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Background: Type 1 Brugada syndrome (BrS) is a hereditary arrhythmogenic disease showing peculiar electrocardiographic (ECG) patterns, characterized by ST-segment elevation in the right precordial leads, and risk of Sudden Cardiac Death (SCD). Furthermore, although various ECG patterns are described in the literature, different individual ECG may show high-grade variability, making the diagnosis problematic. The study aims to develop an innovative system for an accurate diagnosis of Type 1 BrS based on ECG pattern recognition by Machine Learning (ML) models and blood markers analysis trough transcriptomic techniques.Methods: The study is structured in 3 parts: (a) a retrospective study, with the first cohort of 300 anonymized ECG obtained in already diagnosed Type 1 BrS (75 spontaneous, 150 suspected) and 75 from control patients, which will be processed by ML analysis for pattern recognition; (b) a prospective study, with a cohort of 11 patients with spontaneous Type 1 BrS, 11 with drug-induced Type 1 BrS, 11 suspected BrS but negative to Na + channel blockers administration, and 11 controls, enrolled for ECG ML analysis and blood collection for transcriptomics and microvesicles analysis; (c) a validation study, with the third cohort of 100 patients (35 spontaneous and 35 drug-induced BrS, 30 controls) for ML algorithm and biomarkers testing.Discussion: The BrAID system will help clinicians improve the diagnosis of Type 1 BrS by using multiple information, reducing the time between ECG recording and final diagnosis, integrating clinical, biochemical and ECG information thus favoring a more effective use of available resources. Trial registration Clinical Trial.gov, NCT04641585. Registered 17 November 2020, https://clinicaltrials.gov/ct2/show/NCT04641585. [ABSTRACT FROM AUTHOR]

Objectives: To estimate cause specific mortality in a large cohort of Italian workers compensated for silicosis. Methods: The cohort included 14 929 subjects (14 098 men and 831 women) compensated for silicosis between 1946 and 1979, alive on 1 January 1980, and resident in Tuscany (a region of central Italy with 3 547 000 inhabitants). Mortality follow up ranged from 1980 to 1999. Vital status and the causes of death were determined by linkage with the regional mortality registry and with the national mortality database. The cohort mortality rates were compared to the rates of the local reference population. SMRs and their 95% confidence intervals were computed assuming a Poisson distribution of the observed deaths. Specific SMR analyses were performed according to the level of disability, the year of compensation assignment, and the job type. Results: A significant excess mortality was observed in male silicotics for cancer of the lung, trachea, and bronchus and cancer of the liver, respiratory diseases (silicosis, asbestosis, antracosilicosis, and other pneumoconiosis), and for tubercolosis. Statistically significant mortality excess was observed in female silicotics for respiratory diseases (specifically silicosis and other pneumoconiosis) and tuberculosis. Analyses for period of compensation assignment showed a twofold increased SMR for biliary tract cancer among female workers and for liver cancer among male workers compensated before 1970. Conclusions: The excess mortality from respiratory tract cancers and respiratory tract diseases detected in Italian compensated silicotics are in agreement with previous epidemiological studies. Although the twofold increased risk for liver cancer among males is suggestive of a possible association with silica dust exposure, the finding needs to be confirmed. [ABSTRACT FROM AUTHOR]