SI-EPI is epidemiological information system set up in 1978 in the national electricity and gas company, Electricité de France-Gaz de France (EDF-GDF). The worker population comprises about 150,000 individuals, involved in production, transmission and distribution of energy. SI-EPI was developed by the epidemiologists of the Occupational Health Department (180 physicians), and of the Sécurité Sociale Department (120 physicians). Several data bases constitute SI-EPI. The population data base contains demographic, socioeconomic and professional data about each worker. The health data base is an exhaustive register of sick leave, accidents, permanent disabilities, compensated diseases, causes of death and cancer incidence among active workers. The Occupational Exposure and Working Conditions data base includes the MATEX job-exposure matrix (30 potentially carcinogenic agents) and FINDEX files which record data obtained from the systematic individual surveillance of workers. The GAZEL cohort data base concerns a sample of more than 20,000 volunteer workers, followed since 1989; in addition to data from the data bases, it contains information collected from other different sources, including self-questionnaires. Numerous epidemiological studies based on SI-EPI data have been conducted by in-house epidemiologists as well as by external research groups. They include mortality and morbidity studies and address various topics and health problems. Their results are used for internal information, as well as for epidemiological research purposes.
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Surg Endosc
December 2024
Cancer Center Amsterdam, Amsterdam, Netherlands.
Background: The surgical management of complicated diverticulitis varies across Europe. EAES members prioritized this topic to be addressed by a clinical practice guideline through an online questionnaire.
Objective: To develop evidence-informed clinical practice recommendations for key stakeholders involved in the treatment of complicated diverticulitis; to improve operative and perioperative outcomes, patient experience and quality of life through a systematic evidence-to-decision approach by a diverse, multidisciplinary panel.
Sci Rep
December 2024
School of Civil and Hydraulic Engineering, Chongqing University of Science & Technology, Chongqing, 400074, China.
The CRTS (China Railway Track System) II slab ballastless track is widely utilized in high-speed railway construction owing to its excellent structural integrity. However, its interfacial performance deteriorates under high-temperature conditions, leading to significant damage in structural details. Furthermore, the evolution of its performance under these conditions has not been comprehensively studied.
View Article and Find Full Text PDFChronic heart failure (CHF) represents one of the most severe and advanced stages of cardiovascular disease. Despite the critical importance of cardiac rehabilitation (CR) in CHF management, while studies have explored the effectiveness of various CR delivery modes and offered valuable context-specific insights, their relative efficacy remains inconsistent across different patient groups, healthcare environments, and intervention approaches. A clearer understanding requires comprehensive comparisons and in-depth analyses to address these variations.
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December 2024
Department of Endocrinology and Metabolism, Chengdu First People's Hospital, No.18 North Vientiane Road, High-Tech Zone, Chengdu, 610000, Sichuan, China.
We aimed to determine the association between anion gap-to-calcium ratio (ACR) and 30-day mortality in sepsis patients with diabetes mellitus (DM). Data for sepsis patients diagnosed with DM was extracted from Medical Information Mart for Intensive Care Database IV. After screening, 4429 eligible subjects were included in our study finally.
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December 2024
School of Computer Science and Information Engineering, Harbin Normal University, Harbin, 150025, China.
Accurately identifying bearing faults in aeroengines is crucial for maintaining their lifespan and cost. However, most current models are black-box models, such as deep learning models such as deep neural networks. The decision-making process of these models is more complex and lacks interpretability, which results in insufficient credibility of the results.
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