Evidence map›Paper›PMID 33513630›Full record

ArticleRevista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia2021

Is it Possible to Predict Massive Bleeding in Nulliparous Women with Placenta Previa?

Gokcen Orgul, Sule Goncu Ayhan, Gulhan Cetinkaya Saracoglu, Aykan Yucel

Open access · diamondAbstract read
In one paragraph

Article in Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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

4 authors at 1 institution in 1 country.

Gokcen OrgulDepartment of Perinatology, University of Health Sciences, Ankara, Turkey.ORCID 0000-0003-0578-4230
Sule Goncu AyhanDepartment of Perinatology, University of Health Sciences, Ankara, Turkey.ORCID 0000-0003-4523-6677
Gulhan Cetinkaya SaracogluDepartment of Perinatology, University of Health Sciences, Ankara, Turkey.ORCID 0000-0002-5169-428X
Aykan YucelDepartment of Perinatology, University of Health Sciences, Ankara, Turkey.ORCID 0000-0002-5888-692X
Ankara University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe evaluated risk factors to determine if there were specific risk factors that could predict massive bleeding in nulliparous women with placenta previa.

methodsThe participants were classified into two groups. Women with a calculated blood loss ≥ 1,000 mL were included in the massive bleeding group. Women without any signs or symptoms related with hypovolemia or with a calculated bleeding volume < 1,000 mL were categorized into the non-massive bleeding group.

resultsThere were 28 patients (40.6%) with massive bleeding and 41 cases (59.4%) with non-massive bleeding. The calculated blood loss and number of cases that required red cell transfusions were statistically different between the groups (< 0.005 and 0.002, respectively). There were no statistically significant differences in terms of maternal or fetal factors, placental location, or delivery characteristics between the two groups.

conclusionWe could not determine the predictive features for massive hemorrhage based on clinical features, delivery features, or placental location.

Indexed as

Placenta PreviaPrenatal DiagnosisAdultCesarean SectionFemaleHumansParityPostpartum HemorrhagePredictive Value of TestsPregnancy

Identifiers

PMID33513630
PMCPMC10183915
OpenAlexW3123160633

What OpenQuestion holds

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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.