Sökning: (hsv:(MEDICIN OCH HÄLSOVETENSKAP) hsv:(Medicinska och farmaceutiska grundvetenskaper) hsv:(Farmakologi och toxikologi)) pers:(Wadelius Mia) >
Identification of r...
Identification of risk factors for adverse drug reactions in a pharmacovigilance database
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- Attelind, Sofia (författare)
- Uppsala universitet,Klinisk farmakogenomik och osteoporos,Swedish Med Prod Agcy, Dept Drug Safety, Uppsala, Sweden.
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- Eriksson, Niclas, 1978- (författare)
- Uppsala universitet,Klinisk farmakogenomik och osteoporos,Uppsala Univ Hosp, Uppsala Clin Res Ctr, Uppsala, Sweden.
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Sundstroem, Anders (författare)
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- Wadelius, Mia (författare)
- Uppsala universitet,Klinisk farmakogenomik och osteoporos
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- Hallberg, Pär, 1974- (författare)
- Uppsala universitet,Klinisk farmakogenomik och osteoporos
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(creator_code:org_t)
- John Wiley & Sons, 2023
- 2023
- Engelska.
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Ingår i: Pharmacoepidemiology and Drug Safety. - : John Wiley & Sons. - 1053-8569 .- 1099-1557. ; 32:12, s. 1431-1438
- Relaterad länk:
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https://doi.org/10.1...
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https://uu.diva-port... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Introduction In addition to identifying new safety signals, pharmacovigilance databases could be used to identify potential risk factors for adverse drug reactions (ADRs).Objective To evaluate whether data mining in a pharmacovigilance database can be used to identify known and possible novel risk factors for ADRs, for use in pharmacovigilance practice.Method Exploratory data mining was performed within the Swedish national database of spontaneously reported ADRs. Bleeding associated with direct oral anticoagulants (DOACs)-rivaroxaban, apixaban, edoxaban, and dabigatran-was used as a test model. We compared demographics, drug treatment, and clinical features between cases with bleeding (N = 965) and controls who had experienced other serious ADRs to DOACs (N = 511). Statistical analysis was performed by unadjusted and age adjusted logistic regression models, and the random forest based machine-learning method Boruta.Results In the logistic regression, 13 factors were significantly more common among cases of bleeding compared with controls. Eleven were labelled or previously proposed risk factors. Cardiac arrhythmia (e.g., atrial fibrillation), hypertension, mental impairment disorders (e.g., dementia), renal and urinary tract procedures, gastrointestinal ulceration and perforation, and interacting drugs remained significant after adjustment for age. In the Boruta analysis, high age, arrhythmia, hypertension, cardiac failure, thromboembolism, and pharmacodynamically interacting drugs had a larger than random association with the outcome. High age, cardiac arrhythmia, hypertension, cardiac failure, and pharmacodynamically interacting drugs had odds ratios for bleeding above one, while thromboembolism had an odds ratio below one.Conclusions We demonstrated that data mining within a pharmacovigilance database identifies known risk factors for DOAC bleeding, and potential risk factors such as dementia and atrial fibrillation. We propose that the method could be used in pharmacovigilance for identification of potential ADR risk factors that merit further evaluation.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Kardiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Farmakologi och toxikologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Pharmacology and Toxicology (hsv//eng)
Nyckelord
- anticoagulant-induced bleedings
- direct oral anticoagulants
- pharmacovigilance database
- risk factors
- suspected adverse drug reactions
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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