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In this article we approach the concept of paradoxical lucidity (LP) (an unexpected, spontaneous, significant and relevant episode of communication or connection) in persons with advanced dementia. The existence of LP could change the paradigm of dementia as a degenerative, chronic, progressive and irreversible disease (where neuronal death plays the leading role), towards a model where functional deficits of neuronal networks acquire importance, which raises new potentially reversible therapeutic and rehabilitative possibilities. We analyze the ethical consequences that these episodes may have with respect to the implicated persons (patients, caregivers and professionals in charge of their care) and try to answer the following question: Do persons with advanced dementia continue to maintain their personal identity despite suffering cognitive impairment so severe?. The LP indicates that this is possible. In this work we make a transversal outline of the different concepts and theories of personal identity in these patients, from different areas of knowledge (philosophy, psychology, neuroscience)., (Copyright © 2024 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.)

Objective: To design a mortality indicator in acute coronary syndrome (ACS) in the intensive care unit (ICU)., Design: A multicenter, observational descriptive study was carried out., Participants: Patients with ACS admitted to the ICUs included in the ARIAM-SEMICYUC registry between January 2013 and April 2019., Interventions: None., Main Variables of Interest: Demographic parameters, time of access to the healthcare system, and clinical condition. Revascularization therapy, drugs and mortality were analyzed. Cox regression analysis was performed, followed by the design of a neural network. A receiver operating characteristic curve (ROC) was plotted to calculate the power of the new score. Lastly, the clinical utility or relevance of the ARIAM indicator (ARIAM' s ) was assessed using a Fagan test., Results: A total of 17,258 patients were included in the study, with a mortality rate of 3.5% (n = 605) at discharge from the ICU. The variables showing statistical significance (P < .001) were entered into the supervised predictive model, an artificial neural network. The new ARIAM' s yielded a mean of 0.0257 (95%CI: 0.0245-0.0267) in patients discharged from the ICU versus 0.27085 (95%CI: 0.2533-0.2886) in those who died (P < .001). The area under the ROC curve of the model was 0.918 (95%CI: 0.907-0.930). Based on the Fagan test, the ARIAM' s showed the mortality risk to be 19% (95%CI: 18%-20%) when positive and 0.9% (95%CI: 0.8%-1.01%) when negative., Conclusions: A new mortality indicator for ACS in the ICU can be established that is more accurate and reproducible, and periodically updated., (Copyright © 2023 Elsevier España, S.L.U. and SEMICYUC. All rights reserved.)

Background: To test whether a Shallow Neural Network (S-NN) can detect and classify vascular tone dependent changes in arterial blood pressure (ABP) by advanced photopletysmographic (PPG) waveform analysis., Methods: PPG and invasive ABP signals were recorded in 26 patients undergoing scheduled general surgery. We studied the occurrence of episodes of hypertension (systolic arterial pressure (SAP) >140 mmHg), normotension and hypotension (SAP < 90 mmHg). Vascular tone according to PPG was classified in two ways: 1) By visual inspection of changes in PPG waveform amplitude and dichrotic notch position; where Classes I-II represent vasoconstriction (notch placed >50% of PPG amplitude in small amplitude waves), Class III normal vascular tone (notch placed between 20-50% of PPG amplitude in normal waves) and Classes IV-V-VI vasodilation (notch <20% of PPG amplitude in large waves). 2) By an automated analysis, using S-NN trained and validated system that combines seven PPG derived parameters., Results: The visual assessment was precise in detecting hypotension (sensitivity 91%, specificity 86% and accuracy 88%) and hypertension (sensitivity 93%, specificity 88% and accuracy 90%). Normotension presented as a visual Class III (III-III) (median and 1st-3rd quartiles), hypotension as a Class V (IV-VI) and hypertension as a Class II (I-III); all p < .0001. The automated S-NN performed well in classifying ABP conditions. The percentage of data with correct classification by S-ANN was 83% for normotension, 94% for hypotension, and 90% for hypertension., Conclusions: Changes in ABP were correctly classified automatically by S-NN analysis of the PPG waveform contour., (Copyright © 2022 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.)

Functional magnetic resonance imaging (fMRI) is an advanced tool for the study of brain functions in healthy subjects and in neuropsychiatric patients. This tool makes it possible to identify and locate specific phenomena related to neuronal metabolism and activity. Starting with the detection of changes in the blood supply to a region that participates in a function, more complex approaches have been developed to study the dynamics of neuronal networks. Studies examining the brain at rest or involved in different tasks have provided evidence related to the onset, development, and/or response to treatment in various diseases. The diversity of the possible artifacts associated with image registration as well as the complexity of the analytical experimental designs has generated abundant debate about the technique behind fMRI. This article aims to introduce readers to the fundamentals underlying fMRI, to explain how fMRI studies are interpreted, and to discuss fMRI's contributions to the study of the mechanisms underlying diverse diseases of the nervous system., (Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.)

A detailed analysis of the literature on consciousness and cognition mechanisms based on the neural networks theory is presented. The immune and inflammatory response to the anesthetic-surgical procedure induces modulation of neuronal plasticity by influencing higher cognitive functions. Anesthetic drugs can cause unconsciousness, producing a functional disruption of cortical and thalamic cortical integration complex. The external and internal perceptions are processed through an intricate network of neural connections, involving the higher nervous activity centers, especially the cerebral cortex. This requires an integrated model, formed by neural networks and their interactions with highly specialized regions, through large-scale networks, which are distributed throughout the brain collecting information flow of these perceptions. Functional and effective connectivity between large-scale networks, are essential for consciousness, unconsciousness and cognition. It is what is called the "human connectome" or map neural networks., (Copyright © 2014 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.)