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Percorrer ESSLei - Capítulos de livros por Objetivos de Desenvolvimento Sustentável (ODS) "03:Saúde de Qualidade"
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- Disorders of ConsciousnessPublication . Teixeira, Liliana; Blacker, Danielle; Rocha, NunoA disorder of consciousness (DoC) is a state where consciousness has been affected by damage to the brain. DoC range in the form of a hierarchy, including coma, vegetative state and minimally conscious state. The most common way to assess consciousness is to observe their responses to stimulation. However, observing these responses and detecting purposeful behaviours is extremely challenging. Several studies have shown that misdiagnosis is common. It is crucial to optimise the way consciousness assessments are performed. Clinical management of DoC patients, from treatment of pain to end-of-life decisions, depends on behavioural observations. In the present chapter, we review the challenges posed by the assessment of consciousness and the importance of combining clinical assessment with complementary methods of assessment, such as positron emission tomography, functional magnetic resonance imaging and electroencephalography. According to the diagnosis established, the patient will follow different care pathways. Although therapeutic options of DoC are still limited, basic therapies include artificial nutrition and hydration, physical and occupational therapies as well as sensory stimulation. Pharmacologic trials, deep brain stimulation and multisensory stimulations are some of the therapeutic options for DoCs. Recently, it was removed the requirement to obtain legal sanction for every decision to withdraw clinically assisted nutrition and hydration from people in DoCs. This has led to an entire paradigm shift, from a focus on the diagnosis to a focus on the patient's best interest. Although these decisions will spare the courts' involvement, one should never disregard reaching a correct diagnosis for this vulnerable population.
- Human-Computer Interaction in BedPublication . Desouzart, Gustavo; Filgueiras, ErnestoSleep disorders are increasingly common view and it is a growing problem in modern societies. There are several problems that can cause this type of disturbance, being the demanding obligations of work and study, a current problem, which leads individuals to allocate more time their rest period in at home. Currently, we are seeing the replacement of handwork by mental, automated and computerized work, which translates into an increasing percentage of time spent performing repetitive static character tasks (physical effort), being able to compare yourself to your work done in industry, traditional production lines (Caetano & Vala 2002). It is no less demanding contexts of labor among which are those activities that involve the long hours spent at the computer. This paper presents a study whose objective was to research the human-computer interaction with the time spent by young adults in carrying out activities with computing devices (computer, tablet or mobile phone) in residences’ bedrooms of air force military and university students in rest time periods and with ecological validation with observation method to video analysis and using a Software iSEE. A sample of 32956 observations, which corresponds to 1824 sleep-hours of 24 young adults, was classified into two (2) Interaction Categories (IC), body position while participants were awake in bed (2873 observations) and doing activities (3001 observations). The image registration was performed during the period of six months, divided into two periods with each participant, to enable the analysis of different times of the year and not just a single period can mean a higher specific activity. The results show that 38.7% (N = 1113 observations) of the participants presented the sitting as the most common postural behavior during awake in bed when the participants doing activities. In reference of activities in bed, 49.2% (N = 1475) used the computer, followed by Using mobile devices, with 16.7% (N = 501) of observations. When we analyze the group of participants, the students showed 49.2% of the period of activity in bed, using the computer, and 13.8% used mobile equipment. In the same reference, the military also used the computer (49%) as the main activity in bed during the night rest, but they used more mobile devices (19.4%) than students. Regarding the postures, students used the sitting (57.1%) as the main active posture when in bed, however, the military was the only sitting 3rd indication posture in bed, being the 1st observation of posture in bed,was the supine position with 30.7%. This data set the type of use of computer devices in bed (studying, playing games, watching movie or playing). Findings of this study allow suggesting what graphical interface designers must seek as newstrategies and solutions for posture in bed, exploring other peripheral equipment for using informatics equipment in bed position.
- Hyperbaric Oxygen Therapy Improves Glucose Homeostasis in Type 2 Diabetes Patients: A Likely Involvement of the Carotid BodiesPublication . Vera-Cruz, P.; Guerreiro, F.; Ribeiro, M.J.; Guarino M.P.; Conde, S.V.The carotid bodies (CBs) are peripheral chemoreceptors that respond to hypoxia increasing minute ventilation and activating the sympathetic nervous system. Besides its role in ventilation we recently described that CB regulate peripheral insulin sensitivity. Knowing that the CB is functionally blocked by hyperoxia and that hyperbaric oxygen therapy (HBOT) improves fasting blood glucose in diabetes patients, we have investigated the effect of HBOT on glucose tolerance in type 2 diabetes patients. Volunteers with indication for HBOT were recruited at the Subaquatic and Hyperbaric Medicine Center of Portuguese Navy and divided into two groups: type 2 diabetes patients and controls. Groups were submitted to 20 sessions of HBOT. OGTT were done before the first and after the last HBOT session. Sixteen diabetic patients and 16 control individual were included. Fasting glycemia was143.5 ± 12.62 mg/dl in diabetic patients and 92.06 ± 2.99 mg/dl in controls. In diabetic patients glycemia post-OGTT was 280.25 ± 22.29 mg/dl before the first HBOT session. After 20 sessions, fasting and 2 h post-OGTT glycemia decreased significantly. In control group HBOT did not modify fasting glycemia and post-OGTT glycemia. Our results showed that HBOT ameliorates glucose tolerance in diabetic patients and suggest that HBOT could be used as a therapeutic intervention for type 2 diabetes.
- Level up! How Gamed-Based Activities Transform Learning and Alleviate Stress in Institutionalized ElderlyPublication . Lacomba-Arnau, Elena; Ribeiro, Anaísa; Sabino, Raquel; Pinheiro, Rafael; Lopes, Susana; Gaspar, Marisa; Navarro-Mateos, Carmen; Sousa, Micael; Rosa, MarleneMental health issues are a critical concern for the elderly, as the inability to manage stress during stimulation activities can significantly impair their ability to accept and effectively learn new tasks, thereby affecting their performance in daily life activities. Serious games are increasingly recognized as valuable in the context of rehabilitation; however, there is a paucity of studies examining how elderly individuals manage stress and learn in regular practice using such games. In this study, 10 institutionalized elderly participants underwent 6 game-based stimulation sessions playing the serious games Ta!Ti! and Mexerico. Learning variables, including time and error rates, were assessed at baseline (T0), mid-point (T1), and the final session (T2), along with stress management indicators, specifically cortisol levels, at T0 and T2. The findings revealed that learning profiles improved throughout the program, with more pronounced gains observed initially. Additionally, stress levels decreased following each game-based session. The study identified significant relationships between stress management and learning profiles, suggesting that game-based activities can effectively enhance both learning outcomes and stress reduction in the elderly.
- STM-GNN: Space-Time-and-Memory Graph Neural Networks for Predicting Multi-Drug Resistance Risks in Dynamic Patient NetworksPublication . Geissbuhler, Damien; Bornet, Alban; Marques, Catarina; Anjos, André; Pereira, Sónia; Teodoro, DouglasHospital-acquired infections (HAIs), particularly those caused by multidrug-resistant (MDR) bacteria, pose significant risks to vulnerable patients. Accurate predictive models are important for assessing infection dynamics and informing infection prediction and control (IPC) programmes. Graph-based methods, including graph neural networks (GNNs), offer a powerful approach to model complex relationships between patients and environments but often struggle with data sparsity, irregularity, and heterogeneity. We propose the space-time-and-memory (STM)-GNN, a temporal GNN enhanced with recurrent connectivity designed to capture spatiotemporal infection dynamics. STM-GNN effectively integrates sparse, heterogeneous data combining network information from patient-environment interactions and internal memory from historical colonization and contact patterns. Using a unique IPC dataset containing clinical and environmental colonization information collected from a long-term healthcare unit, we show that STM-GNN effectively addresses the challenges of limited and irregular data in an MDR prediction task. Our model reaches 0.84 AUROC, and achieves the most balanced performance overall compared to classic machine learning algorithms, as well as temporal GNN approaches.
- Understanding the Metabolic Syndrome Using a Biomedical Chemistry ProfilePublication . Pereira, Cidália; Monteiro, Rosário; Martins, Maria João2.3.1 Introduction For quite some time, it has been identified that high blood pressure, dyslipidemia [increased triglycerides and reduced high-density lipoprotein (HDL) cholesterol levels], impaired glucose homeostasis and abdominal obesity take place concurrently more than by random, supporting the existence of the metabolic syndrome (MetSyn). Additionally, hyperuricemia, a prothrombotic state, oxidative stress, chronic low grade inflammation, increased levels of apolipoprotein-B and small dense low density lipoprotein (LDL) cholesterol (contributing to atherogenic dyslipidemia), non-alcoholic fatty liver disease and/or non-alcoholic steatohepatitis, obstructive sleep apnea and/or polycystic ovarian disease (Fulop, 2006; Alberti, 2009; Roberts, 2009; Ma, 2012; Matsuda, 2013; Mule, 2014; Carson, 2015) are quite often present on the MetSyn, although not yet included in its current/actual definition. Taking this into consideration, it is not surprising that the MetSyn associates with an increased risk of type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (Fulop, 2006; Qiao, 2007; Carson, 2015).