ABSTRACT
OBJECTIVE: Helicobacter pylori infection is mostly a family-based infectious disease. To facilitate its prevention and management, a national consensus meeting was held to review current evidence and propose strategies for population-wide and family-based H. pylori infection control and management to reduce the related disease burden. METHODS: Fifty-seven experts from 41 major universities and institutions in 20 provinces/regions of mainland China were invited to review evidence and modify statements using Delphi process and grading of recommendations assessment, development and evaluation system. The consensus level was defined as ≥80% for agreement on the proposed statements. RESULTS: Experts discussed and modified the original 23 statements on family-based H. pylori infection transmission, control and management, and reached consensus on 16 statements. The final report consists of three parts: (1) H. pylori infection and transmission among family members, (2) prevention and management of H. pylori infection in children and elderly people within households, and (3) strategies for prevention and management of H. pylori infection for family members. In addition to the 'test-and-treat' and 'screen-and-treat' strategies, this consensus also introduced a novel third 'family-based H. pylori infection control and management' strategy to prevent its intrafamilial transmission and development of related diseases. CONCLUSION: H. pylori is transmissible from person to person, and among family members. A family-based H. pylori prevention and eradication strategy would be a suitable approach to prevent its intra-familial transmission and related diseases. The notion and practice would be beneficial not only for Chinese residents but also valuable as a reference for other highly infected areas.
Subject(s)
Family Health , Helicobacter Infections/prevention & control , Helicobacter pylori , Infection Control/organization & administration , Adolescent , Adult , Aged , Child , Child, Preschool , China , Consensus , Delphi Technique , Helicobacter Infections/diagnosis , Helicobacter Infections/transmission , Humans , Infant , Middle Aged , Young AdultABSTRACT
BACKGROUND: This study was aimed to develop a computer-aided diagnosis (CAD) system with deep-learning technique and to validate its efficiency on detecting the four categories of lesions such as polyps, advanced cancer, erosion/ulcer and varices at endoscopy. METHODS: A deep convolutional neural network (CNN) that consists of more than 50 layers were trained with a big dataset containing 327,121 white light images (WLI) of endoscopy from 117,005 cases collected from 2012 to 2017. Two CAD models were developed using images with or without annotation of the training dataset. The efficiency of the CAD system detecting the four categories of lesions was validated by another dataset containing consecutive cases from 2018 to 2019. RESULTS: A total of 1734 cases with 33,959 images were included in the validation datasets which containing lesions of polyps 1265, advanced cancer 500, erosion/ulcer 486, and varices 248. The CAD system developed in this study may detect polyps, advanced cancer, erosion/ulcer and varices as abnormality with the sensitivity of 88.3% and specificity of 90.3%, respectively, in 0.05 s. The training datasets with annotation may enhance either sensitivity or specificity about 20%, p = 0.000. The sensitivities and specificities for polyps, advanced cancer, erosion/ulcer and varices reached about 90%, respectively. The detect efficiency for the four categories of lesions reached to 89.7%. CONCLUSION: The CAD model for detection of multiple lesions in gastrointestinal lumen would be potentially developed into a double check along with real-time assessment and interpretation of the findings encountered by the endoscopists and may be a benefit to reduce the events of missing lesions.