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OAE: The Ontology of Adverse Events.

He Y, Sarntivijai S, Lin Y, Xiang Z, Guo A, Zhang S, Jagannathan D, Toldo L, Tao C, Smith B - J Biomed Semantics (2014)

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: University of Michigan, Ann Arbor, MI, USA.

ABSTRACT

Background: A 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.

Conclusion: OAE 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.

No MeSH data available.


Related in: MedlinePlus

Key ontology terms in OAE. Except those with special labels, all arrows represent the same is-kind-of relations. Except those terms labelled with ontology abbreviation names, all terms inside boxes come from OAE. The detailed information of the class and relation terms used in this figure is available in Additional file1: Table S1 and Additional file2: Table S2.
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Figure 3: Key ontology terms in OAE. Except those with special labels, all arrows represent the same is-kind-of relations. Except those terms labelled with ontology abbreviation names, all terms inside boxes come from OAE. The detailed information of the class and relation terms used in this figure is available in Additional file1: Table S1 and Additional file2: Table S2.

Mentions: OAE provides a framework that allows the representation and analysis of different factors and mechanisms that possibly influence adverse event outcomes. For example, two major factors that determine distinct AEs associated with killed and live attenuated influenza vaccines include the viability of vaccine organism and the vaccination route[8,10]. A killed influenza vaccine is administered through intramuscular injection. A live attenuated influenza vaccine is administered through intranasal spray. While it is still unclear whether the vaccination route affects the adverse event outcomes[10], our linkage between adverse events and vaccination routes provides us a way to systematically study this issue. Since OAE links the patients to the adverse event (Figure 2), it is possible to link the patient records (e.g., age, gender, vaccine administered, and vaccination method) to adverse events. An example is that vaccinees in different age groups likely have different occurrence rates for specific AEs. Such age-AE associations, clearly documented in vaccine package inserts, have been ontologically recorded in our recent OAE-based study[28]. Therefore, the OAE framework provides the computational infrastructure to model the relations between different factors and the clinical outcome.Genetic background of a patient also affects the occurrence of the adverse event in this example. Knowledge of intricate drug-patient and drug-drug interactions is also crucial to determining final adverse drug event outcomes. Some adverse events happen due to cross-interactions between drug and food (as for example in the case of statins and grapefruit). A patient may have taken a medicine or retain a pre-existing condition (e.g., drinking alcohol). The alcohol may have an increased effect on some adverse event induced by a drug (e.g., benzodiazepines). Through the inclusion of a patient with specific conditions in the OAE design pattern (Figure 3), OAE outlines the computational infrastructure with the capability to capture these potential interaction mechanisms through ontological linkages with the long-term goal of understanding the fundamental basis of these specialized causal events. When new evidences become known to support the likelihood of a drug-AE causal association, appropriate measures can be rationally designed to counter these adverse effects.


OAE: The Ontology of Adverse Events.

He Y, Sarntivijai S, Lin Y, Xiang Z, Guo A, Zhang S, Jagannathan D, Toldo L, Tao C, Smith B - J Biomed Semantics (2014)

Key ontology terms in OAE. Except those with special labels, all arrows represent the same is-kind-of relations. Except those terms labelled with ontology abbreviation names, all terms inside boxes come from OAE. The detailed information of the class and relation terms used in this figure is available in Additional file1: Table S1 and Additional file2: Table S2.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4120740&req=5

Figure 3: Key ontology terms in OAE. Except those with special labels, all arrows represent the same is-kind-of relations. Except those terms labelled with ontology abbreviation names, all terms inside boxes come from OAE. The detailed information of the class and relation terms used in this figure is available in Additional file1: Table S1 and Additional file2: Table S2.
Mentions: OAE provides a framework that allows the representation and analysis of different factors and mechanisms that possibly influence adverse event outcomes. For example, two major factors that determine distinct AEs associated with killed and live attenuated influenza vaccines include the viability of vaccine organism and the vaccination route[8,10]. A killed influenza vaccine is administered through intramuscular injection. A live attenuated influenza vaccine is administered through intranasal spray. While it is still unclear whether the vaccination route affects the adverse event outcomes[10], our linkage between adverse events and vaccination routes provides us a way to systematically study this issue. Since OAE links the patients to the adverse event (Figure 2), it is possible to link the patient records (e.g., age, gender, vaccine administered, and vaccination method) to adverse events. An example is that vaccinees in different age groups likely have different occurrence rates for specific AEs. Such age-AE associations, clearly documented in vaccine package inserts, have been ontologically recorded in our recent OAE-based study[28]. Therefore, the OAE framework provides the computational infrastructure to model the relations between different factors and the clinical outcome.Genetic background of a patient also affects the occurrence of the adverse event in this example. Knowledge of intricate drug-patient and drug-drug interactions is also crucial to determining final adverse drug event outcomes. Some adverse events happen due to cross-interactions between drug and food (as for example in the case of statins and grapefruit). A patient may have taken a medicine or retain a pre-existing condition (e.g., drinking alcohol). The alcohol may have an increased effect on some adverse event induced by a drug (e.g., benzodiazepines). Through the inclusion of a patient with specific conditions in the OAE design pattern (Figure 3), OAE outlines the computational infrastructure with the capability to capture these potential interaction mechanisms through ontological linkages with the long-term goal of understanding the fundamental basis of these specialized causal events. When new evidences become known to support the likelihood of a drug-AE causal association, appropriate measures can be rationally designed to counter these adverse effects.

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: University of Michigan, Ann Arbor, MI, USA.

ABSTRACT

Background: A 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.

Conclusion: OAE 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.

No MeSH data available.


Related in: MedlinePlus