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Record W2804388686 · doi:10.18433/jpps29893

An Update on Drug-induced Oral Reactions

2018· review· en· W2804388686 on OpenAlexvenueno aff
Hila Yousefi, Mohammad Abdollahı

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2018
Typereview
Languageen
FieldDentistry
TopicOral Health Pathology and Treatment
Canadian institutionsnot available
FundersIran National Science Foundation
KeywordsMedicineDrugOral lichen planusCulpritDrug reactionNonsteroidalAdverse effectMEDLINEScopusAdverse drug reactionDermatologyPharmacologyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Adverse drug reactions (ADRs) are one of the major culprits in the development of oral lesions, which can be misdiagnosed with underlying diseases. The goal of this study is to summarize and update the current knowledge about drug-induced oral reactions. Electronic searches were performed in Scopus, Google Scholar, Cochrane and PubMed databases, for articles published between January 2008 and August 2017. Two authors screened the titles and abstracts for eligibility. Finally, 56 studies included in this review. There was no systematic homogeneity in the included studies; thereby no meta-analysis was performed. The most frequent oral ADR was xerostomia,andthe most reported cause was antihypertensive medications. Cardiovascular drugs were the most reported culprit agents for induction of oral ulcerative and vesiculo-bullous lesions, followed by methotrexate. Nonsteroidal anti-inflammatory drugs (NSAIDs) and β-blockers were found the most common responsible drugs for induction of oral lichen planus. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.335
GPT teacher head0.579
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2018
Admission routes1
Has abstractyes

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