Evidence map›Paper›PMID 33323131›Full record

ArticleDiagnostic and prognostic research2020

Protocol for the development and validation of a risk prediction model for stillbirths from 35 weeks gestation in Australia.

Jessica K Sexton, Michael Coory, Sailesh Kumar, Gordon Smith, Adrienne Gordon, Georgina Chambers, Gavin Pereira, Camille Raynes-Greenow, Lisa Hilder, Philippa Middleton and 6 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diagnostic and prognostic research, 2020. 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
0.9field-weighted citation impact, top 23% 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, 4 citations in OpenAlex.

  1. Article
  2. Article
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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

16 authors at 9 institutions in 3 countries.

Jessica K SextonNHMRC Centre of Research Excellence in Stillbirth, Mater Research Institute - University of Queensland, Level 3 Aubigny Place, Brisbane, 4101, Australia. jessica.sexton@uq.edu.au.
Michael CooryNHMRC Centre of Research Excellence in Stillbirth, Mater Research Institute - University of Queensland, Level 3 Aubigny Place, Brisbane, 4101, Australia.
Sailesh KumarSchool of Medicine, University of Queensland, Brisbane, Australia.
Gordon SmithDepartment of Obstetrics & Gynaecology, University of Cambridge, Cambridge, UK.
Adrienne GordonSydney Medical School, University of Sydney, Sydney, Australia.
Georgina ChambersUniversity of New South Wales, Sydney, Australia.
Gavin PereiraSchool of Public Health, Curtin University, Perth, Australia.
Camille Raynes-GreenowSchool of Public Health, The University of Sydney, Sydney, Australia.
Lisa HilderNational Perinatal Epidemiology and Statistics Unit, Centre for Big Data Research in Health and School of Women's and Children's Health, University of New South Wales, Sydney, Australia.
Philippa MiddletonSouth Australian Health and Medical Research Institute, SAHMRI Women and Kids, Adelaide, Australia.
Anneka BowmanSouth Australian Health and Medical Research Institute, SAHMRI Women and Kids, Adelaide, Australia.
Scott N LieskeUniversity of Queensland, Brisbane, Australia.
Kara WarrilowNHMRC Centre of Research Excellence in Stillbirth, Mater Research Institute - University of Queensland, Level 3 Aubigny Place, Brisbane, 4101, Australia.
Jonathan MorrisWomen and Babies Research, The University of Sydney Northern Clinical School, St. Leonards, Australia.
David EllwoodNHMRC Centre of Research Excellence in Stillbirth, Mater Research Institute - University of Queensland, Level 3 Aubigny Place, Brisbane, 4101, Australia.
Vicki FlenadyNHMRC Centre of Research Excellence in Stillbirth, Mater Research Institute - University of Queensland, Level 3 Aubigny Place, Brisbane, 4101, Australia. vicki.flenady@mater.uq.edu.au.
University of Queensland · AUMater Research · AUSouth Australian Health and Medical Research Institute · AUUniversity of Sydney · AUUNSW Sydney · AUCurtin University · AUGriffith University · AUNorthern Sydney Local Health District · AUUniversity of Cambridge · GB

Funding

National Health and Medical Research Council 1116640
6 · The paper itself

Abstract

backgroundDespite advances in the care of women and their babies in the past century, an estimated 1.7 million babies are born still each year throughout the world. A robust method to estimate a pregnant woman's individualized risk of late-pregnancy stillbirth is needed to inform decision-making around the timing of birth to reduce the risk of stillbirth from 35 weeks of gestation in Australia, a high-resource setting.

methodsThis is a protocol for a cross-sectional study of all late-pregnancy births in Australia (2005-2015) from 35 weeks of gestation including 5188 stillbirths among 3.1 million births at an estimated rate of 1.7 stillbirths per 1000 births. A multivariable logistic regression model will be developed in line with current Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) guidelines to estimate the gestation-specific probability of stillbirth with prediction intervals. Candidate predictors were identified from systematic reviews and clinical consultation and will be described through univariable regression analysis. To generate a final model, elimination by backward stepwise multivariable logistic regression will be performed. The model will be internally validated using bootstrapping with 1000 repetitions and externally validated using a temporally unique dataset. Overall model performance will be assessed with R DISCUSSION: A robust method to predict a pregnant woman's individualized risk of late-pregnancy stillbirth is needed to inform timely, appropriate care to reduce stillbirth. Among existing prediction models designed for obstetric use, few have been subject to internal and external validation and many fail to meet recommended reporting standards. In developing a risk prediction model for late-gestation stillbirth with both providers and pregnant women in mind, we endeavor to develop a validated model for clinical use in Australia that meets current reporting standards.

Indexed as

AUROCFetal deathObstetricsPerinatalPredictionPrognosticRiskStillbirth

Identifiers

PMID33323131
PMCPMC7739473
OpenAlexW3098916736

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.