PURPOSE: To develop a series of recommendations for the contemporary management management of staghorn calculi and to provide a clinical framework for urologists treating patients with these complex stones.
METHODS: A comprehensive literature search for articles published in English between 01/01/1976 and 31/12/2022 in the PubMed, OVID, Embase and Medline database is performed. A series of recommendations are developed and individually graded following the review of literature and panel discussion.
RESULTS: The definition, pathogenesis, pathophysiology, preoperative evaluation, intraoperative treatment strategies and procedural advice, early postoperative management, follow up and prevention of stone recurrence are summarized in the present document.
CONCLUSION: A series of recommendations regarding the management of staghorn calculi, along with related commentary and supporting documentation offered in the present guideline is intended to provide a clinical framework for the practicing urologists in the management of staghorn calculi.
OBJECTIVES: In this paper, the Advanced Human-Robot Collaboration Model (AHRCM) approach is to enhance the risk assessment and to make the workplace involving security robots. The robots use perception cameras and generate scene diagrams for semantic depictions of their environment. Furthermore, Artificial Intelligence (AI) and Information and Communication Technology (ICT) have utilized to develop a highly protected security robot based risk management system in the workplace.
RESULTS: The experimental results show that the proposed AHRCM method achieves high performance in human-robot mutual adaption and reduce the risk.
CONCLUSION: Through an experiment in the field of human subjects, demonstrated that policies based on the proposed model improved the efficiency of the human-robot team significantly compared with policies assuming complete human-robot adaptation.
OBJECTIVE: This study aimed to explore the relationship between job stress, psychological capital, and professional identity through a mediation analysis of Chinese medical interns.
METHODS: A descriptive cross-sectional study was conducted in 30 hospitals and clinics in China from June 2021 to March 2022. A total of 665 medical interns filled out questionnaires related to demographic questions, psychological capital, job stress, and professional identity. Data analysis was executed using the IBM SPSS version 22.0 software and its add-in PROCESS Windows version 4.0.
RESULTS: The findings indicated a statistically significant mediating effect of psychological capital between job stress and professional identity. Job stress and job stress combined with psychological capital accounted for 5.3% and 37.9%, respectively, of the variance in professional identity. The bootstrapping method corroborated the significance of the indirect effect of job stress through psychological capital (95% bootstrap CI = -4.7921, -2.4345).
CONCLUSION: The current findings underscore the need for increased attention on improving the psychological capital of medical interns.
METHODS: Positron emission tomography (PET) and computed tomography (CT) image data from 97 patients with LC and 77 patients with TB nodules were collected. One hundred radiomic features were extracted from both PET and CT imaging using the pyradiomics platform, and 2048 deep learning features were obtained through a residual neural network approach. Four models included traditional machine learning model with radiomic features as input (traditional radiomics), a deep learning model with separate input of image features (deep convolutional neural networks [DCNN]), a deep learning model with two inputs of radiomic features and deep learning features (radiomics-DCNN) and a deep learning model with inputs of radiomic features and deep learning features and clinical information (integrated model). The models were evaluated using area under the curve (AUC), sensitivity, accuracy, specificity, and F1-score metrics.
RESULTS: The results of the classification of TB nodules and LC showed that the integrated model achieved an AUC of 0.84 (0.82-0.88), sensitivity of 0.85 (0.80-0.88), and specificity of 0.84 (0.83-0.87), performing better than the other models.
CONCLUSION: The integrated model was found to be the best classification model in the diagnosis of TB nodules and solid LC.
METHODS: 2010-2015 incidence data for influenza A (IAV), influenza B (IBV), respiratory syncytial (RSV) and parainfluenza (PIV) virus infections were collected from 18 sites (14 countries), consisting of local (n = 6), regional (n = 9) and national (n = 3) laboratories using molecular diagnostic methods. Each site submitted monthly virus incidence data, together with details of their patient populations tested and diagnostic assays used.
RESULTS: For the Northern Hemisphere temperate countries, the IAV, IBV and RSV incidence peaks were 2-6 months out of phase with those in the Southern Hemisphere, with IAV having a sharp out-of-phase difference at 6 months, whereas IBV and RSV showed more variable out-of-phase differences of 2-6 months. The tropical sites Singapore and Kuala Lumpur showed fluctuating incidence of these viruses throughout the year, whereas subtropical sites such as Hong Kong, Brisbane and Sydney showed distinctive biannual peaks for IAV but not for RSV and PIV.
CONCLUSIONS: There was a notable pattern of synchrony of IAV, IBV and RSV incidence peaks globally, and within countries with multiple sampling sites (Canada, UK, Australia), despite significant distances between these sites.