LEARN algorithm:a novel option for predicting non-alcoholic steatohepatitis

Background:There is an unmet need for accurate non-invasive methods to diagnose non-alcoholic steatohepatitis(NASH).Since impedance-based measurements of body composition are simple,repeatable and have a strong association with non-alcoholic fatty liver disease(NAFLD)severity,we aimed to develop a novel and fully automatic machine learning algorithm,consisting of a deep neural network based on impedance-based measurements of body composition to identify NASH[the bioeLectrical impEdance Analysis foR Nash(LEARN)algorithm].Methods:A total of 1,259 consecutive subjects with suspected NAFLD were screened from six medical centers across China,of which 766 patients with biopsy-proven NAFLD were included in final analysis.These patients were randomly subdivided into the training and validation groups,in a ratio of 4:1.The LEARN algorithm was developed in the training group to identify NASH,and subsequently,tested in the validation group.Results:The LEARN algorithm utilizing impedance-based measurements of body composition along with age,sex,pre-existing hypertension and diabetes,was able to predict the likelihood of having NASH.This algorithm showed good discriminatory ability for identifying NASH in both the training and validation groups[area under the receiver operating characteristics(AUROC):0.81,95%CI:0.77-0.84 and AUROC:0.80,95%CI:0.73-0.87,respectively].This algorithm also performed better than serum cytokeratin-18 neoepitope M30(CK-18 M30)level or other non-invasive NASH scores(including HAIR,ION,NICE)for identifying NASH(P value<0.001).Additionally,the LEARN algorithm performed well in identifying NASH in different patient subgroups,as well as in subjects with partial missing body composition data.Conclusions:The LEARN algorithm,utilizing simple easily obtained measures,provides a fully automated,simple,non-invasive method for identifying NASH.

Machine learning improves prediction of severity and outcomes of acute pancreatitis:a prospective multi-center cohort study

Dear Editor,Acute pancreatitis(AP)is a common acute pancreatic disease of variable severity and outcomes(Mederos et al.,2021).According to systemic and local complications,patients can be classified into severe,moderately severe,and mild AP(Banks et al.,2013).About 20%of AP patients develop severe acute pancreatitis(SAP,with persistent organ failures)of whom 20%–50%die.