Evidence map›Paper›PMID 25093068›Full record

ArticleJournal of biomedical semantics2014

OAE: The Ontology of Adverse Events.

Yongqun He, Sirarat Sarntivijai, Yu Lin, Zuoshuang Xiang, Abra Guo, Shelley Zhang, Desikan Jagannathan, Luca Toldo, Cui Tao, Barry Smith

Open access · goldAbstract read
In one paragraph

Article in Journal of biomedical semantics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 2 pooled it
5.1field-weighted citation impact, top 4% 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

72 citing papers in PubMed, 2 syntheses or guidelines pooled it, 131 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. VO: The Vaccine Ontology.bioRxiv : the preprint server for biology · 2025
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. An ontology-based tool for modeling and documenting events in neurosurgery.BMC medical informatics and decision making · 2024
    Article
  18. The Immunopeptidomics Ontology (ImPO).Database : the journal of biological databases and curation · 2024
    Article
  19. Article
  20. Article

12 more citing papers are in PubMed but not listed here.

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

10 authors at 5 institutions in 2 countries.

Yongqun HeUniversity of Michigan, Ann Arbor, MI, USA.
Sirarat SarntivijaiUniversity of Michigan, Ann Arbor, MI, USA ; US Food and Drug Administration, Silver Spring, MD, USA.
Yu LinUniversity of Michigan, Ann Arbor, MI, USA.
Zuoshuang XiangUniversity of Michigan, Ann Arbor, MI, USA.
Abra GuoUniversity of Michigan, Ann Arbor, MI, USA.
Shelley ZhangUniversity of Michigan, Ann Arbor, MI, USA.
Desikan JagannathanUniversity of Michigan, Ann Arbor, MI, USA.
Luca ToldoMerck KGaA, Darmstadt, Germany.
Cui TaoUniversity at Texas Health Science Center at Houston, Houston, TX, USA.
Barry SmithUniversity at Buffalo, Buffalo, NY, USA.
University of Michigan–Ann Arbor · USBuffalo State University · USMerck (Germany) · DEThe University of Texas Health Science Center at Houston · USUnited States Food and Drug Administration · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA medical intervention is a medical procedure or application intended to relieve or prevent illness or injury. Examples of medical interventions include vaccination and drug administration. After a medical intervention, adverse events (AEs) may occur which lie outside the intended consequences of the intervention. The representation and analysis of AEs are critical to the improvement of public health. DESCRIPTION: The Ontology of Adverse Events (OAE), previously named Adverse Event Ontology (AEO), is a community-driven ontology developed to standardize and integrate data relating to AEs arising subsequent to medical interventions, as well as to support computer-assisted reasoning. OAE has over 3,000 terms with unique identifiers, including terms imported from existing ontologies and more than 1,800 OAE-specific terms. In OAE, the term 'adverse event' denotes a pathological bodily process in a patient that occurs after a medical intervention. Causal adverse events are defined by OAE as those events that are causal consequences of a medical intervention. OAE represents various adverse events based on patient anatomic regions and clinical outcomes, including symptoms, signs, and abnormal processes. OAE has been used in the analysis of several different sorts of vaccine and drug adverse event data. For example, using the data extracted from the Vaccine Adverse Event Reporting System (VAERS), OAE was used to analyse vaccine adverse events associated with the administrations of different types of influenza vaccines. OAE has also been used to represent and classify the vaccine adverse events cited in package inserts of FDA-licensed human vaccines in the USA.

conclusionOAE is a biomedical ontology that logically defines and classifies various adverse events occurring after medical interventions. OAE has successfully been applied in several adverse event studies. The OAE ontological framework provides a platform for systematic representation and analysis of adverse events and of the factors (e.g., vaccinee age) important for determining their clinical outcomes.

Indexed as

Adverse eventDesign patternDrugDrug adverse eventOAEOntologyOntology of Adverse EventsVaccineVaccine adverse eventVAERS

Identifiers

PMID25093068
PMCPMC4120740
OpenAlexW2141201603

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.