HLA-C*12:02 is strongly associated with Xuesaitong-induced cutaneous adverse drug reactions

Study on the Relationship Between the Number of Adverse Drug Reactions of Essential Drugs and Visits: Based on Vector Autoregressive Model

Objective

To analyse the relationship between the adverse drug reactions (ADRs) of essential drugs and visits, based on the recorded annual increase in ADRs associated with essential medicines in China, to provide a reliable theoretical basis for further analysis and optimization of the safety of essential drugs.

Methods

The data of adverse reactions of essential drugs in China from 2011 to 2020, time series analysis was conducted, and vector autoregressive (VAR) model was established. The relationship between the number of ADRs and visits was explored empirically through Granger causality test, impulse response function and variance decomposition.

Results

There was a long-term cointegration relationship and one-way causality between the number of visits and ADRs caused by essential medicines. In the initial stage, the ADR response to the number of visits increased sharply, but with an increase in the number of lag periods, the impact remained basically stable, even showing a slight decreasing trend.

Conclusion

The number of visits impacts ADRs caused by essential medicines, but this impact remains basically stable after reaching a certain level.

Develop an ADR prediction system of Chinese herbal injections containing Panax notoginseng saponin: a nested case-control study using machine learning

OBJECTIVE

This study aimed to develop an adverse drug reactions (ADR) antecedent prediction system using machine learning algorithms to provide the reference for security usage of Chinese herbal injections containing Panax notoginseng saponin in clinical practice.

DESIGN

A nested case-control study.

SETTING

National Center for ADR Monitoring and the Electronic Medical Record (EMR) system.

PARTICIPANTS

All patients were from five medical institutions in Sichuan Province from January 2010 to December 2018.

MAIN OUTCOMES/MEASURES

Data of patients with ADR who used Chinese herbal injections containing Panax notoginseng saponin were collected from the National Center for ADR Monitoring. A nested case-control study was used to randomly match patients without ADR from the EMR system by the ratio of 1:4. Eighteen machine learning algorithms were applied for the development of ADR prediction models. Area under curve (AUC), accuracy, precision, recall rate and F1 value were used to evaluate the predictive performance of the model. An ADR prediction system was established by the best model selected from the 1080 models.

RESULTS

A total of 530 patients from five medical institutions were included, and 1080 ADR prediction models were developed. Among these models, the AUC of the best capable one was 0.9141 and the accuracy was 0.8947. According to the best model, a prediction system, which can provide early identification of patients at risk for the ADR of Panax notoginseng saponin, has been established.

CONCLUSION

The prediction system developed based on the machine learning model in this study had good predictive performance and potential clinical application.

Analysis of differential gene expression profiles uncovers mechanisms of Xuesaitong injection against cerebral ischemia-reperfusion injury

BACKGROUND

Xuesaitong injection (XST), a well-known traditional Chinese patent medicine, has been widely used in the treatment of cardiovascular and cerebrovascular diseases. The exact mechanisms of XST in ischemic stroke remain to be thoroughly elucidated.

PURPOSE

This study aims to characterize the candidate differentially expressed genes (DEGs) and pathways of XST in ischemic stroke by bioinformatics analysis, and to explore new clues for the underlying mechanisms of XST.

METHODS

A dataset (GSE61616) was performed to screen out DEGs for deep analysis. Series Test of Cluster analysis for DEGs was carried out. For all DEGs, Gene Ontology (GO) annotation analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for visualization. The screened hub gene expression characteristics were verified in middle cerebral artery occlusion (MCAO) rats. In vivo studies have demonstrated the mechanisms of XST against cerebral ischemia-reperfusion (CIR) injury.

RESULTS

A total of 8066 DEGs were screened out and the expression of genes in profile 8 was suggested to have clinical significance. The MAPK signaling pathway was indicated as the most significantly enriched pathway in profile 8. Bdnf was identified as the most significant hub gene according to node degree. Animal experiments demonstrated that XST attenuated CIR injury. XST increased brain-derived neurotrophic factor (BDNF) and its high-affinity receptor tropomyosin-related kinase B (TrkB) levels in MCAO. Furthermore, the knockdown of BDNF by siRNA abolished the in vivo effects of XST on brain injury, neurodegeneration and apoptosis after CIR.

CONCLUSION

The integrated strategy, based on bioinformatics analyses with experimental verification, provides a novel cellular mechanism by which XST alleviates CIR injury. The BDNF-TrkB pathway was highly thought to play a vital role in the neuroprotective effects of XST.