Evidence map›Paper›PMID 35534768›Full record

ArticleReproductive sciences (Thousand Oaks, Calif.)2022

Racial and Ethnic Disparities Among Women Undergoing a Trial of Labor After Cesarean Delivery: Performance of the VBAC Calculator with and without Patients' Race/Ethnicity.

Ayisha Buckley, Stephanie Sestito, Tonia Ogundipe, Jacqueline Roig, Henri Mitchell Rosenberg, Natalie Cohen, Kelly Wang, Guillaume Stoffels, Teresa Janevic, Chelsea DeBolt and 5 more

Abstract read
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In one paragraph

Article in Reproductive sciences (Thousand Oaks, Calif.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 6% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 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

15 authors at 1 institution in 1 country.

Ayisha BuckleyIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA. Abb08c@gmail.com.ORCID 0000-0003-2748-2022
Stephanie SestitoIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Tonia OgundipeIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Jacqueline RoigIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Henri Mitchell RosenbergIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Natalie CohenIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Kelly WangIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Guillaume StoffelsIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Teresa JanevicIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Chelsea DeBoltIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Camila CabreraIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Elizabeth CochraneIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Jill BerkinIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Angela BiancoIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Luciana VieiraIcahn School of Medicine at Mount Sinai Hospital, New York, NY, 10029, USA.
Mount Sinai Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Maternal Fetal Medicine Units Network (MFMU) vaginal birth after cesarean (VBAC) calculator is a clinical tool designed to predict trial of labor after cesarean delivery (TOLAC) success. The calculator has come under scrutiny for its inclusion of race and ethnicity, which systematically predicts a lower likelihood of success for patients who identify as African American or Hispanic. We hypothesized that the calculator would predict VBAC more accurately without the use of race or ethnicity. A retrospective chart review including all patients undergoing TOLAC from 2016 to 2019 was conducted. A multivariate logistic regression was used to compare one model that utilizes the original variables in predicting VBAC (model 1) and another that uses the same variables except for race and ethnicity (model 2). In model 1, race and ethnicity were the only variables not associated with the probability of successful TOLAC (p = 0.065). The area under the curve (AUC) for models 1 and 2 were 0.77 and 0.78, respectively. There was not a statistically significant difference between the predictive abilities of the two models (p = 0.40). Rates of PPH (p = 0.001), abruption (p = 0.04), intra-amniotic infection (p < 0.0001), and other postpartum complications (p = 0.005) differed significantly by race and ethnicity. The use of race and ethnicity did not contribute to the accuracy of VBAC prediction. The use of race and ethnicity in this predictive model should be omitted to prevent inherent bias and discrimination. There were also significant racial and ethnic differences in overall postpartum complication rates.

Indexed as

Vaginal Birth after CesareanCesarean SectionEthnicityFemaleHumansPregnancyRetrospective StudiesTrial of LaborRacial and ethnic disparitiesTrial of labor after cesarean deliveryVaginal birth after cesarean

Identifiers

PMID35534768
OpenAlexW4229446151

What OpenQuestion holds

Textmetadata
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.