Background:The recently introduced set of terminologies defining categories of steatotic liver disease(SLD)includes metabolic dysfunction-associated SLD(MASLD),alcohol-associated liver disease(ALD),and metabolic dysfu...Background:The recently introduced set of terminologies defining categories of steatotic liver disease(SLD)includes metabolic dysfunction-associated SLD(MASLD),alcohol-associated liver disease(ALD),and metabolic dysfunction associated steatotic liver disease and increased alcohol intake(MetALD).The present retrospective cohort study examines clinical characteristics,prevalence,and mortality risk across alcoholic intake spectrum in SLD individuals.Methods:Data between 1999 to 2018 were extracted from National Health and Nutrition Examination Survey registries and analysed.Population baseline characteristics were evaluated across classifications of SLD.SLD was confirmed using either fatty liver index(FLI)or United States FLI(US-FLI).Multivariate analyses were used to study mortality-related outcomes.Results:The 20,510 individuals with SLD included were classified into MASLD predominant(69.00%),MetALD(18.77%),and ALD predominant(12.23%)groups.Temporal analysis revealed significant decreases in MASLD prevalence in the SLD population from 1999-2018 in general[average annual percentage change(AAPC)−4.802%,P=0.001],as well as in females,Mexican Americans,and Non-Hispanic Blacks.MetALD prevalence in the SLD population increased from 1999-2018 in general(AAPC+1.635%,P<0.001),and in males,females,Mexican Americans,Non-Hispanic Blacks and other ethnicities.No significant change in ALD prevalence was found.Compared to MASLD predominant individuals,ALD predominant individuals had higher risks of all-cause[hazard ratio(HR):1.189,95%confidence interval(CI):1.026 to 1.378,P=0.02]and cancer-related mortality(subdistribution HR:1.277,95%CI:1.032 to 1.579,P=0.02).No significant difference was observed for all-cause,cancer-related,or cardiovascular disease(CVD)-related mortality in MetALD and CVD-related mortality in ALD predominant individuals,relative to MASLD predominant individuals.Conclusions:ALD predominant patients have higher all-cause and cancer-related mortality risks than MASLD predominant patients but not CVD-related mortality.SLD is highly heterogeneous in clinical characteristics,prevalence,and mortality risks which healthcare professionals must account for to avert adverse health outcomes.展开更多
Hepatocellular carcinoma(HCC)is a major cause of cancer-related deaths worldwide.This review explores the recent progress in the application of artificial intelligence(AI)in radiological diagnosis of HCC.The Barcelona...Hepatocellular carcinoma(HCC)is a major cause of cancer-related deaths worldwide.This review explores the recent progress in the application of artificial intelligence(AI)in radiological diagnosis of HCC.The Barcelona Classification of Liver Cancer criteria guides treatment decisions based on tumour characteristics and liver function indicators,but HCC often remains undetected until intermediate or advanced stages,limiting treatment options and patient outcomes.Timely and accurate diagnostic methods are crucial for enabling curative therapies and improving patient outcomes.AI,particularly deep learning and neural network models,has shown promise in the radiological detection of HCC.AI offers several advantages in HCC diagnosis,including reducing diagnostic variability,optimising data analysis and reallocating healthcare resources.By providing objective and consistent analysis of imaging data,AI can overcome the limitations of human interpretation and enhance the accuracy of HCC diagnosis.Furthermore,AI systems can assist healthcare professionals in managing the increasing workload by serving as a reliable diagnostic tool.Integration of AI with information systems enables comprehensive analysis of patient data,facilitating more informed and reliable diagnoses.The advancements in AI-based radiological diagnosis hold significant potential to improve early detection,treatment selection and patient outcomes in HCC.Further research and clinical implementation of AI models in routine practice are necessary to harness the full potential of this technology in HCC management.展开更多
文摘Background:The recently introduced set of terminologies defining categories of steatotic liver disease(SLD)includes metabolic dysfunction-associated SLD(MASLD),alcohol-associated liver disease(ALD),and metabolic dysfunction associated steatotic liver disease and increased alcohol intake(MetALD).The present retrospective cohort study examines clinical characteristics,prevalence,and mortality risk across alcoholic intake spectrum in SLD individuals.Methods:Data between 1999 to 2018 were extracted from National Health and Nutrition Examination Survey registries and analysed.Population baseline characteristics were evaluated across classifications of SLD.SLD was confirmed using either fatty liver index(FLI)or United States FLI(US-FLI).Multivariate analyses were used to study mortality-related outcomes.Results:The 20,510 individuals with SLD included were classified into MASLD predominant(69.00%),MetALD(18.77%),and ALD predominant(12.23%)groups.Temporal analysis revealed significant decreases in MASLD prevalence in the SLD population from 1999-2018 in general[average annual percentage change(AAPC)−4.802%,P=0.001],as well as in females,Mexican Americans,and Non-Hispanic Blacks.MetALD prevalence in the SLD population increased from 1999-2018 in general(AAPC+1.635%,P<0.001),and in males,females,Mexican Americans,Non-Hispanic Blacks and other ethnicities.No significant change in ALD prevalence was found.Compared to MASLD predominant individuals,ALD predominant individuals had higher risks of all-cause[hazard ratio(HR):1.189,95%confidence interval(CI):1.026 to 1.378,P=0.02]and cancer-related mortality(subdistribution HR:1.277,95%CI:1.032 to 1.579,P=0.02).No significant difference was observed for all-cause,cancer-related,or cardiovascular disease(CVD)-related mortality in MetALD and CVD-related mortality in ALD predominant individuals,relative to MASLD predominant individuals.Conclusions:ALD predominant patients have higher all-cause and cancer-related mortality risks than MASLD predominant patients but not CVD-related mortality.SLD is highly heterogeneous in clinical characteristics,prevalence,and mortality risks which healthcare professionals must account for to avert adverse health outcomes.
文摘Hepatocellular carcinoma(HCC)is a major cause of cancer-related deaths worldwide.This review explores the recent progress in the application of artificial intelligence(AI)in radiological diagnosis of HCC.The Barcelona Classification of Liver Cancer criteria guides treatment decisions based on tumour characteristics and liver function indicators,but HCC often remains undetected until intermediate or advanced stages,limiting treatment options and patient outcomes.Timely and accurate diagnostic methods are crucial for enabling curative therapies and improving patient outcomes.AI,particularly deep learning and neural network models,has shown promise in the radiological detection of HCC.AI offers several advantages in HCC diagnosis,including reducing diagnostic variability,optimising data analysis and reallocating healthcare resources.By providing objective and consistent analysis of imaging data,AI can overcome the limitations of human interpretation and enhance the accuracy of HCC diagnosis.Furthermore,AI systems can assist healthcare professionals in managing the increasing workload by serving as a reliable diagnostic tool.Integration of AI with information systems enables comprehensive analysis of patient data,facilitating more informed and reliable diagnoses.The advancements in AI-based radiological diagnosis hold significant potential to improve early detection,treatment selection and patient outcomes in HCC.Further research and clinical implementation of AI models in routine practice are necessary to harness the full potential of this technology in HCC management.
