Recent upper gastrointestinal panendoscopy increases the risk of pyogenic liver abscess

AIM To investigate the association between a recent gastrointestinal(GI) endoscopy and the subsequent risk of pyogenic liver abscess(PLA).METHODS We designed a nested case control study. Using the Taiwan National Health Insurance Research Database, 2135 patients with a first diagnosis of PLA were identified from 1998 to 2011. Another 10675 patients without PLA matched by age and sex were selected as reference controls. We identified and compared the possible risk factors for PLA and GI endoscopies performed before the index date(when PLA was diagnosed) between the two cohorts. Multivariate analysis was conducted to examine the risk of PLA within the 90 d after the GI endoscopies.RESULTS Patients with a history of diabetes [adjusted odds ratio(a OR) = 4.92, 95%CI: 1.78-13.61], end-stage renal disease(a OR = 3.98, 95%CI: 1.45-10.91), biliary tract infection(a OR = 2.68, 95%CI: 2.11-3.40), liver cirrhosis(a OR = 2.19, 95%CI: 1.39-3.46), GI malignancies(a OR = 5.68, 95%CI: 4.23-7.64), appendicitis(a OR = 3.16, 95%CI: 2.27-4.41), diverticulitis(a OR = 1.64, 95%CI: 1.01-2.64), and recent endoscopic retrograde cholangiopancreatography(a OR = 27.04, 95%CI: 11.65-62.72) were significantly associated with an increased risk of PLA. After adjusting for the above risk factors and the frequency of outpatient department visits and abdominal ultrasounds during 90 d before the index date, an upper GI panendoscopy(a OR = 2.75, 95%CI: 2.05-3.69) but not a lower GI endoscopy(a OR = 1.07, 95%CI: 0.62-1.86) was significantly associated with PLA.CONCLUSION An upper GI panendoscopy performed before 90 d may increase the risk of PLA.

KGSR-GG:A Noval Scheme for Dynamic Recommendation

Recommendation algorithms regard user-item interaction as a sequence to capture the user’s short-term preferences,but conventional algorithms cannot capture information of constantly-changing user interest in complex contexts.In these years,combining the knowledge graphwith sequential recommendation has gained momentum.The advantages of knowledge graph-based recommendation systems are that more semantic associations can improve the accuracy of recommendations,rich association facts can increase the diversity of recommendations,and complex relational paths can hence the interpretability of recommendations.But the information in the knowledge graph,such as entities and relations,often fails to be fully utilized and high-order connectivity is unattainable in graph modelling in knowledge graph-based sequential recommender systems.To address the above problems,a knowledge graph-based sequential recommendation algorithm that combines the gated recurrent unit and the graph neural network(KGSRGG)is proposed in the present work.Specifically,entity disambiguation in the knowledge graph is performed on the preprocessing layer;on the embedding layer,the TransR embedding technique is employed to process the user information,item information and the entities and relations in the knowledge graph;on the aggregation layer,the information is aggregated by graph convolutional neural networks and residual connections;and at last,on the sequence layer,a bi-directional gated recurrent unit(Bi-GRU)is utilized to model the user’s sequential preferences.The research results showed that this newalgorithm performed better than existing sequential recommendation algorithms on the MovieLens-1M and Book-Crossing datasets,as measured by five evaluation indicators.

China artificial joint annual data report

To the Editor:Artificial joint replacement,the most effective treatment for end-stage arthropathy of the hip and knee joint caused by various reasons,has been popularly performed around the world.[1]It was reported the number of total hip replacement case in the United States in 2017 was 1.1 million and the number of total knee replacement case in 2018 was 1.3 million.[2]And the case number is increasing annually.With the biggest population in the world,there is a big volume of joint replacement procedures in China.However,there is lack of artificial joint annual data report in China up-to-date.In this study,we intended to collect the data of artificial joint replacement in the mainland of China within the recent 10 years,and make a preliminary artificial joint annual report.