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Risk factors for hepatocellular carcinoma associated with hepatitis C genotype 3 infection:A systematic review
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作者 Hamzah Z Farooq Michael James +4 位作者 Jane Abbott Patrick Oyibo Pip Divall Naheed Choudhry Graham R Foster 《World Journal of Gastrointestinal Oncology》 SCIE 2024年第4期1596-1612,共17页
BACKGROUND Hepatitis C virus(HCV)is a blood-borne virus which globally affects around 79 million people and is associated with high morbidity and mortality.Chronic infection leads to cirrhosis in a large proportion of... BACKGROUND Hepatitis C virus(HCV)is a blood-borne virus which globally affects around 79 million people and is associated with high morbidity and mortality.Chronic infection leads to cirrhosis in a large proportion of patients and often causes hepatocellular carcinoma(HCC)in people with cirrhosis.Of the 6 HCV genotypes(G1-G6),genotype-3 accounts for 17.9%of infections.HCV genotype-3 responds least well to directly-acting antivirals and patients with genotype-3 infection are at increased risk of HCC even if they do not have cirrhosis.AIM To systematically review and critically appraise all risk factors for HCC secondary to HCV-G3 in all settings.Consequently,we studied possible risk factors for HCC due to HCV-G3 in the literature from 1946 to 2023.METHODS This systematic review aimed to synthesise existing and published studies of risk factors for HCC secondary to HCV genotype-3 and evaluate their strengths and limitations.We searched Web of Science,Medline,EMBASE,and CENTRAL for publications reporting risk factors for HCC due to HCV genotype-3 in all settings,1946-2023.RESULTS Four thousand one hundred and forty-four records were identified from the four databases with 260 records removed as duplicates.Three thousand eight hundred and eighty-four records were screened with 3514 excluded.Three hundred and seventy-one full-texts were assessed for eligibility with seven studies included for analysis.Of the seven studies,three studies were retrospective case-control trials,two retrospective cohort studies,one a prospective cohort study and one a cross-sectional study design.All were based in hospital settings with four in Pakistan,two in South Korea and one in the United States.The total number of participants were 9621 of which 167 developed HCC(1.7%).All seven studies found cirrhosis to be a risk factor for HCC secondary to HCV genotype-3 followed by higher age(five-studies),with two studies each showing male sex,high alpha feto-protein,directly-acting antivirals treatment and achievement of sustained virologic response as risk factors for developing HCC.CONCLUSION Although,studies have shown that HCV genotype-3 infection is an independent risk factor for end-stage liver disease,HCC,and liver-related death,there is a lack of evidence for specific risk factors for HCC secondary to HCV genotype-3.Only cirrhosis and age have demonstrated an association;however,the number of studies is very small,and more research is required to investigate risk factors for HCC secondary to HCV genotype-3. 展开更多
关键词 Hepatocellular carcinoma Hepatitis C Genotype 3 Systematic review Blood-borne viruses Liver cancer
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Dissecting Psychiatric Heterogeneity and Comorbidity with Core Region-Based Machine Learning 被引量:1
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作者 Qian Lv Kristina Zeljic +3 位作者 Shaoling Zhao Jiangtao Zhang Jianmin Zhang Zheng Wang 《Neuroscience Bulletin》 SCIE CAS CSCD 2023年第8期1309-1326,共18页
Machine learning approaches are increasingly being applied to neuroimaging data from patients with psychiatric disorders to extract brain-based features for diagnosis and prognosis.The goal of this review is to discus... Machine learning approaches are increasingly being applied to neuroimaging data from patients with psychiatric disorders to extract brain-based features for diagnosis and prognosis.The goal of this review is to discuss recent practices for evaluating machine learning applications to obsessive-compulsive and related disorders and to advance a novel strategy of building machine learning models based on a set of core brain regions for better performance,interpretability,and generalizability.Specifically,we argue that a core set of co-altered brain regions(namely‘core regions’)comprising areas central to the underlying psychopathology enables the efficient construction of a predictive model to identify distinct symptom dimensions/clusters in individual patients.Hypothesis-driven and data-driven approaches are further introduced showing how core regions are identified from the entire brain.We demonstrate a broadly applicable roadmap for leveraging this core set-based strategy to accelerate the pursuit of neuroimaging-based markers for diagnosis and prognosis in a variety of psychiatric disorders. 展开更多
关键词 Psychiatric disorders Obsessive-compulsive disorder Core region Magnetic resonance imaging Machine learning Neuroimaging-based diagnosis
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