Evidence map›Paper›PMID 32699319›Full record

Observational studyScientific reports2020

Volatile organic compound analysis, a new tool in the quest for preterm birth prediction-an observational cohort study.

Lauren Lacey, Emma Daulton, Alfian Wicaksono, James A Covington, Siobhan Quenby

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 25% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Article
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  5. Article
  6. Review
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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

5 authors at 2 institutions in 1 country.

Lauren LaceyWarwick Medical School, University of Warwick, Coventry, CV4 7AL, UK. l.lacey.1@warwick.ac.uk.
Emma DaultonSchool of Engineering, University of Warwick, Coventry, CV4 7AL, UK.
Alfian WicaksonoSchool of Engineering, University of Warwick, Coventry, CV4 7AL, UK.
James A CovingtonSchool of Engineering, University of Warwick, Coventry, CV4 7AL, UK.
Siobhan QuenbyWarwick Medical School, University of Warwick, Coventry, CV4 7AL, UK.
University of Warwick · GBCoventry (United Kingdom) · GB

Funding

Medical Research Council MR/R014167/1
6 · The paper itself

Abstract

Preterm birth is the leading cause of death worldwide in children under five years. Due to its complex multifactorial nature, prediction is a challenge. Current research is aiming to develop accurate predictive models using patient history, ultrasound and biochemical markers. Volatile organic compound (VOC) analysis is an approach, which has good diagnostic potential to predict many disease states. Analysis of VOCs can reflect both the microbiome and host response to a condition. We aimed to ascertain if VOC analysis of vaginal swabs, taken throughout pregnancy, could predict which women go on to deliver preterm. Our prospective observational cohort study demonstrates that VOC analysis of vaginal swabs, taken in the midtrimester, is a fair test (AUC 0.79) for preterm prediction, with a sensitivity of 0.66 (95%CI 0.56-0.75) and specificity 0.89 (95%CI 0.82-0.94). Using vaginal swabs taken closest to delivery, VOC analysis is a good test (AUC 0.84) for the prediction of preterm birth with a sensitivity of 0.73 (95%CI 0.64-0.81) and specificity of 0.90 (95%CI 0.82-0.95). Consequently, VOC analysis of vaginal swabs has potential to be used as a predictive tool. With further work it could be considered as an additional component in models for predicting preterm birth.

Indexed as

AdultArea Under CurveFemaleGas Chromatography-Mass SpectrometryHumansMicrobiotaPregnancyPregnancy Trimester, SecondPremature BirthROC CurveSensitivity and SpecificityVaginaVolatile Organic CompoundsVolatile Organic Compounds

Identifiers

PMID32699319
PMCPMC7376243
OpenAlexW3044213565

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.