Interval assessment using task- and procedure-based simulations: an attempt to supplement neurosurgical residency curriculum.

OBJECTIVE: The longer learning curve and smaller margin of error make nontraditional, or "out of operating room" simulation training, essential in neurosurgery. In this study, the authors propose an evaluation system for residents combining both task-based and procedure-based exercises and also present the perception of residents regarding its utility. METHODS: Residents were evaluated using a combination of task-based and virtual reality (VR)-based exercises. The results were analyzed in terms of the seniority of the residents as well as their laboratory credits. Questionnaire-based feedback was sought from the residents regarding the utility of this evaluation system incorporating the VR-based exercises. RESULTS: A total of 35 residents were included in this study and were divided into 3 groups according to seniority. There were 11 residents in groups 1 and 3 and 13 residents in group 2. On the overall assessment of microsuturing skills including both 4-0 and 10-0 microsuturing, the suturing skills of groups 2 and 3 were observed to be better than those of group 1 (p = 0.0014). Additionally, it was found that microsuturing scores improved significantly with the increasing laboratory credits (R2 = 0.72, p < 0.001), and this was found to be the most significant for group 1 residents (R2 = 0.85, p < 0.001). Group 3 residents performed significantly better than the other two groups in both straight (p = 0.02) and diagonal (p = 0.042) ring transfer tasks, but there was no significant difference between group 1 and group 2 residents (p = 0.35). Endoscopic evaluation points were also found to be positively correlated with previous laboratory training (p = 0.002); however, for the individual seniority groups, the correlation failed to reach statistical significance. The 3 seniority groups performed similarly in the cranial and spinal VR modules. Group 3 residents showed significant disagreement with the utility of the VR platform for improving surgical dexterity (p = 0.027) and improving the understanding of surgical procedures (p = 0.034). Similarly, there was greater disagreement for VR-based evaluation to identify target areas of improvement among the senior residents (groups 2 and 3), but it did not reach statistical significance (p = 0.194). CONCLUSIONS: The combination of task- and procedure-based assessment of trainees using physical and VR simulation models can supplement the existing neurosurgery curriculum. The currently available VR-based simulations are useful in the early years of training, but they need significant improvement to offer beneficial learning opportunities to senior trainees.

Can financial crisis be detected? Laplacian energy measure

How to rapidly and accurately detect the financial crisis is one of the fundamental and challenging problems in the field of financial risk management. This paper aims to develop a novel network characteristic indicator to deal with this issue. Specifically, we select the daily closing price of stocks spanning from 2006 to 2020 in China’s A-share market to establish a series of complex networks, and extract Laplacian energy measure as a new network indicator. By employing the method of seasonal-trend decomposition procedure based on loess, the proposed indicator successfully detects the global financial crisis, the Eurozone debt crisis, the Chinese stock market crash, the Sino-US trade friction and the COVID-19 pandemic. Furthermore, compared with the traditional topological indicators (e.g. global efficiency, average clustering coefficient, characteristic path length and network density), the proposed indicator demonstrates the outstanding characteristics of higher identification accuracy, wider application range and faster response speed. Lastly, the robustness of the Laplacian energy measure in the financial crisis detection is further confirmed in the US, UK, German, French and Spanish stock markets. © 2022 Informa UK Limited, trading as Taylor & Francis Group.