ABSTRACT
BACKGROUND: EuroSCORE II is a mortality risk score for cardiac surgery in adults. This version is widely validated and compared with other scores in Europe, North America, and Asia. AIM: To determine the performance of the EuroSCORE II for the prediction of mortality in cardiac surgeries in Latin America. MATERIAL AND METHODS: A systematic review was carried out of studies from Latin American countries evaluating the performance of EuroSCORE II in cardiac surgery. The inclusion criteria were patients older than 18 years, from Latin America, published in English, Spanish and/or Portuguese, between the years 2012 to 2020, with the term "EuroSCORE II" in the title. Observed mortality and estimated mortality data by EuroSCORE II were extracted. The calibration was determined by the observed/estimated mortality ratio and the discrimination was evaluated using receiver operating characteristic (ROC) curves. RESULTS: Four articles met the inclusion criteria, including 8372 patients. The average patients' age was 62 years and 34% were women. The observed and Euroscore II estimated mortality figures were 7.08 and 3.89%, respectively. The average area under the curve of ROC curves was 0.77 and the observed/ estimated mortality ratio was 2.04. CONCLUSIONS: In these studies, EuroSCORE II underestimated mortality in cardiac surgery.
Subject(s)
Humans , Male , Female , Adult , Middle Aged , Cardiac Surgical Procedures , Risk Factors , ROC Curve , Hospital Mortality , Risk Assessment , Latin AmericaABSTRACT
In health sciences and medicine, collaborative learning has an important role in the development of competences to solve clinical situations. Adequate cooperation, coordination and communication skills have a direct effect on patient safety. Computer Supported Collaborative Learning (CSCL) and Clinical Simulation (CS), separately, are effective and efficient educational methods to develop competences in undergraduate medical students. To our knowledge, educational models that combine both teaching methods, including a personalized attention of the student, educational infrastructure, materials, teaching techniques and assessment competencies, have not been proposed previously. This article describes the application of a combined model of CSCL and CS for teaching clinical competences to medical students. Since 2015, the collaborative clinical simulation model is part of the training agenda of the Universidad de Talca Medical School in Chile. During 2016 and 2017 it was also applied on students of the Universidad de Barcelona Faculty of Medicine in Spain. According to the experience acquired, implementation of this method is feasible with commonly used resources, although its real efficacy remains to be evaluated.
Subject(s)
Humans , Teaching , Computer-Assisted Instruction/methods , Clinical Competence , Models, Educational , Education, Medical, Undergraduate/methods , Personal Satisfaction , SpainABSTRACT
After the progress made during the genomics era, bioinformatics was tasked with supporting the flow of information generated by nanobiotechnology efforts. This challenge requires adapting classical bioinformatic and computational chemistry tools to store, standardize, analyze, and visualize nanobiotechnological information. Thus, old and new bioinformatic and computational chemistry tools have been merged into a new sub-discipline: nanoinformatics. This review takes a second look at the development of this new and exciting area as seen from the perspective of the evolution of nanobiotechnology applied to the life sciences. The knowledge obtained at the nano-scale level implies answers to new questions and the development of new concepts in different fields. The rapid convergence of technologies around nanobiotechnologies has spun off collaborative networks and web platforms created for sharing and discussing the knowledge generated in nanobiotechnology. The implementation of new database schemes suitable for storage, processing and integrating physical, chemical, and biological properties of nanoparticles will be a key element in achieving the promises in this convergent field. In this work, we will review some applications of nanobiotechnology to life sciences in generating new requirements for diverse scientific fields, such as bioinformatics and computational chemistry.