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Record W2958188060 · doi:10.1371/journal.pone.0219095

The French Pregnancy Cohort: Medication use during pregnancy in the French population

2019· article· en· W2958188060 on OpenAlexaff
Anick Bérard, Fatima Abbas‐Chorfa, Behrouz Kassaï, Thierry Vial, Kim An Nguyen, Odile Sheehy, Anne‐Marie Schott

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsPregnancyMedicineMedical prescriptionPopulationCohortMedical recordObstetricsSpecialtyCohort studyFamily medicineGestationPediatricsEnvironmental healthNursingSurgeryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: We described the medication use during pregnancy in the French population using the French Pregnancy Cohort (FPC). METHODS: The FPC was built with the sampling of all pregnant women included in the French Echantillon généraliste des bénéficiaires (EGB), which is a 1/97th representative sample of the population covered by the French health insurance. The EGB includes anonymized information on the socio-demographic and medical characteristics of beneficiaries, and the health care services they have received such as diagnoses and procedure codes as well as data on filled reimbursed medication; EGB also includes data on hospital stays in all public and private French health facilities. Each filled prescription record contains information on drug brand and generic names, date of prescription and date of dispensing, quantity dispensed, mode of administration, duration of prescription, dosage, and prescribing physician specialty. FPC includes data on all pregnancies of women in the EGB (2010-2013). Date of entry in the FPC is the first day of pregnancy regardless of pregnancy outcome (spontaneous abortions or planned abortions (with or without medical reasons), deliveries), and data on women are collected retrospectively for a period of one year before pregnancy, and prospectively during pregnancy, and up to one year after delivery. The prevalence of prescribed medications before, during and after pregnancy was compared; comparison was also done between trimesters. Pregnancy outcomes are described and include spontaneous and planned abortions, livebirths, and stillbirths. RESULTS: FPC includes data on 36,065 pregnancies. Among them, 27,253 (75.6%) resulted in a delivery including 201 stillbirths (0.7%). The total number of spontaneous abortions was 6,718 (18.6%), and planned abortions 2,094 (5.8%). The prevalence of filled medication use was 91.1%, 89.9%, and 95.6% before, during and after pregnancy, respectively. Although there was a statistically significant decrease in the proportion of use once the pregnancy was diagnosed (first trimester exposure, 76.4% vs. exposure in the year prior to pregnancy, 91.1% (p < .01)), post-pregnancy medication use was above the pre-pregnancy level (95.6%). Maternal depression was the most prevalent comorbidity during pregnancy (20%), and post-partum depression was higher in those who delivered a stillborn infant (38.8%) as well as in those with a spontaneous (19.5%) or planned abortion (22.4%) compared to those with a liveborn (12.0%). CONCLUSION: FPC is an excellent tool for the study of the risk and benefit of drug use during the perinatal period. FPC has the advantage of including a representative sample of French pregnant women, and study medications only available in France in addition to others available worldwide.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.039
GPT teacher head0.264
Teacher spread0.225 · 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

Citations90
Published2019
Admission routes1
Has abstractyes

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