Artificial intelligence and learning technologies to enhance competencies in health students / Inteligencia artificial y tecnologías del aprendizaje para potenciar competencias en estudiantes de salud

With the advent of learning and knowledge technologies (LKT), the role of the teacher evolved from instructor to facilitator, and the student went from being a mere receiver to a creator. One of the technologies that has significantly transformed all aspects of everyday life, including education, is artificial intelligence (AI). In the educational environment, especially in higher education, new tools are made available capable of transforming the traditional processes of teaching and learning and with it, the development of students' competencies. This study offers a perspective on the use of LKT and AI in the nursing career, as well as its implications in teaching, based on scientific literature and the experience developed in the institution. The authors' experience with its use as part of the research projects "Innovative bimodal teaching for the development of generic competencies in university students" and "Bimodal teaching system for the development of learning and knowledge technologies" is described. which is part of the research program "Curriculum, innovation, education and training". The advantages of its use are shown, and the important ethical and practical challenges are reflected. The authors aim to provide valuable information on how technological and artificial intelligence tools can be successfully incorporated into the educational environment to develop specific and transversal competencies in university students, while promoting responsible and ethical use. The authors consider that the use of artificial intelligence in higher education should not be prohibited, but that its use should be regulated through policies that promote ethical and responsible use and that, in addition, teachers and students should be taught and taught to read and write about the proper use of this powerful tool, which would help in the teaching and learning process and the development of competencies.

Con la llegada de las tecnologías del aprendizaje y el conocimiento (TAC), el rol del docente evolucionó de instructor a facilitador, y el estudiante pasó de ser un mero receptor a un creador. Una de las tecnologías que ha transformado significativamente todos los aspectos de la vida cotidiana, incluyendo la educación, es la inteligencia artificial (IA). En el entorno educativo, especialmente en la enseñanza superior, se ponen a disposición nuevas herramientas capaces de transformar los procesos tradicionales de enseñanza y aprendizaje y con ello, el desarrollo de competencias del estudiantado. Este estudio ofrece una perspectiva sobre el uso de TAC e IA en la carrera de enfermería, así como sus implicaciones en la enseñanza, basándose en literatura científica y la experiencia desarrollada en la institución. Se describe la experiencia de los autores con su uso como parte de los proyectos de investigación "Enseñanza bimodal innovadora para el desarrollo de competencias genéricas en estudiantes universitarios" y "Sistema de enseñanza bimodal para el desarrollo de tecnologías del aprendizaje y el conocimiento", los cuales se enmarcan en el programa de investigación "Currículo, innovación, educación y formación". Se muestran las ventajas de su uso, y se reflexiona sobre los importantes desafíos éticos y prácticos. Los autores pretenden proporcionar información valiosa sobre cómo las herramientas tecnológicas y de inteligencia artificial pueden incorporarse con éxito al entorno educativo para desarrollar competencias específicas y transversales en los estudiantes universitarios, promoviendo al mismo tiempo un uso responsable y ético. Los autores consideran que no se debe prohibir el uso de la inteligencia artificial en la enseñanza superior, sino que se debe regular su uso mediante políticas que promuevan el uso ético y responsable y que, además, se alfabetice a docentes y estudiantes sobre el uso adecuado de esta poderosa herramienta, lo cual ayudaría en el proceso de enseñanza y aprendizaje y el desarrollo de competencias.

Com o advento das tecnologias de aprendizagem e conhecimento (TAC), o papel do professor evoluiu de instrutor para facilitador, e o aluno passou de mero receptor a criador. Uma das tecnologias que tem transformado significativamente todos os aspectos do dia a dia, inclusive a educação, é a inteligência artificial (IA). No ambiente educacional, especialmente no ensino superior, são disponibilizadas novas ferramentas capazes de transformar os processos tradicionais de ensino e aprendizagem e, com isso, o desenvolvimento das competências dos alunos. Este estudo oferece uma perspectiva sobre o uso da TAC e da IA na carreira de enfermagem, bem como suas implicações no ensino, com base na literatura científica e na experiência desenvolvida na instituição. Descreve-se a experiência dos autores com sua utilização como parte dos projetos de pesquisa "Ensino bimodal inovador para o desenvolvimento de competências genéricas em estudantes universitários" e "Sistema de ensino bimodal para o desenvolvimento de tecnologias de aprendizagem e conhecimento". que fazem parte do programa de pesquisa "Currículo, inovação, educação e treinamento". As vantagens de seu uso são mostradas, e os importantes desafios éticos e práticos são refletidos. Os autores pretendem fornecer informações valiosas sobre como ferramentas tecnológicas e de inteligência artificial podem ser incorporadas com sucesso ao ambiente educacional para desenvolver competências específicas e transversais em estudantes universitários, promovendo o uso responsável e ético. Os autores consideram que o uso da inteligência artificial no ensino superior não deve ser proibido, mas que seu uso deve ser regulamentado por meio de políticas que promovam o uso ético e responsável e que, além disso, professores e alunos devem ser ensinados e ensinados a ler e escrever sobre o uso adequado dessa poderosa ferramenta, o que ajudaria no processo de ensino e aprendizagem e no desenvolvimento de competências.

Exogenous glucocorticoids to improve extinction learning for post-traumatic stress disorder patients with hypothalamic-pituitary-adrenal-axis dysregulation: a study protocol description.

Background: Trauma-focused treatments for post-traumatic stress disorder (PTSD) are effective for many patients. However, relapse may occur when acquired extinction memories fail to generalize beyond treatment contexts. A subgroup of PTSD patients - potentially with substantial exposure to early-life adversity (ELA) - show dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, which results in lower cortisol levels. Glucocorticoids, including cortisol, appear to facilitate strength and generalization of emotional memories.Objective: We describe the protocol of an integrated PTSD study. We investigate (A) associations between HPA-axis dysregulation, ELA, epigenetic markers, and PTSD treatment outcome (observational study); and (B) effects of exogenous glucocorticoids on strength and generalization of extinction memories and associated neural mechanisms [pharmacological intervention study with functional magnetic resonance imaging (fMRI)]. The objective is to provide proof of concept that PTSD patients with HPA-axis dysregulation often experienced ELA and may show improved strength and generalization of extinction learning after glucocorticoid administration.Method: The observational study (n = 160 PTSD group, n = 30 control group) assesses ELA, follow-up PTSD symptoms, epigenetic markers, and HPA-axis characteristics (salivary cortisol levels during low-dose dexamethasone suppression test and socially evaluated cold-pressor test). The pharmacological intervention study (n = 80 PTSD group, with and without HPA-axis dysregulation) is a placebo-controlled fMRI study with a crossover design. To investigate strength and generalization of extinction memories, we use a differential fear acquisition, extinction, and extinction recall task with spatial contexts within a virtual environment. Prior to extinction learning, 20 mg hydrocortisone or placebo is administered. During next-day recall, strength of the extinction memory is determined by recovery of skin conductance and pupil dilation differential responding, whereas generalization is assessed by comparing responses between different spatial contexts.Conclusion: The integrated study described in the current protocol paper could inform a personalized treatment approach in which these PTSD patients may receive glucocorticoids as a treatment enhancer in trauma-focused therapies.Trial registration: The research project is registered in the European Union Drug Regulating Authorities Clinical Trials (EudraCT) database, https://eudract.ema.europa.eu/, EudraCT number 2020-000712-30.

This protocol reports a proof-of-concept study for glucocorticoids as an enhancer for PTSD treatment.The study examines whether glucocorticoids enhance the strength and generalization of extinction memory.A further aim is to identify HPA-axis-related PTSD subgroups that may particularly benefit.

Processo de ensino e aprendizagem no período de suspensão das aulas presenciais em virtude da pandemia de COVID-19: estudo com professores / Teaching and learning process in the suspension period of classes in virtue of the COVID-19 pandemy: study with teachers / Proceso de enseñanza y aprendizaje durante el período de suspensión de clases presencial por la pandemia del COVID-19: estudio con docentes

Introdução: Sabe-se que durante o período da pandemia do COVID-19, escolas e professores precisaram adaptar-se com alternativas para dar continuidade às aulas. Objetivo: Investigar estratégias e recursos pedagógicos de aprendizagem adotados por professores da rede pública e/ou privada de ensino, do interior de um estado brasileiro, durante o período de suspensão das aulas presenciais, em virtude da Pandemia de Covid-19 e seus efeitos para estudantes com e sem dificuldades de aprendizagem. Método: Aplicação de questionário on-line utilizando a ferramenta Google Forms para 37 professores atuantes do 1° ao 5° ano da rede pública e/ou privada no interior do estado, que tenham trabalhado remotamente durante a Pandemia no período de suspensão das aulas presenciais. Esse material continha questões de múltipla escolha e dissertativas e averiguava a forma de trabalho durante este período, as estratégias e os recursos adotados. Resultados: Os resultados mostraram que as estratégias mais utilizadas pelos professores foram uso de materiais impressos. Os professores relataram as dificuldades e os desafios em adotar o ensino remoto, referentes à desigualdade social dos alunos, a dificuldade de adaptação dos professores a esta forma de ensino e ao empenho restrito das famílias no processo de aprendizagem. Conclusão: foi possível verificar como ocorreu o processo de adaptação ao ensino remoto pelos professores. Verifica-se a necessidade de explorar o trabalho conjunto com a Fonoaudiologia, visando minimizar as dificuldades apresentadas pelos estudantes, o que auxiliaria no processo de ensino e aprendizagem dos alunos que, posteriormente, poderiam vir a ser futuros pacientes do setor de Fonoaudiologia. (AU)

Introduction: it is known that during the period of the COVID-19 pandemic, schools and teachers needed to adapt with alternatives to continue classes. Purpose: Investigate pedagogical learning strategies and resources adopted by teachers from public and/or private schools in the interior of a Brazilian state during the period of suspension of face-to-face classes, due to the Covid-19 Pandemic and its effects on students with and without learning difficulties. Method: This research included the application of an online questionnaire through Google Forms to 37 active teachers from the 1st to the 5th year of the public and/or private network at Brasilian state who have worked remotely during the Pandemic during the suspension period of in-person classes. This material contained multiple choice questions and essays, referring to the way of working during this period, strategies and resources adopted. Results: The results showed that the most used strategies by teachers were the use of printed materials. Teachers reported the difficulties and challenges in adopting remote teaching, referring to the social inequality of students, the limited commitment of families in the learning process and the difficulty of teachers to adapt to this form of teaching. Conclusion: Among 37 teachers who joined the study, it was possible to verify how the process of adaptation to remote teaching took place. There is a need to explore the joint work with Speech Therapy, aiming to minimize the difficulties presented by students. Such clarifications would help in the teaching and learning process of students who could later become future patients in the Speech Therapy sector. (AU)

Introducción: se sabe que durante el período de la pandemia del COVID-19, las escuelas y los docentes requirieron adaptarse con alternativas para continuar las clases. Objetivos: Investigar estrategias y recursos pedagógicos de aprendizaje adoptados por profesores de escuelas públicas y/o privadas del interior de un estado brasileño durante el período de suspensión de clases presenciales, debido a la Pandemia Covid-19 y sus efectos en estudiantes con y sin dificultades de aprendizaje. Método: Esta investigación implicó la aplicación de un cuestionario en línea a través de Formularios de Google a 37 docentes que laboran del 1° al 5° año de la red pública y/o privada del interior del estado, que habían trabajado de manera remota durante la Pandemia en el período de suspensión de clases presenciales. Este material contenía preguntas de selección múltiple y desarrollo, referentes a la forma de trabajar durante este período, las estrategias y los recursos adoptados. Resultados: Los resultados mostraron que las estrategias más utilizadas por los docentes fue el uso de materiales impresos. Los docentes relataron las dificultades y desafíos en la adopción de la enseñanza a distancia, refiriéndose a la desigualdad social de los estudiantes, el compromiso restringido de las familias en el proceso de aprendizaje y la dificultad de adaptación de los docentes a esta forma de enseñanza. Conclusión: Entre 37 docentes que se sumaron al estudio, fue posible verificar cómo ocurrió el proceso de adaptación a la enseñanza a distancia. Existe la necesidad de explorar el trabajo conjunto con la Logopedia, con el objetivo de minimizar las dificultades presentadas por los estudiantes. Tales aclaraciones ayudarían en el proceso de enseñanza y aprendizaje de los estudiantes que luego podrían convertirse en futuros pacientes del sector de Logopedia. (AU)

A problem-based learning experience in a radiology rotation for sixth-year medical students.

OBJECTIVE: To analyse a problem-based learning experience (PBL) in the sixth year of medicine, within a course organised in successive rotations of 12 school days for 7 annual groups. MATERIAL AND METHODS: Each group was divided into subgroups of 6-8 students. Each subgroup was assigned two cases with radiographic images that they had to prepare and present in a joint session in which the students discussed each case and the teacher acted as moderator, without providing solutions. Finally, they had 15 days to complete the debate in an online forum and prepare a written report on each case. RESULTS: During 6 consecutive years, 1001 students participated, whose annual grades ranged between 7.7 ±â€¯1.6 and 9.0 ±â€¯0.7 (mean ±â€¯standard deviation). No correlation was found between the degree of difficulty assigned to the cases and the mean score obtained by each group (R2 = 0.0115). Sixty-six point two percent completed a questionnaire rating various aspects of this experience above 4 out of 5 points and providing overall scores above 8.3 out of 10 points in the different years. The students found this experience appropriate to the objectives of the subject and useful for their educational needs. CONCLUSIONS: PBL allows students to acquire skills of understanding, reasoning and deepening in radiological diagnosis. This study demonstrates that an experience based on PBL can be included in a radiology course organised in a traditional way, allowing students to be graded regardless of the difficulty of the cases.

Machine learning models based on ultrasound and physical examination for airway assessment.

PURPOSE: To demonstrate the utility of machine learning models for predicting difficult airways using clinical and ultrasound parameters. METHODS: This is a prospective non-consecutive cohort of patients undergoing elective surgery. We collected as predictor variables age, sex, BMI, OSA, Mallampatti, thyromental distance, bite test, cervical circumference, cervical ultrasound measurements, and Cormack-Lehanne class after laryngoscopy. We univariate analyzed the relationship of the predictor variables with the Cormack-Lehanne class to design machine learning models by applying the random forest technique with each predictor variable separately and in combination. We found each design's AUC-ROC, sensitivity, specificity, and positive and negative predictive values. RESULTS: We recruited 400 patients. Cormack-Lehanne patients≥III had higher age, BMI, cervical circumference, Mallampati class membership≥III, and bite test≥II and their ultrasound measurements were significantly higher. Machine learning models based on physical examination obtained better AUC-ROC values than ultrasound measurements but without reaching statistical significance. The combination of physical variables that we call the "Classic Model" achieved the highest AUC-ROC value among all the models [0.75 (0.67-0.83)], this difference being statistically significant compared to the rest of the ultrasound models. CONCLUSIONS: The use of machine learning models for diagnosing VAD is a real possibility, although it is still in a very preliminary stage of development. CLINICAL REGISTRY: ClinicalTrials.gov: NCT04816435.

Oral anticoagulant treatment in atrial fibrillation: the AFIRMA real-world study using natural language processing and machine learning.

INTRODUCTION: Oral anticoagulation (OAC) is key in atrial fibrillation (AF) thromboprophylaxis, but Spain lacks substantial real-world evidence. We aimed to analyze the prevalence, clinical characteristics, and treatment patterns among patients with AF undertaking OAC, using natural language processing (NLP) and machine learning (ML). MATERIALS AND METHODS: This retrospective study included AF patients on OAC from 15 Spanish hospitals (2014-2020). Using EHRead® (including NLP and ML), and SNOMED_CT, we extracted and analyzed patient demographics, comorbidities, and OAC treatment from electronic health records. AF prevalence was estimated, and a descriptive analysis was conducted. RESULTS: Among 4,664,224 patients in our cohort, AF prevalence ranged from 1.9% to 2.9%. A total of 57,190 patients on OAC therapy were included, 80.7% receiving Vitamin K antagonists (VKA) and 19.3% Direct-acting OAC (DOAC). The median age was 78 and 76 years respectively, with males constituting 53% of the cohort. Comorbidities like hypertension (76.3%), diabetes (48.0%), heart failure (42.2%), and renal disease (18.7%) were common, and more frequent in VKA users. Over 50% had a high CHA2DS2-VASc score. The most frequent treatment switch was from DOAC to acenocoumarol (58.6% to 70.2%). In switches from VKA to DOAC, apixaban was the most chosen (35.2%). CONCLUSIONS: Utilizing NLP and ML to extract RWD, we established the most comprehensive Spanish cohort of AF patients with OAC to date. Analysis revealed a high AF prevalence, patient complexity, and a marked VKA preference over DOAC. Importantly, in VKA to DOAC transitions, apixaban was the favored option.

Sepsis mortality prediction with Machine Learning Tecniques.

OBJECTIVE: To develop a sepsis death classification model based on machine learning techniques for patients admitted to the Intensive Care Unit (ICU). DESIGN: Cross-sectional descriptive study. SETTING: The Intensive Care Units (ICUs) of three Hospitals from Murcia (Spain) and patients from the MIMIC III open-access database. PATIENTS: 180 patients diagnosed with sepsis in the ICUs of three hospitals and a total of 4559 patients from the MIMIC III database. MAIN VARIABLES OF INTEREST: Age, weight, heart rate, respiratory rate, temperature, lactate levels, partial oxygen saturation, systolic and diastolic blood pressure, pH, urine, and potassium levels. RESULTS: A random forest classification model was calculated using the local and MIMIC III databases. The sensitivity of the model of our database, considering all the variables classified as important by the random forest, was 95.45%, the specificity was 100%, the accuracy was 96.77%, and an AUC of 95%. . In the case of the model based on the MIMIC III database, the sensitivity was 97.55%, the specificity was 100%, and the precision was 98.28%, with an AUC of 97.3%. CONCLUSIONS: According to random forest classification in both databases, lactate levels, urine output and variables related to acid.base equilibrium were the most important variable in mortality due to sepsis in the ICU. The potassium levels were more critical in the MIMIC III database than the local database.

Realidad virtual y biomarcadores digitales: una herramienta clínica para el diagnóstico del autismo / Virtual reality and digital biomarkers: a clinical tool for early autism diagnosis

Resumen Introducción : El Trastorno del Espectro Autista (TEA) es un trastorno del neurodesarrollo, y sus procedimien tos tradicionales de evaluación encuentran ciertas li mitaciones. El actual campo de investigación sobre TEA está explorando y respaldando métodos innovadores para evaluar el trastorno tempranamente, basándose en la detección automática de biomarcadores. Sin embargo, muchos de estos procedimientos carecen de validez ecológica en sus mediciones. En este contexto, la reali dad virtual (RV) presenta un prometedor potencial para registrar objetivamente bioseñales mientras los usuarios experimentan situaciones ecológicas. Métodos : Este estudio describe un novedoso y lúdi co procedimiento de RV para la evaluación temprana del TEA, basado en la grabación multimodal de bio señales. Durante una experiencia de RV con 12 esce nas virtuales, se midieron la mirada, las habilidades motoras, la actividad electrodermal y el rendimiento conductual en 39 niños con TEA y 42 compañeros de control. Se desarrollaron modelos de aprendizaje automático para identificar biomarcadores digitales y clasificar el autismo. Resultados : Las bioseñales reportaron un rendimien to variado en la detección del TEA, mientras que el modelo resultante de la combinación de los modelos de las bioseñales demostró la capacidad de identificar el TEA con una precisión del 83% (DE = 3%) y un AUC de 0.91 (DE = 0.04). Discusión : Esta herramienta de detección pue de respaldar el diagnóstico del TEA al reforzar los resultados de los procedimientos tradicionales de evaluación.

Abstract Introduction : Autism Spectrum Disorder (ASD) is a neurodevelopmental condition which traditional as sessment procedures encounter certain limitations. The current ASD research field is exploring and endorsing innovative methods to assess the disorder early on, based on the automatic detection of biomarkers. How ever, many of these procedures lack ecological validity in their measurements. In this context, virtual reality (VR) shows promise for objectively recording biosignals while users experience ecological situations. Methods : This study outlines a novel and playful VR procedure for the early assessment of ASD, relying on multimodal biosignal recording. During a VR experience featuring 12 virtual scenes, eye gaze, motor skills, elec trodermal activity and behavioural performance were measured in 39 children with ASD and 42 control peers. Machine learning models were developed to identify digital biomarkers and classify autism. Results : Biosignals reported varied performance in detecting ASD, while the combined model resulting from the combination of specific-biosignal models demon strated the ability to identify ASD with an accuracy of 83% (SD = 3%) and an AUC of 0.91 (SD = 0.04). Discussion : This screening tool may support ASD diagnosis by reinforcing the outcomes of traditional assessment procedures.

Classification tree obtained by artificial intelligence for the prediction of heart failure after acute coronary syndromes. / Árboles de clasificación obtenidos mediante inteligencia artificial para la predicción de insuficiencia cardiaca tras el síndrome coronario agudo.

BACKGROUND: Coronary heart disease is the leading cause of heart failure (HF), and tools are needed to identify patients with a higher probability of developing HF after an acute coronary syndrome (ACS). Artificial intelligence (AI) has proven to be useful in identifying variables related to the development of cardiovascular complications. METHODS: We included all consecutive patients discharged after ACS in two Spanish centers between 2006 and 2017. Clinical data were collected and patients were followed up for a median of 53months. Decision tree models were created by the model-based recursive partitioning algorithm. RESULTS: The cohort consisted of 7,097 patients with a median follow-up of 53months (interquartile range: 18-77). The readmission rate for HF was 13.6% (964 patients). Eight relevant variables were identified to predict HF hospitalization time: HF at index hospitalization, diabetes, atrial fibrillation, glomerular filtration rate, age, Charlson index, hemoglobin, and left ventricular ejection fraction. The decision tree model provided 15 clinical risk patterns with significantly different HF readmission rates. CONCLUSIONS: The decision tree model, obtained by AI, identified 8 leading variables capable of predicting HF and generated 15 differentiated clinical patterns with respect to the probability of being hospitalized for HF. An electronic application was created and made available for free.

Analysis of machine learning algorithmic models for the prediction of vital status at six months after hip fracture in patients older than 74 years. / Análisis de modelos algorítmicos de aprendizaje automático para la predicción del estado vital a los seis meses tras fractura de cadera en pacientes mayores de 74 años.

BACKGROUND AND OBJECTIVE: The objective is to develop a model that predicts vital status six months after fracture as accurately as possible. For this purpose we will use five different data sources obtained through the National Hip Fracture Registry, the Health Management Unit and the Economic Management Department. MATERIAL AND METHODS: The study population is a cohort of patients over 74 years of age who suffered a hip fracture between May 2020 and December 2022. A warehouse is created from five different data sources with the necessary variables. An analysis of missing values and outliers as well as unbalanced classes of the target variable («vital status¼) is performed. Fourteen different algorithmic models are trained with the training. The model with the best performance is selected and a fine tuning is performed. Finally, the performance of the selected model is analyzed with test data. RESULTS: A data warehouse is created with 502 patients and 144 variables. The best performing model is Linear Regression. Sixteen of the 24 cases of deceased patients are classified as live, and 14 live patients are classified as deceased. A sensitivity of 31%, an accuracy of 34% and an area under the curve of 0.65 is achieved. CONCLUSIONS: We have not been able to generate a model for the prediction of six-month survival in the current cohort. However, we believe that the method used for the generation of algorithms based on machine learning can serve as a reference for future works.

Didactic model based on study techniques: an analysis in nursing student from Ecuador / Modelo didáctico basado en técnicas de estudio: un análisis en estudiantes de Enfermería de Ecuador / Modelo didático baseado em técnicas de estudo: uma análise em estudantes de enfermagem do Equador

Objective: To design a didactic model for the teaching of study techniques in the students of the Bachelor of Nursing career of a university in Ecuador. Methodology: A quasi-experimental study with pre- and post-intervention evaluation of a particular group and experts in pedagogy validated the proposed didactic model. Results: The data obtained before and after the application of the model were significant, the didactic model combines through the diagnosis, planning, execution and control of actions a system of relationships between understanding, analysis and health needs, with emphasis on communication and people skills, emotional stability and physical endurance . It consists of personal aspects (teacher and students, techniques and learning styles, activities and approaches) Discussion: the implementation contributed to the improvement of the organization, planning of activities, the adoption of study techniques and the motivation of students to carry out the academic activities of independent work of the Bachelor of Nursing career, as well as project the articulation of knowledge learned at university in their working life.

Objetivo: Diseñar un modelo didáctico para la enseñanza de técnicas de estudio en los estudiantes de la carrera de Licenciatura en Enfermería de una universidad de Ecuador. Metodología: Estudio cuasi experimental con evaluación pre y post intervención de un solo grupo y se contó con expertos en pedagogía que validaron el modelo didáctico propuesto. Resultados: Los datos obtenidos antes y después de la aplicación del modelo fueron significativos, el modelo didáctico conjuga a través del diagnóstico, planificación, ejecución y control de acciones un sistema de relaciones entre la comprensión, análisis y necesidades de salud, con énfasis en las Habilidades de comunicación e interpersonales, estabilidad emocional y resistencia física. Se compone de aspectos personales (profesor y estudiantes, técnicas y estilos de aprendizaje, actividades y enfoques) Discusión: la implementación contribuyó al mejoramiento de la organización, planificación de actividades, la adopción de técnicas de estudio y la motivación de los estudiantes para realizar las actividades académicas de trabajo independiente de la carrera de Licenciatura en Enfermería, así como proyectar la articulación de los conocimientos aprendidos en la universidad en su vida laboral.

Objetivo: Elaborar um modelo didático para o ensino de técnicas de estudo nos alunos do curso de Bacharelado em Enfermagem de uma universidade do Equador. Metodologia: Estudo quase-experimental com avaliação pré e pós-intervenção de um único grupo e especialistas em pedagogia validou o modelo didático proposto. Resultados: Os dados obtidos antes e após a aplicação do modelo foram significativos, o modelo didático combina através do diagnóstico, planejamento, execução e controle das ações um sistema de relações entre compreensão, análise e necessidades de saúde, com ênfase na comunicação e habilidades interpessoais, estabilidade emocional e resistência física. Consiste em aspectos pessoais (professor e alunos, técnicas e estilos de aprendizagem, atividades e abordagens) Discussão: a implementação contribuiu para a melhoria da organização, planejamento das atividades, adoção de técnicas de estudo e motivação dos alunos para realizar as atividades acadêmicas de trabalho independente da carreira de Bacharel em Enfermagem, bem como projetar a articulação de saberes aprenderam na universidade em sua vida profissional.

La enseñanza de la radiología en los programas docentes integrados / Teaching Radiology in integrated educational programs

La radiología es una disciplina médica, un área de conocimiento transversal integrada en cualquier situación clínica. El aprendizaje óptimo del conocimiento, habilidades y aptitudes en radiología en el Grado en Medicina requiere la integración de cualquier modalidad de imagen en las distintas áreas del conocimiento: desde las asignaturas básicas hasta cualquier asignatura clínica del grado. El presente artículo describe la integración de la docencia en radiología del plan de estudios en todo el grado de medicina de la Universidad de Girona (UdG), describiendo las distintas actividades docentes de radiología que se imparten en las distintas asignaturas; desde primero a sexto curso. Se detallan las actividades específicas de la asignatura de «radiología», incluyendo talleres, seminarios, prácticas, juego de ordenador interactivo, y describiendo las características de la actividad metodológica docente principal de la UdG, el aprendizaje basado en problemas.(AU)

Radiology is a medical discipline, an area of transversal knowledge integrated into any clinical situation. The optimal training of learning knowledge, skills and aptitudes in Radiology in the Degree in Medicine requires the integration of any imaging modality in the different areas of knowledge; from the basic subjects to any clinical subject of the Degree. This article describes the integration of Radiology teaching into the curriculum throughout the Medicine Degree at the University of Girona (UdG), describing the different radiology teaching activities that are taught. The specific activities of the subject «Radiology» are detailed; through workshops, seminars, practices, interactive computer game; and describing the characteristics of the main teaching methodological activity of the UdG, Problem-Based Learning.(AU)

Estudios normativos españoles (proyecto NEURONORMA-Plus): Normas para el Wisconsin Card Sorting Test (WCST), la Figura Compleja Modificada de Taylor (FCMT) y el Ruff-Light Trail Learning Test (RULIT) / Spanish normative studies (NEURONORMA-Plus project): norms for the Wisconsin Card Sorting Test, the Modified Taylor Complex Figure, and the Ruff-Light Trail Learning Test

Objetivo: El presente estudio tiene como objetivo proporcionar normas y ajustes para edad, educación y género para el Wisconsin Card Sorting Test (WCST), la Figura Compleja Modificada de Taylor (FCMT) y el Ruff-Light Trail Learning Test (RULIT) como parte del proyecto NEURONORMA-Plus. Método: La muestra consiste en 308 individuos cognitivamente sanos de entre 18 y 92 años. Se proporcionan tablas para convertir las puntuaciones brutas en puntuaciones escalares ajustadas por edad y ajustes por educación y género tras aplicar modelos de regresión independientes en 2 grupos de edad (< 50 y ≥ 50 años). Resultados: La edad tuvo un efecto negativo en el rendimiento en ambos grupos etarios. Observamos un efecto positivo de la educación en el rendimiento del WCST en el grupo más joven (< 50 años), y en todas las medidas del FCMT (con la excepción de la tarea de reconocimiento) en el grupo de mayor edad (≥ 50 años). La educación no influyó en el rendimiento en el RULIT, pero sí el género, que tuvo un efecto leve, aunque significativo, mostrando los hombres jóvenes un mayor rendimiento en una variable. Conclusión: Los datos normativos aportados pueden contribuir en la interpretación clínica del rendimiento en estas pruebas en población española.(AU)

Objective: The present study aims to provide norms and age-, education-, and sex-adjusted data for the Wisconsin Card Sorting Test (WCST), the Modified Taylor Complex Figure (MTCF), and the Ruff-Light Trail Learning Test (RULIT) as part of the NEURONORMA-Plus project. Methods: We recruited 308 cognitively healthy individuals aged between 18 and 92 years. Tables are provided to convert raw scores to age-adjusted scaled scores, as well as adjustments for education and sex after applying independent regression models in 2 age groups (< 50 and ≥ 50 years). Results: Older age had a negative effect on performance in both age groups. We observed a positive effect of education on WCST performance in the younger group (< 50 years), and on all MTCF measures (with the exception of the recognition task) in the older group (≥ 50 years). Education had no impact on performance in the RULIT, although sex did, with a small but significant effect whereby young men showed higher performance for one variable. Conclusion: The normative data provided can contribute to the clinical interpretation of performance in these tests in the Spanish population.(AU)

Prediction and simulation of PEEP setting effects with machine learning models / Predicción y simulación de los efectos de la configuración de la PEEP con modelos de aprendizaje automático

Objective To establish a new machine learning-based method to adjust positive end-expiratory pressure (PEEP) using only already routinely measured data. Design Retrospective observational study. Setting Intensive care unit (ICU). Patients or participants 51811 mechanically ventilated patients in multiple ICUs in the USA (data from MIMIC-III and eICU databases). Interventions No interventions. Main variables of interest Success parameters of ventilation (arterial partial pressures of oxygen and carbon dioxide and respiratory system compliance). Results The multi-tasking neural network model performed significantly best for all target tasks in the primary test set. The model predicts arterial partial pressures of oxygen and carbon dioxide and respiratory system compliance about 45 min into the future with mean absolute percentage errors of about 21.7%, 10.0% and 15.8%, respectively. The proposed use of the model was demonstrated in case scenarios, where we simulated possible effects of PEEP adjustments for individual cases. Conclusions Our study implies that machine learning approach to PEEP titration is a promising new method which comes with no extra cost once the infrastructure is in place. Availability of databases with most recent ICU patient data is crucial for the refinement of prediction performance. (AU)

Objetivo Establecer un nuevo método basado en el aprendizaje automático para ajustar la presión positiva al final de la espiración (PEEP según sus siglas en inglés) utilizando únicamente datos ya obtenidos de forma rutinaria. Diseño Estudio retrospectivo de observación. Ámbito Unidad de cuidados intesivos (UCI) Pacientes o participantes 51811 pacientes ventilados mecánicamente en múltiples UCIs de EE.UU. (tomados de las bases de datos MIMIC-III y eICU). Intervenciones Sin intervenciones. Variables de interés principales Parametros de éxito de la ventilación (presiones parciales arteriales de oxígeno y dióxido de carbono y distensibilidad del sistema respiratorio). Resultados El modelo de red neuronal multitarea obtuvo los mejores resultados en todos los objetivos del conjunto de pruebas primario. El modelo predice las presiones parciales arteriales de oxígeno y dióxido de carbono así como la distensibilidad del sistema respiratorio con aproximadamente 45 minutos de anticipación, mostrando errores porcentuales absolutos medios de aproximadamente 21.7%, 10.0% y 15.8%, respectivamente. El uso propuesto del modelo se demostró en situaciones hipotéticas en las que se simularon los posibles efectos de los ajustes de PEEP para casos individuales. Conclusiones Nuestro estudio implica que el enfoque de aprendizaje automático para el ajuste de la PEEP es un método nuevo y prometedor que no supone ningún coste adicional una vez que se dispone de la infraestructura necesaria. La disponibilidad de bases de datos con información de pacientes de UCI más recientes es crucial para perfeccionar el rendimiento de la predicción. (AU)

Satisfacción de los estudiantes de Odontología con el aprendizaje blended-learning en la Universidad San Sebastián, Chile / Student satisfaction with blended-learning in dentistry education in San Sebastian University, Chile

Introducción: La asignatura de Preclínico y Rehabilitación de la licenciatura de Odontología de la Universidad San Sebastián (Chile) prepara a los estudiantes para el desarrollo de habilidades prácticas que permiten el trabajo clínico con pacientes. En el año académico 2020-2021, posterior a la cuarentena por COVID-19, se mantuvo el curso en un entorno de aprendizaje en línea y con carácter semipresencial, apoyándose en un enfoque de aula invertida incorporando la estrategia blended-learning (B-learning). Objetivo: Evaluar la satisfacción del estudiantado con respecto a las actividades prácticas en modalidad B-learning.Materiales y métodos. Se realizó un estudio descriptivo-observacional. Se analizó el programa de la asignatura para desarrollar diversos recursos que se alojaron en una plataforma learning management system para efectuar una metodología de aula invertida. En 2022 se aplicó un instrumento en línea a 143 estudiantes con 18 ítems, en los que se usó una escala de tipo Likert para valorar su satisfacción en relación con la modalidad B-learning utilizada en la asignatura de Preclínico y Rehabilitación. Resultados: De 143 estudiantes inscritos en el curso 2021, contestaron 77. Se evidenció una buena consistencia internadel instrumento a través de un análisis del alfa de Cronbach (0,9). Para la subdimensión satisfacción con el aprendizaje se obtuvo una alta satisfacción, un 82,56%; un 86,75% en el ámbito de las metodologías y recursos; y un 94,38% para elproceso docente. Conclusiones: La modalidad B-learning se consideró satisfactoria para el estudiantado. El instrumento utilizado mostróuna buena consistencia interna, lo que permite retroalimentar procesos educativos.(AU)

Introduction: The Preclinical and Rehabilitation course in the Dentistry Degree at the University San Sebastian in Chile, prepares students for the development of practical skills essential for clinical work with patients. In the academic year 2020-2021, following the COVID-19 quarantine, the course was conducted in a blended learning environment, combining online and semi-presential aspects, employing a flipped classroom approach with the integration of blended learning (B-learning) strategy. Objective: To assess student satisfaction regarding practical activities in the B-learning mode.Materials and methods. A descriptive-observational study was conducted. The course program was analyzed to develop various resources hosted on a learning management system platform to implement a flipped classroom methodology. In 2022, an online instrument with 18 items, using a Likert scale, was administered to 143 students to assess their satisfaction with the B-learning mode in the Preclinical and Rehabilitation course. Results: Out of 143 enrolled students in the 2021 academic year, 77 responded. The instrument showed good internal consistency through Cronbach’s alpha analysis (0.9). For the satisfaction with learning sub-dimension, high satisfaction rates were obtained (82.56%), 86.75% for methodologies and resources, and 94.38% for the teaching process. Conclusions: The B-learning mode was considered satisfactory for the students. The instrument used demonstrated good internal consistency, providing feedback for educational processes.(AU)

Teaching radiology in integrated educational programs.

Radiology is a medical discipline, an area of transversal knowledge integrated into any clinical situation. The optimal training of learning knowledge, skills and aptitudes in Radiology in the Degree in Medicine requires the integration of any imaging modality in the different areas of knowledge; from the basic subjects to any clinical subject of the Degree. This article describes the integration of Radiology teaching into the curriculum throughout the Medicine Degree at the University of Girona (UdG), describing the different radiology teaching activities that are taught. The specific activities of the subject "Radiology" are detailed; through workshops, seminars, practices, interactive computer game; and describing the characteristics of the main teaching methodological activity of the UdG, Problem-Based Learning.

Examen Práctico Objetivo Estructurado como metodología de evaluación en la asignatura de Anatomía Humana: Experiencia de una Implementación Piloto

Aprendizajes en anatomía humana tradicionalmente han sido evaluados a través del reconocimiento de estructuras anatómicas. A pesar de su popularidad, pueden tener un componente subjetivo y memorístico. El Examen Práctico Objetivo Estructurado (EPOE) se ha presentado como una manera más global de evaluación. El objetivo de este estudio fue evidenciar el efecto en el rendimiento académico tras la implementación del EPOE en pasos prácticos. En el estudio 2312 estudiantes fueron divididos: Metodología Tradicional (n=1155) y Metodología EPOE (n=1157). A su vez, los estudiantes fueron identificados según carrera: Enfermería (n=1182); Fonoaudiología (n=185); Kinesiología (n=514) y Terapia Ocupacional (n=431). Se mantuvieron las condiciones de la asignatura en ambos grupos con tres evaluaciones prácticas. Se analizaron las calificaciones obtenidas. Evaluaciones 1 y 2 no presentaron diferencias entre grupos. Evaluación 3, que evaluó sistema nervioso, mostró disminución significativa de 0,5 puntos en el grupo EPOE. El factor tipo de metodología resultó ser significativo en evaluación 3 (p < 0,001; h2p = 0,029) y promedio de las 3 evaluaciones (p < 0,029; h2p = 0,002). El factor carrera resultó ser significativo para las tres evaluaciones. La interacción de ambos factores no mostró significancia estadística. El análisis post hoc mostró diferencias significativas entre estudiantes de Enfermería con las demás carreras, ya que obtuvieron mejores calificaciones en todas las evaluaciones (p < 0,05). Metodología EPOE no produjo drásticos cambios en el rendimiento académico de los estudiantes y tiene un amplio potencial de desarrollo por su naturaleza de evaluación integral no invasiva ni traumática. Se debe considerar la naturaleza de los contenidos en el diseño de la metodología de enseñanza-aprendizaje y en la metodología de evaluación, alineando a nivel microcurricular estos aspectos fundamentales de la formación de nuevos profesionales de la salud.

SUMMARY: Learning in human anatomy has traditionally been assessed by recognizing anatomical structures. Despite their popularity, they can have a subjective component. The Objective Structured Practical Examination (EPOE) has been presented as a more global way of assessment. The aim of this study was to demonstrate the effect on academic performance after the implementation of the EPOE in practical activities. In this study 2312 students were divided into Traditional Methodology (n=1155) and EPOE Methodology (n=1157). In turn, students were identified according to career: Nursing (n=1182), Speech Therapy (n=185), Physical Therapy (n=514), and Occupational Therapy (n=431). Subject conditions were maintained in both groups with three practical evaluations. The grades obtained were analyzed. Assessments 1 and 2 showed no differences between groups. Evaluation 3, which evaluated the nervous system, showed a significant decrease of 0.5 points in the EPOE group. The type of methodology factor was significant in evaluation 3 (p < 0.001; ?2p = 0.029) and the average of 3 evaluations (p < 0.029; ?2p = 0.002). The career factor was significant for all three evaluations. The interaction of both factors did not show statistical significance. The post hoc analysis showed significant differences between nursing students and the other careers since they obtained better scores in all evaluations (p < 0.05). EPOE methodology did not produce drastic changes in students' academic performance and had a broad potential for development due to its non-invasive and non-traumatic comprehensive assessment nature. The nature of the contents should be considered in the design of the teaching-learning methodology and the evaluation methodology, aligning at the micro-curricular level with these fundamental aspects of training new health professionals.

Wiki educativa para la Clínica Virtual de Salud de Santiago de Cuba

El programa de las tecnologías de la información y las comunicaciones se ha implementado en todas las instituciones pertenecientes al sector de la salud en Cuba, pues favorece la formación a través de los entornos de enseñanza y aprendizaje en función del desarrollo y las perspectivas académicas, mediante plataformas tecnológicas para facilitar el intercambio de información. En el presente artículo se destaca la necesidad de incrementar el uso de la wiki como herramienta educativa, que favorece el aprendizaje colaborativo como un proceso de creación de conocimiento a través de la web 2.0, donde no solo se publican contenidos sino que contribuye a desarrollar habilidades de cooperación en los procesos formativos de la salud pública.

The program of information and communications technologies has been implemented in all the institutions belonging to the health sector in Cuba, because it favors the training through the teaching and learning environments in function of development and academic perspectives, by means of technological platforms to facilitate the exchange of information. In this work the necessity to increase the wiki use as educational tool in enhanced, that favors the collaborative learning as a process of knowledge creation through the web 2.0, where contents are not only published but also contributes to develop cooperation abilities in the training processes of public health.

Current perspectives on the use of artificial intelligence in critical patient safety.

Intensive Care Units (ICUs) have undergone enhancements in patient safety, and artificial intelligence (AI) emerges as a disruptive technology offering novel opportunities. While the published evidence is limited and presents methodological issues, certain areas show promise, such as decision support systems, detection of adverse events, and prescription error identification. The application of AI in safety may pursue predictive or diagnostic objectives. Implementing AI-based systems necessitates procedures to ensure secure assistance, addressing challenges including trust in such systems, biases, data quality, scalability, and ethical and confidentiality considerations. The development and application of AI demand thorough testing, encompassing retrospective data assessments, real-time validation with prospective cohorts, and efficacy demonstration in clinical trials. Algorithmic transparency and explainability are essential, with active involvement of clinical professionals being crucial in the implementation process.

Utility of artificial intelligence for detection of pneumothorax on chest radiopgraphs done after transthoracic percutaneous transthoracic biopsy guided by computed tomography.

OBJETIVE: To assess the ability of an artificial intelligence software to detect pneumothorax in chest radiographs done after percutaneous transthoracic biopsy. MATERIAL AND METHODS: We included retrospectively in our study adult patients who underwent CT-guided percutaneous transthoracic biopsies from lung, pleural or mediastinal lesions from June 2019 to June 2020, and who had a follow-up chest radiograph after the procedure. These chest radiographs were read to search the presence of pneumothorax independently by an expert thoracic radiologist and a radiodiagnosis resident, whose unified lecture was defined as the gold standard, and the result of each radiograph after interpretation by the artificial intelligence software was documented for posterior comparison with the gold standard. RESULTS: A total of 284 chest radiographs were included in the study and the incidence of pneumothorax was 14.4%. There were no discrepancies between the two readers' interpretation of any of the postbiopsy chest radiographs. The artificial intelligence software was able to detect 41/41 of the present pneumothorax, implying a sensitivity of 100% and a negative predictive value of 100%, with a specificity of 79.4% and a positive predictive value of 45%. The accuracy was 82.4%, indicating that there is a high probability that an individual will be adequately classified by the software. It has also been documented that the presence of Port-a-cath is the cause of 8 of the 50 of false positives by the software. CONCLUSIONS: The software has detected 100% of cases of pneumothorax in the postbiopsy chest radiographs. A potential use of this software could be as a prioritisation tool, allowing radiologists not to read immediately (or even not to read) chest radiographs classified as non-pathological by the software, with the confidence that there are no pathological cases.