Análisis de los estilos de aprendizaje en un curso de habilidades técnicas laparoscópicas. Implicaciones para el entrenamiento quirúrgico / Analysis of learning styles in a laparoscopic technical skills course. Implications for surgical training

Introducción: El aprendizaje de las técnicas quirúrgicas es un proceso dinámico. David Kolb describió en los años ochenta un modelo de aprendizaje que permite adaptar el tipo de enseñanza y mejorar los resultados de esta. El objetivo del estudio es identificar los estilos de aprendizaje según Kolb de los participantes en un curso de habilidades técnicas laparoscópicas y comprobar si existe relación con el rendimiento final de la tarea realizada. Métodos: Estudio observacional descriptivo que incluye 64 participantes que completaron un curso intensivo donde realizaron anastomosis intestinales manuales laparoscópicas. Todos ellos completaron el inventario de estilos de aprendizaje de Kolb. En cada anastomosis se recogió el tiempo de ejecución y se valoró su calidad. Posteriormente, los datos fueron analizados estadísticamente. Resultados: El estilo de aprendizaje más frecuente fue el asimilador (39,1%). No se observan diferencias significativas entre los estilos y el sexo de los participantes, su categoría profesional, el tiempo en realizar la anastomosis o su calidad. Conclusiones: El estilo de aprendizaje predominante es el asimilador, sin diferencias entre categorías, edad o sexo. No existe relación entre el estilo de aprendizaje de los participantes y los resultados obtenidos en el curso. (AU)

Introduction: Learning surgical techniques is a dynamic process. In the 1980s David Kolb described developed a learning model that enabled teaching styles to adapt for better learner outcomes. The aim of this study was to identify the Kolb learning styles of the participants in a laparoscopic technical skills course and to check see if there was any relationship with performance. Methods: An observational descriptive study was conducted with 64 participants in an intensive course in which they performed laparoscopic manual intestinal anastomoses. All completed Kolb's inventory of learning styles. For each anastomosis, join quality was assessed and the performing time recorded. After that, they were analyzed through statistical studies. Results: The most frequent learning style was assimilating type (39.1%). No significant differences were observed between different learning styles and gender, professional category, the time taken or the quality of the anastomoses. Conclusions: Assimilating type was the most frequent Kolb learning style, with no differences observed between categories, age or gender. There is no relationship between the learning style of the participants and the results obtained in the course. (AU)

Analysis of learning styles in a laparoscopic technical skills course. Implications for surgical training.

INTRODUCTION: Learning surgical techniques is a dynamic process. In the 1980s David Kolb described developed a learning model that enabled teaching styles to adapt for better learner outcomes. The aim of this study was to identify the Kolb learning styles of the participants in a laparoscopic technical skills course and to check see if there was any relationship with performance. METHODS: An observational descriptive study was conducted with 64 participants in an intensive course in which they performed laparoscopic manual intestinal anastomoses. All completed Kolb's inventory of learning styles. For each anastomosis, join quality was assessed and the performing time recorded. After that, they were analyzed through statistical studies. RESULTS: The most frequent learning style was assimilating type (39.1%). No significant differences were observed between different learning styles and gender, professional category, the time taken or the quality of the anastomoses. CONCLUSIONS: Assimilating type was the most frequent Kolb learning style, with no differences observed between categories, age or gender. There is no relationship between the learning style of the participants and the results obtained in the course.

Analysis of learning styles in a laparoscopic technical skills course. Implications for surgical training. / Análisis de los estilos de aprendizaje en un curso de habilidades técnicas laparoscópicas. Implicaciones para el entrenamiento quirúrgico.

INTRODUCTION: Learning surgical techniques is a dynamic process. In the 1980s David Kolb described developed a learning model that enabled teaching styles to adapt for better learner outcomes. The aim of this study was to identify the Kolb learning styles of the participants in a laparoscopic technical skills course and to check see if there was any relationship with performance. METHODS: An observational descriptive study was conducted with 64 participants in an intensive course in which they performed laparoscopic manual intestinal anastomoses. All completed Kolb's inventory of learning styles. For each anastomosis, join quality was assessed and the performing time recorded. After that, they were analyzed through statistical studies. RESULTS: The most frequent learning style was assimilating type (39.1%). No significant differences were observed between different learning styles and gender, professional category, the time taken or the quality of the anastomoses. CONCLUSIONS: Assimilating type was the most frequent Kolb learning style, with no differences observed between categories, age or gender. There is no relationship between the learning style of the participants and the results obtained in the course.

Continuous Detection of Increasing Concentrations of Thrombin Employing a Label-Free Photonic Crystal Aptasensor.

Thrombin generation is a complex and finely regulated pathway that provokes dynamical changes of thrombin concentration in blood when a vascular injury occurs. In order to characterize the initiation phase of such process, when thrombin concentration is in the nmol/L range, a label-free optical aptasensor is proposed here. This aptasensor combines a 1D photonic crystal structure consisting of a silicon corrugated waveguide with thrombin binding aptamers on its surface as bioreceptors. As a result, this aptasensor has been demonstrated to specifically detect thrombin concentrations ranging from 270 pmol/L to 27 nmol/L with an estimated detection limit of 33.5 pmol/L and a response time of ~2 min. Furthermore, it has also been demonstrated that this aptasensor is able to continuously respond to consecutive increasing concentrations of thrombin and to detect binding events as they occur. All these features make this aptasensor a good candidate to continuously study how thrombin concentration progressively increases during the initiation phase of the coagulation cascade.

Stabilization of Polymeric Nanofibers Layers for Use as Real-Time and In-Flow Photonic Sensors.

In order to increase the sensitivity of a sensor, the relationship between its volume and the surface available to be functionalized is of great importance. Accordingly, porous materials are becoming very relevant, because they have a notable surface-to-volume ratio. Moreover, they offer the possibility to infiltrate the target substances on them. Among other porous structures, polymeric nanofibers (NFs) layers fabricated by electrospinning have emerged as a very promising alternative to low-cost and easy-to-produce high-performance photonic sensors. However, experimental results show a spectrum drift when performing sensing measurements in real-time. That drift is responsible for a significant error when trying to determine the refractive index variation for a target solution, and, because of that, for the detection of the presence of certain analytes. In order to avoid that problem, different chemical and thermal treatments were studied. The best results were obtained for thermal steps at 190 °C during times between 3 and 5 h. As a result, spectrum drifts lower than 5 pm/min and sensitivities of 518 nm/refractive index unit (RIU) in the visible range of the spectrum were achieved in different electrospun NFs sensors.

Computational binding study of cardiac troponin I antibody towards cardiac versus skeletal troponin I.

A computational study of the interaction of cardiac troponin I (cTnI) with its specific antibody and of that antibody with skeletal troponin I (sTnI), the principal interferon of cTnI, is carried out. Computational and simulation tools such as FTSite, FTMap, FTDock and pyDock are used to determine the binding sites of these molecules and to study their interactions and molecular docking performance, allowing us to obtain relevant information related with the antigen-antibody interaction for each of the targets. In the context of the development of immunosensing platforms, this type of computational analysis allows performing a preliminary in-silico affinity study of the available bioreceptors for a better selection when moving to the experimental stage, with the subsequent saving in cost and time.

Commercial polycarbonate track-etched membranes as substrates for low-cost optical sensors.

Porous materials have become one of the best options for the development of optical sensors, since they maximize the interaction between the optical field and the target substances, which boosts the sensitivity. In this work, we propose the use of a readily available mesoporous material for the development of such sensors: commercial polycarbonate track-etched membranes. In order to demonstrate their utility for this purpose, we firstly characterized their optical response in the near-infrared range. This response is an interference fringe pattern, characteristic of a Fabry-Pérot interferometer, which is an optical device typically used for sensing purposes. Afterwards, several refractive index sensing experiments were performed by placing different concentrations of ethanol solution on the polycarbonate track-etched membranes. As a result, a sensitivity value of around 56 nm/RIU was obtained and the reusability of the substrate was demonstrated. These results pave the way for the development of optical porous sensors with such easily available mesoporous material.