Benefits of the dog-assisted therapy on the hospitalized pediatric population

Trabajo fin de grado en EnfermeríaIntroducción: la compañía de los animales se ha relacionado siempre con ciertos beneficios, los cuales se han empezado a estudiar con el fin de poder aplicarlos de manera terapéutica, surgiendo así la Terapia Asistida con Animales, y más concretamente, la Terapia Asistida con Perros, ya que es una de las más usadas actualmente. Objetivo: realizar una revisión bibliográfica para conocer los beneficios que la Terapia Asistida con Perros puede tener sobre la población pediátrica hospitalizada. Metodología: para desarrollar esta revisión narrativa se realizó una búsqueda bibliográfica en las bases de datos PubMed, CUIDEN, SciELO, CINHAL y Cochrane a partir de términos MeSH y DeCS combinados con los operadores booleanos “AND” y “OR”. Se encontraron 11 artículos que cumplían los criterios de inclusión y que resultaron útiles para verificar los objetivos planteados. Resultados: los resultados obtenidos fueron clasificados según las características de los pacientes en aspectos como la edad y la patología que tienen, los beneficios obtenidos de la Terapia Asistida con Perros en estos pacientes y las características de las intervenciones como la duración, el número de sesiones, la raza de los perros y las actividades realizadas durante la sesión. Discusión: se estudió la Terapia Asistida con Perros en pacientes de pediatría sometidos a una intervención quirúrgica y pacientes de psiquiatría principalmente. Se vieron beneficios como disminución del dolor, la ansiedad y aumento de la socialización con sesiones de entre 5 y 20 minutos con el perro. Conclusiones: con esta revisión narrativa se ha podido comprobar que la Terapia Asistida con Perros puede producir beneficios tanto a nivel fisiológico como psicológico en pacientes de pediatría de entre 3 y 18 años que se encuentran hospitalizados por diversos motivos.Introduction: the company of animals has always been related to certain benefits, which have began to be studied in order to be able to apply them in a therapeutic way, thus emerging the Animal Assisted Therapy, and more specifically, Dog-Assisted Therapy, because it is one of the most used currently. Objective: Carry out a bibliographic review to know the benefits that the Dog-Assisted Therapy may have on the hospitalized pediatric population. Methodology: to develop this narrative review a literature research was performed in data bases such as PubMed, CUIDEN, SciELO, CINHAL and Cochrane using MeSH and DeCS terms combined with the boolean operators “AND” and “OR”. Eleven articles that met the inclusion criteria and were useful to verify the objectives were found. Results: the results obtained were classified according to the characteristics of the patients in aspects such as their age and pathology, the benefits obtained from the Dog-Assisted Therpay in these patients and the characteristics of the interventions such as the length, the number of sessions, the dog’s breed and the activities taken during the sessions. Discussion: Dog-Assisted Therapy was studied in pediatric patients undergoing surgical intervention and psychiatry patients mainly. Benefits such us decrease pain, anxiety and increased socialization with sessions of between 5 and 20 minutes were seen. Conclusions: with this bibliographic review it has been proved that the Dog-Assisted Therapy may produce physiological and psychological benefits on pediatric patients between 3 and 18 years old that are hospitalized for different reason

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts