Evidence map›Paper›PMID 29763992›Full record

ArticlePharmacoepidemiology and drug safety2018

Development of an algorithm to identify pregnancy episodes and related outcomes in health care claims databases: An application to antiepileptic drug use in 4.9 million pregnant women in France.

Pierre-Olivier Blotière, Alain Weill, Marie Dalichampt, Cécile Billionnet, Myriam Mezzarobba, Fanny Raguideau, Rosemary Dray-Spira, Mahmoud Zureik, Joël Coste, François Alla

Open access · hybridAbstract read
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
6.9field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

38 citing papers in PubMed, 68 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Pierre-Olivier BlotièreDepartment of Studies in Public Health, French National Health Insurance (CNAMTS), Paris, France.ORCID 0000-0002-6857-6781
Alain WeillDepartment of Studies in Public Health, French National Health Insurance (CNAMTS), Paris, France.ORCID 0000-0001-8687-9092
Marie DalichamptDepartment of Studies in Public Health, French National Health Insurance (CNAMTS), Paris, France.
Cécile BillionnetDepartment of Studies in Public Health, French National Health Insurance (CNAMTS), Paris, France.
Myriam MezzarobbaDepartment of Studies in Public Health, French National Health Insurance (CNAMTS), Paris, France.
Fanny RaguideauDepartment of Epidemiology of Health Products, The French National Agency for Medicines and Health Products Safety, Saint-Denis, France.
Rosemary Dray-SpiraDepartment of Epidemiology of Health Products, The French National Agency for Medicines and Health Products Safety, Saint-Denis, France.
Mahmoud ZureikDepartment of Epidemiology of Health Products, The French National Agency for Medicines and Health Products Safety, Saint-Denis, France.
Joël CosteDepartment of Studies in Public Health, French National Health Insurance (CNAMTS), Paris, France.
François AllaUniversité de Lorraine, université Paris-Descartes, Apemac, EA 4360, Nancy, France.
l'Assurance Maladie · FRAgence Nationale de Sécurité Sanitaire de l’Alimentation, de l’Environnement et du Travail · FRInserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAccess to claims databases provides an opportunity to study medication use and safety during pregnancy. We developed an algorithm to identify pregnancy episodes in the French health care databases and applied it to study antiepileptic drug (AED) use during pregnancy between 2007 and 2014.

methodsThe algorithm searched the French health care databases for discharge diagnoses and medical procedures indicative of completion of a pregnancy. To differentiate claims associated with separate pregnancies, an interval of at least 28 weeks was required between 2 consecutive pregnancies resulting in a birth and 6 weeks for terminations of pregnancy. Pregnancy outcomes were categorized into live births, stillbirths, elective abortions, therapeutic abortions, spontaneous abortions, and ectopic pregnancies. Outcome dates and gestational ages were used to calculate pregnancy start dates.

resultsAccording to our algorithm, live birth was the most common pregnancy outcome (73.9%), followed by elective abortion (17.2%), spontaneous abortion (4.2%), ectopic pregnancy (1.1%), therapeutic abortion (1.0%), and stillbirth (0.4%). These results were globally consistent with French official data. Among 7 559 701 pregnancies starting between 2007 and 2014, corresponding to 4 900 139 women, 6.7 per 1000 pregnancies were exposed to an AED. The number of pregnancies exposed to older AEDs, comprising the most teratogenic AEDs, decreased throughout the study period (-69.4%), while the use of newer AEDs increased (+73.4%).

conclusionsWe have developed an algorithm that allows identification of a large number of pregnancies and all types of pregnancy outcomes. Pregnancy outcome and start dates were accurately identified, and maternal data could be linked to neonatal data.

Indexed as

Pregnancy OutcomeAdolescentAdultAlgorithmsAnticonvulsantsDatabases, FactualEpilepsyFemaleFranceHumansInfant, NewbornMiddle AgedPregnancyPregnancy ComplicationsRisk FactorsYoung AdultAnticonvulsantsalgorithmantiepileptic drugsclaims dataFrench health care databasespharmacoepidemiologypregnancy

Identifiers

PMID29763992
PMCPMC6055607
OpenAlexW2804968317

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.