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| 1 | Herb-induced liver injury: Systematic review and meta-analysis显示文摘BACKGROUND The use of herbal supplements and alternative medicines has been increasing in the last decades.Despite popular belief that the consumption of natural products is harmless,herbs might cause injury to various organs,particularly to the liver,which is responsible for their metabolism in the form of herb-induced liver injury(HILI).AIM To identify herbal products associated with HILI and describe the type of lesion associated with each product.METHODS Studies were retrieved using Medical Subject Headings Descriptors combined with Boolean operators.Searches were run on the electronic databases Scopus,Web of Science,MEDLINE,BIREME,LILACS,Cochrane Library for Systematic Reviews,SciELO,Embase,and Opengray.eu.Languages were restricted to English,Spanish,and Portuguese.There was no date of publication restrictions.The reference lists of the studies retrieved were searched manually.To access causality,the Maria and Victorino System of Causality Assessment in Drug Induced Liver Injury was used.Simple descriptive analysis were used to summarize the results.RESULTS The search strategy retrieved 5918 references.In the final analysis,446 references were included,with a total of 936 cases reported.We found 79 types of herbs or herbal compounds related to HILI.He-Shou-Wu,Green tea extract,Herbalife,kava kava,Greater celandine,multiple herbs,germander,hydroxycut,skullcap,kratom,Gynura segetum,garcinia cambogia,ma huang,chaparral,senna,and aloe vera were the most common supplements with HILI reported.Most of these patients had complete clinical recovery(82.8%).However,liver transplantation was necessary for 6.6%of these cases.Also,chronic liver disease and death were observed in 1.5%and 10.4%of the cases,respectively.CONCLUSION HILI is normally associated with a good prognosis,once the implied product is withdrawn.Nevertheless,it is paramount to raise awareness in the medical and non-medical community of the risks of the indiscriminate use of herbal products. | Vinícius Remus Ballotin Lucas Goldmann Bigarella Ajacio Bandeira de Mello Brandão Raul Angelo Balbinot Silvana Sartori Balbinot Jonathan Soldera | 2021 | World Journal of Clinical Cases2021，9，20： | 4 |
| 2 | An improved tool path discretization method for five-axis sculptured surface显示文摘 | LI H REMUS O FATAN T | 2007 | International Journal of Advanced Manufacturing Technology2007，33，910： | 1 |
| 3 | Determination of geometry-based errors for interpolated tool paths in five axis surface machining显示文摘 | REMUS O FATAN T FENG H Y | 2005 | Journal of Manufacturing Science and Engineering2005，127，1： | 1 |
| 4 | Artificial Neural network Models for Forecasting and Decision Making显示文摘 | Hill T Marquez O' Connor M Remus W | 1993 | International Journal of Forecasting1993，，3： | 1 |
| 5 | Enhancement of Nasal Absorption of Insulin Using Chitosan Nanoparticles显示文摘 | Rocío Fernández-Urrusuno Pilar Calvo Carmen Remu?án-López Jose Luis Vila-Jato María José Alonso | 1999 | Pharmaceutical Research1999，，10： | 1 |
| 6 | N, Neural Network models for time series forecasts显示文摘 | Hill T O Connor M ~- Remus W | 1996 | Mangement science1996，7，： | 1 |
| 7 | Configuration analysis of five-axis machine tools using a generic kinematic model显示文摘 | Tutunea-Fatan O Remus Feng His-yung | 2004 | International Journal of Machine Tools and Manufacture2004，44，9： | 1 |
| 8 | Regular trav- eling waves in a one-dimen-sional network of Theta neurons显示文摘 | REMUS O JONATHAN R BARD E | 2002 | SIAM d Appi Math2002，62，4： | 1 |
| 9 | Neural Network Models for Time Series Forecasts显示文摘 | Hill T O' Connor M Remus W | 1996 | Management Science1996，42，7： | 1 |
| 10 | Enhancement of Nasal Absorption of Insulin Using Chitosan Nanoparticles显示文摘 | Rocío Fernández-Urrusuno Pilar Calvo Carmen Remu?án-López Jose Luis Vila-Jato María José Alonso | 1999 | Pharmaceutical Research1999，，10： | 1 |
| 11 | Determination of geometry-based errors for interpolated tool paths in fiveaxis surface machining显示文摘 | Remus O Fatan T Feng H Y | 2005 | ASME J Eng2005，127，2： | 1 |
| 12 | Configuration analysis of five-axis machine tools using a generic kinematic model 显示文摘 | Remus Tutunea-Fatan O His-Yung Feng | 2004 | Machine Tools and Mannfaetltre2004，44，： | 1 |
| 13 | Configuration analysis of five -axis machine tools using a generic kinematic model 显示文摘 | O Remus Tutunea-Fatan Hsi-Yung Feng | 2004 | International Journal of Machine Tools & Manufacture2004，44，： | 1 |
| 14 | Enhancement of Nasal Absorption of Insulin Using Chitosan Nanoparticles显示文摘 | Rocío Fernández-Urrusuno Pilar Calvo Carmen Remu?án-López Jose Luis Vila-Jato María José Alonso | 1999 | Pharmaceutical Research1999，，10： | 1 |
| 15 | The role of lysyl oxidase family members in the stabilization of ab- dominal aortic aneurysms显示文摘 | REMUS EW O'DONNELL RE JR RAFFERTY K | 2012 | Am J Physiol Heart Circ Physiol2012，303，8： | 1 |
| 16 | An improved tool path discretization method for five-axis sculptured surface显示文摘 | Li H W Remus O Fatan T Feng H Y | 2007 | International Journal of Advanced Manufacturing Technology2007，33，： | 1 |
| 17 | Neural network models for time series forecasts显示文摘 | Hill T Oconner M Remus W | 1996 | Management Science1996，42，7： | 1 |
| 18 | Predicting major adverse cardiovascular events after orthotopic liver transplantation using a supervised machine learning model:A cohort study显示文摘BACKGROUND Liver transplant(LT)patients have become older and sicker.The rate of post-LT major adverse cardiovascular events(MACE)has increased,and this in turn raises 30-d post-LT mortality.Noninvasive cardiac stress testing loses accuracy when applied to pre-LT cirrhotic patients.AIM To assess the feasibility and accuracy of a machine learning model used to predict post-LT MACE in a regional cohort.METHODS This retrospective cohort study involved 575 LT patients from a Southern Brazilian academic center.We developed a predictive model for post-LT MACE(defined as a composite outcome of stroke,new-onset heart failure,severe arrhythmia,and myocardial infarction)using the extreme gradient boosting(XGBoost)machine learning model.We addressed missing data(below 20%)for relevant variables using the k-nearest neighbor imputation method,calculating the mean from the ten nearest neighbors for each case.The modeling dataset included 83 features,encompassing patient and laboratory data,cirrhosis complications,and pre-LT cardiac assessments.Model performance was assessed using the area under the receiver operating characteristic curve(AUROC).We also employed Shapley additive explanations(SHAP)to interpret feature impacts.The dataset was split into training(75%)and testing(25%)sets.Calibration was evaluated using the Brier score.We followed Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines for reporting.Scikit-learn and SHAP in Python 3 were used for all analyses.The supplementary material includes code for model development and a user-friendly online MACE prediction calculator.RESULTS Of the 537 included patients,23(4.46%)developed in-hospital MACE,with a mean age at transplantation of 52.9 years.The majority,66.1%,were male.The XGBoost model achieved an impressive AUROC of 0.89 during the training stage.This model exhibited accuracy,precision,recall,and F1-score values of 0.84,0.85,0.80,and 0.79,respectively.Calibration,as assessed by the Brier score,indicated excellent model calibration with a score of 0.07.Furthermore,SHAP values highlighted the significance of certain variables in predicting postoperative MACE,with negative noninvasive cardiac stress testing,use of nonselective beta-blockers,direct bilirubin levels,blood type O,and dynamic alterations on myocardial perfusion scintigraphy being the most influential factors at the cohort-wide level.These results highlight the predictive capability of our XGBoost model in assessing the risk of post-LT MACE,making it a valuable tool for clinical practice.CONCLUSION Our study successfully assessed the feasibility and accuracy of the XGBoost machine learning model in predicting post-LT MACE,using both cardiovascular and hepatic variables.The model demonstrated impressive performance,aligning with literature findings,and exhibited excellent calibration.Notably,our cautious approach to prevent overfitting and data leakage suggests the stability of results when applied to prospective data,reinforcing the model’s value as a reliable tool for predicting post-LT MACE in clinical practice. | Jonathan Soldera Leandro Luis Corso Matheus Machado Rech Vinícius Remus Ballotin Lucas Goldmann Bigarella Fernanda Tomé Nathalia Moraes Rafael Sartori Balbinot Santiago Rodriguez Ajacio Bandeira de Mello Brandão Bruno Hochhegger | 2024 | World Journal of Hepatology2024，16，2： | 0 |
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