy individuals and MCI. Based on these results we propose a shortened EMQ version comprising 10 items (EMQ-10).Discussion: Not all cognitive complaints have the same clinical relevance. Only subjective complaints on specific cognitive domains are able to discriminate MCI. We encourage clinicians to the EMQ-10 as a useful tool to quantify and monitor the progression of individuals who report cognitive complaints