Observational studyBMJ open2023
Data mining techniques for detecting signals of adverse drug reaction of cardiac therapy drugs based on Jinan adverse event reporting system database: a retrospective study.
Observational study in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Artificial intelligence and computational methods in the Asia-Pacific pharmacovigilance landscape: a systematic review.International journal of public health · 2026Pooled it
- Using Artificial Intelligence to Identify Patterns and Predictors of Adverse Drug Reactions in Cardiovascular Patients: A Comprehensive Narrative Review.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2026Review
- Evaluating the Evolving Real-World Adverse Events of GLP-1RAs Using FDA Adverse Event Reporting System (FAERS).Obesity (Silver Spring, Md.) · 2026Article
- A post-marketing disproportionality analysis of the safety of ribociclib based on the FDA Adverse Event Reporting System.Therapeutic advances in drug safety · 2025Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveCardiac therapy drugs are widely used in the treatment of heart disease. However, the concern regarding adverse events (AEs) of cardiac therapy drugs have been rising. This study aimed to analyse cardiac therapy drug-related AEs using the Jinan adverse event reporting system (JAERS) database mining and conduct a comprehensive evaluation to provide safe medication information for patients.
designRetrospective observational study.
settingIn this study, cardiac therapy drug-related AEs were detected using the JAERS database from January 2000 to March 2022.
methodsReports of cardiac therapy drug-related AEs were extracted from JAERS database, and the basic information of patients, reports and common AEs were analysed. Four disproportionality analysis methods, proportional reporting ratio (PRR), reporting odds ratio (ROR), Bayesian Confidence Propagation Neural Network (BCPNN), Medicines and Healthcare products Regulatory Agency (MHRA), were used to detect cardiac therapy drug-related signals. We further checked whether the detected signals exist on drug labels in China and two developed countries, the USA and Japan.
resultsIn total, 168 314 AEs were reported, of which 4788 were associated with cardiac therapy drugs. Using the PRR, ROR, MHRA and BCPNN method, we detected 52 signals, 52 signals, 33 signals and 43 signals, respectively. Among the 52 signals, 14 were not included on the drug labels of China. One (isosorbide mononitrate-head bilges) was not included on the drug labels of the three countries.
conclusionWe identified 14 new cardiac therapy drug signals that did not appear on drug labels in China and 1 new signal that did not appear on drug labels in 3 counties. A causal link between cardiac therapy drugs and AEs should be evaluated in further studies.
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