Evidence map›Paper›PMID 33350719›Full record

ArticleMedicine2020

Transvaginal ultrasound cervical length for prediction of spontaneous labor at term: A protocol for systematic review and meta-analysis.

Lirong Wu, Gang Lei, Ming Tan

Abstract read
In one paragraph

Article in Medicine, 2020. 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
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Lirong WuWuhan Hanyang Hospital.
Gang LeiDepartment of Obstetrics and Gynecology, Central Hospital of Wuhan, affiliated to Huazhong University of Science and Technology.
Ming TanHairdressing Department, Hubei Maternal and Child Health Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology, Wuhan City, Hubei Province, China.ORCID 0000-0003-4100-2793

Funding

Hubei Maternal and Child Health Hospital no
6 · The paper itself

Abstract

purposeTo evaluate the predictive accuracy of transvaginal ultrasound (TVU) cervical length (CL) for spontaneous onset of labor in singleton gestation enrolled at term by a meta-analysis. MATERIALS AND

methodsThis protocol established in this study has been reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. Web of Science, PubMed, EMBASE, and the Cochrane Library were searched for all clinical trials assessing the accuracy of TVU CL in prediction of spontaneous onset of labor in singleton gestations with vertex presentation who were enrolled at term until August 15, 2020. We will use a combination of Medical Subject Heading and free-text terms with various synonyms to search based on the eligibility criteria. Two investigators independently reviewed the included studies and extracted relevant data. The 95% confidence intervals (CIs) of was used as effect estimate. I-square (I2) test, substantial heterogeneity, sensitivity analysis, and publication bias assessment will be performed accordingly. Stata 15.0 and Review Manger 5.3 are used for meta-analysis and systematic review.

resultsThe results will be published in a peer-reviewed journal.

conclusionThe results of this review will be widely disseminated through peer-reviewed publications and conference presentations. This evidence may also assess the accuracy of TVU CL in prediction of spontaneous onset of labor in singleton gestations with vertex presentation. REGISTRATION NUMBER: INPLASY202080065.

Indexed as

Cervical Length MeasurementLabor, ObstetricMeta-Analysis as TopicResearch DesignSystematic Reviews as TopicFemaleHumansPredictive Value of TestsPregnancyVagina

Identifiers

PMID33350719
PMCPMC7769322

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.