Evidence map›Paper›PMID 37736714›Full record

ArticleBMC pregnancy and childbirth2023

Influence of organizational factors on the offer and success rate of a trial of labor after cesarean section in Belgium: an ecological study.

Griet Vandenberghe, An Vercoutere, Nadège Cuvellier, Elke Van Oost, Charlotte Leroy, Régine Goemaes, Monika Laubach, Michel Boulvain, Caroline Daelemans, B.OSS collaborating group

Open access · goldAbstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 79% of its field
1 · What the graph read from it

What it found

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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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Griet Vandenberghe *Department of Obstetrics, Ghent University Hospital, Vrouwenkliniek, Corneel Heymanslaan 10, 9000, Ghent, Belgium. griet.vandenberghe@uzgent.be.
An Vercoutere *Department of Gynaecology and Obstetrics, Université Libre de Bruxelles (ULB) Hôpital Universitaire de Bruxelles (H.U.B.), Hôpital Erasme, Route de Lennik 808, Brussels, 1070, Belgium.
Nadège CuvellierDepartment of Gynaecology and Obstetrics, Université Libre de Bruxelles (ULB) Hôpital Universitaire de Bruxelles (H.U.B.), Hôpital Erasme, Route de Lennik 808, Brussels, 1070, Belgium.
Elke Van OostDepartment of Obstetrics, Ghent University Hospital, Vrouwenkliniek, Corneel Heymanslaan 10, 9000, Ghent, Belgium.
Charlotte LeroyCentre d'Epidémiologie Périnatale (CEpiP) Clos Chapelle-Aux-Champs, 30 Bte, B1.30.04 1200, Brussels, Belgium.
Régine GoemaesStudy Centre for Perinatal Epidemiology (SPE), Koning Albert II-Laan 35 Bus 29, 1030, Brussels, Belgium.
Monika LaubachStudy Centre for Perinatal Epidemiology (SPE), Koning Albert II-Laan 35 Bus 29, 1030, Brussels, Belgium.
Michel BoulvainDepartment of Gynaecology and Obstetrics, Université Libre de Bruxelles (ULB) Hôpital Universitaire de Bruxelles (H.U.B.), Hôpital Erasme, Route de Lennik 808, Brussels, 1070, Belgium.
Caroline DaelemansDepartment of Gynaecology and Obstetrics, Université Libre de Bruxelles (ULB) Hôpital Universitaire de Bruxelles (H.U.B.), Hôpital Erasme, Route de Lennik 808, Brussels, 1070, Belgium.
B.OSS collaborating group
Universitair Ziekenhuis Brussel · BEUniversité Libre de Bruxelles · BEGhent University Hospital · BEStatistics Belgium · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTrial of Labor After Cesarean is an important strategy for reducing the overall rate of cesarean delivery. Offering the option of vaginal delivery to a woman with a history of cesarean section requires the ability to manage a potential uterine rupture quickly and effectively. This requires infrastructure and organization of the maternity unit so that the decision-to-delivery interval is as short as possible when uterine rupture is suspected. We hypothesize that the organizational characteristics of maternity units in Belgium have an impact on their proposal and success rates of trial of labour after cesarean section.

methodsWe collected data on the organizational characteristics of Belgian maternity units using an online questionnaire. Data on the frequency of cesarean section, trial of labor and vaginal birth after cesarean section were obtained from regional perinatal registries. We analyzed the determinants of the proposal and success of trial of labor after cesarean section and report the associations as mean proportions.

resultsOf the 101 maternity units contacted, 97 responded to the questionnaire and data from 95 was included in the analysis. Continuous on-site presence of a gynecologist and an anesthetist was associated with a higher proportion of trial of labor after cesarean section, compared to units where staff was on-call from home (51% versus 46%, p = 0.04). There is a non-significant trend towards more trial of labor after cesarean section in units with an operating room in or near the delivery unit and a shorter transfer time, in larger units (> 1500 deliveries/year) and in units with a neonatal intensive care unit. The proposal of trial of labor after cesarean section and its success was negatively correlated to the number of cesarean section in the maternity unit (Spearman' rho = 0.50 and 0.42, p value < 0.001).

conclusionsOrganizational differences in maternity units appear to affect the proposal of trial of labor after cesarean section. Addressing these organizational factors may not be sufficient to change practice, given that general tendency to perform a cesarean section in the maternity unit is the main contributor to the percentage of trial of labor after cesarean.

Indexed as

Cesarean SectionUterine RuptureBelgiumDelivery, ObstetricFemaleHumansInfant, NewbornPregnancyTrial of LaborDecision-to-delivery intervalEmergency cesarean sectionOn-call scheduleTrial of labor after cesareanVaginal birth after cesarean

Identifiers

PMID37736714
PMCPMC10515028
OpenAlexW4386944309

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.