Evidence map›Paper›PMID 36669842›Full record

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.

Yuyao Guan, Yingmei Qi, Lei Zheng, Jing Yang, Mingzhu Zhang, Qiuhong Zhang, Lei Ji

Open access · goldAbstract readObservational Study
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 3 countries.

Yuyao Guan *Department of Pharmacy, Shandong University Affiliated Shandong Provincial Third Hospital, Jinan, Shandong, China jilei2022022022@163.com zhangqiuhong2222@163.com guanxiaoyao0815@163.com.
Yingmei Qi *Jinan Adverse Drug Reactions and Medical Device Adverse Event Monitoring Center, Jinan, Shandong, China.
Lei ZhengDepartment of Pharmacy, Shandong University Affiliated Shandong Provincial Third Hospital, Jinan, Shandong, China.
Jing YangDepartment of Pharmacy, Shandong University Affiliated Shandong Provincial Third Hospital, Jinan, Shandong, China.
Mingzhu ZhangDepartment of Pharmacy, Shandong University Affiliated Shandong Provincial Third Hospital, Jinan, Shandong, China.
Qiuhong ZhangJinan Adverse Drug Reactions and Medical Device Adverse Event Monitoring Center, Jinan, Shandong, China jilei2022022022@163.com zhangqiuhong2222@163.com guanxiaoyao0815@163.com.
Lei JiShandong Provincial Key Laboratory of Applied Microbiology, Ecology Institute, Qilu University of Technology, Jinan, Shandong, China jilei2022022022@163.com zhangqiuhong2222@163.com guanxiaoyao0815@163.com.ORCID 0000-0001-9828-0140
Shandong University · CNADR-AC (Switzerland) · CHQilu University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Adverse Drug Reaction Reporting SystemsDrug-Related Side Effects and Adverse ReactionsBayes TheoremDatabases, FactualData MiningHumansRetrospective StudiesUnited StatesUnited States Food and Drug AdministrationAdult cardiologyCardiac EpidemiologyHealth & safetyRisk management

Identifiers

PMID36669842
PMCPMC9872458
OpenAlexW4317685069

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.