Objective To evaluate the application of the Huaxi Intelligent Endoscopic Skill Training and Assessment System in minimally invasive surgery (MIS) skills training and provide insights for optimizing MIS training models, we analyzed trainee performance during training and assessment. Methods A retrospective analysis was conducted on the use of this system across 28 medical institutions from January 2022 to January 2025. Results By January 2025, the standardized deployment of 139 simulation units had been completed. A total of 403 trainees from various surgical specialties, including thoracic surgery and general surgery, participated in five customized endoscopic skill training modules: endoscopic recognition, grasping training, positioning and placement, cutting training, and suturing training. Throughout the training period, a total of 78 participants took part in 27 formal assessments. Correlation analysis based on Spearman showed that pre-assessment training pass rates were significantly correlated with final assessment scores, indicating enhancing the quality of each training module and overall training efficacy is a key to improving the effectiveness of MIS training. Conclusion The Huaxi Intelligent Endoscopic Skill Training and Assessment System effectively supports MIS training and evaluation.
With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.
