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Record W4379056326 · doi:10.3389/fphar.2023.1094698

Expert consensus on neurodevelopmental outcomes in pregnancy pharmacovigilance studies

2023· article· en· W4379056326 on OpenAlexaff
Rebecca Bromley, Myriam Bickle Graz, Matthew Bluett‐Duncan, Christina Chambers, Per Damkier, K Dietrich, Helen Dolk, Kimberly S. Grant, Sarah N. Mattson, Kimford J. Meador, Hedvig Nordeng, Tim F. Oberlander, Asher Ornoy, Alexis Revet, Jennifer L. Richardson, Joanne Rovet, Lavínia Schüler‐Faccini, Erica Smearman, Victoria Simms, Charles V. Vorhees, Katarina Wide, Amanda Wood, Laura Yates, Eivind Ystrøm, T. A. Supraja, J. Adams

Bibliographic record

VenueFrontiers in Pharmacology · 2023
Typearticle
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoUniversity of British Columbia
FundersEuropean CommissionEuropean Federation of Pharmaceutical Industries and Associations
KeywordsPharmacovigilanceMedicineDelphi methodPregnancyNeurodevelopmental disorderPsychiatryDrugAutismComputer science

Abstract

fetched live from OpenAlex

Background: Exposure in utero to certain medications can disrupt processes of fetal development, including brain development, leading to a continuum of neurodevelopmental difficulties. Recognizing the deficiency of neurodevelopmental investigations within pregnancy pharmacovigilance, an international Neurodevelopmental Expert Working Group was convened to achieve consensus regarding the core neurodevelopmental outcomes, optimization of methodological approaches and barriers to conducting pregnancy pharmacovigilance studies with neurodevelopmental outcomes. Methods: A modified Delphi study was undertaken based on stakeholder and expert input. Stakeholders (patient, pharmaceutical, academic and regulatory) were invited to define topics, pertaining to neurodevelopmental investigations in medication-exposed pregnancies. Experts were identified for their experience regarding neurodevelopmental outcomes following medicinal, substances of misuse or environmental exposures in utero . Two questionnaire rounds and a virtual discussion meeting were used to explore expert opinion on the topics identified by the stakeholders. Results: Twenty-five experts, from 13 countries and professionally diverse backgrounds took part in the development of 11 recommendations. The recommendations focus on the importance of neurodevelopment as a core feature of pregnancy pharmacovigilance, the timing of study initiation and a core set of distinct but interrelated neurodevelopmental skills or diagnoses which require investigation. Studies should start in infancy with an extended period of investigation into adolescence, with more frequent sampling during rapid periods of development. Additionally, recommendations are made regarding optimal approach to neurodevelopmental outcome measurement, comparator groups, exposure factors, a core set of confounding and mediating variables, attrition, reporting of results and the required improvements in funding for potential later emerging effects. Different study designs will be required depending on the specific neurodevelopmental outcome type under investigation and whether the medicine in question is newly approved or already in widespread use. Conclusion: An improved focus on neurodevelopmental outcomes is required within pregnancy pharmacovigilance. These expert recommendations should be met across a complementary set of studies which converge to form a comprehensive set of evidence regarding neurodevelopmental outcomes in pregnancy pharmacovigilance.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.065
GPT teacher head0.412
Teacher spread0.347 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations19
Published2023
Admission routes1
Has abstractyes

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