RESUMO
The present study aims to evaluate the accuracy of the prognostic discrimination and prediction of the short-term mortality of the Marshall computed tomography (CT) classification and Rotterdam and Helsinki CT scores in a cohort of TBI patients from a low- to middle-income country. This is a post hoc analysis of a previously conducted prospective cohort study conducted in a university-associated, tertiary-level hospital that serves a population of >12 million in Brazil. Marshall CT class, Rotterdam and Helsinki scores, and their components were evaluated in the prediction of 14-day and in-hospital mortality using Nagelkerk's pseudo-R 2 and area under the receiver operating characteristic curve. Multi-variate regression was performed using known outcome predictors (age, Glasgow Coma Scale, pupil response, hypoxia, hypotension, and hemoglobin values) to evaluate the increase in variance explained when adding each of the CT classification systems. Four hundred forty-seven patients were included. Mean age of the patient cohort was 40 (standard deviation, 17.83) years, and 85.5% were male. Marshall CT class was the least accurate model, showing pseudo-R 2 values equal to 0.122 for 14-day mortality and 0.057 for in-hospital mortality, whereas Rotterdam CT scores were 0.245 and 0.194 and Helsinki CT scores were 0.264 and 0.229. The AUC confirms the best prediction of the Rotterdam and Helsinki CT scores regarding the Marshall CT class, which presented greater discriminative ability. When associated with known outcome predictors, Marshall CT class and Rotterdam and Helsinki CT scores showed an increase in the explained variance of 2%, 13.4%, and 21.6%, respectively. In this study, Rotterdam and Helsinki scores were more accurate models in predicting short-term mortality. The study denotes a contribution to the process of external validation of the scores and may collaborate with the best risk stratification for patients with this important pathology.
RESUMO
OBJECTIVE: Neurosurgical training requires several years of supervised procedures and represents a long and challenging process. The development of surgical simulation platforms is essential to reducing the risk of potentially intraoperative severe errors arising from inexperience. To present and perform a phase I validation process of a mixed reality simulation (realistic and virtual simulators combined) for neuroendoscopic surgical training. METHODS: Tridimensional videos were developed by the 3DS Max program. Physical simulators were made with a synthetic thermoretractile and thermosensible rubber, which, when combined with different polymers, produces >30 different textures that simulate consistencies and mechanical resistance of human tissues. Questionnaires regarding the role of virtual and realistic simulators were applied to experienced neurosurgeons to assess the applicability of the mixed-reality simulation for neuroendoscopic surgical training. RESULTS: The model was considered as a potential tool for training new residents in neuroendoscopic surgery. It was also adequate for practical application with inexperienced surgeons. According to the overall score, 83% of the surgeons believed that the realistic physical simulator presents distortions when compared with the real anatomic structure, afterwards the model improved 66% tridimensional reconstruction and 66% reported that the virtual simulator allowed a multiangular perspective ability. CONCLUSIONS: This model provides a highly effective way of working with 3-dimensional data and significantly enhances the learning of surgical anatomy and operative strategies. The combination of virtual and realistic tools may safely improve and abbreviate the surgical learning curve.
