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ADR in Journals: Are They Translated into Regulatory Frameworks?

2021· article· en· W3174972277 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCurrent Drug Safety · 2021
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacovigilance and Adverse Drug Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCasualDrug reactionAdverse drug reactionPharmacovigilanceRegulatory authorityPackage insertFamily medicineDrugPharmacology

Abstract

fetched live from OpenAlex

INTRODUCTION: An adverse drug reaction case report refers to a scientific publication that is written by a health care professional who suspects a casual relationship between a drug and an adverse drug reaction (ADR). ADR case reports help to identify potential risks associated with the use of drug. Most of the case reports do not mention about reporting the ADR to regulatory authorities. With this objective, the aim of this study was to analyze the number of Adverse Drug Reactions (ADR) published as case reports (PubMed indexed journals) from January 2018 to June 2019, and observe if they are translated in regulatory frameworks like Vigibase, and package inserts. MATERIALS AND METHODS: 321 ADRs were obtained with the keywords "Adverse Drug Reaction". Out of those, 158 were independently extracted by two investigators, observed and categorized according to classes of the drugs, geographic location, severity, hospitalization, Completeness of ADR, whether reported to the regulatory authority (Vigibase), or listed in the package insert. Literature review articles were excluded. RESULTS: Out of the 158 ADRs, antibiotics accounted for 12.65%, CNS drugs and monoclonal antibodies11.39%, anticancer drugs 9.49%, CVS drugs 4.43%, anti-viral 3.79%, others 45.56%, respectively. According to geographic region, 26 ADRs published were from USA, Australia 4, Italy 3, India 17, Turkey 9, Singapore and UK 1, China 20, Denmark and Canada 2, Japan 10, France 9, Austria 1, Korea 5, South America 3, Switzerland 2, respectively. Depending upon the severity, causality assessment was done only for 45 ADRs, and not done for 113 ADRs. 41.13% patients (from 65 case reports) were hospitalized. Among the 158 ADRs, 14 ADRs were not found in Vigibase. 32 ADRs were not mentioned in the Drug package inserts. When categorized according to the completeness of case reports, weight accounted for1.89%, lab values and procedure for diagnosis, 96.8%, risk factors, 95.56%, prior exposure, 88.60%, Post ADR status, 60.12%, start-stop medication, route of administration, first dose, last dose, duration of illness accounted for 100%, respectively. CONCLUSION: Depending upon our observation, we have noticed that there is deficiency in reporting of suspected ADRs to regulatory authorities. Reporting can be included as mandatory criteria for ADR case reports. Also, there is an increased need to aware various healthcare workers for reporting ADR.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.108
GPT teacher head0.466
Teacher spread0.358 · 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