↓ Skip to main content

Risk‐scoring systems for predicting preterm birth with the aim of reducing associated adverse outcomes

Overview of attention for article published in Cochrane database of systematic reviews, October 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
16 X users
wikipedia
5 Wikipedia pages

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
236 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Risk‐scoring systems for predicting preterm birth with the aim of reducing associated adverse outcomes
Published in
Cochrane database of systematic reviews, October 2015
DOI 10.1002/14651858.cd004902.pub5
Pubmed ID
Authors

Mary‐Ann Davey, Lyndsey Watson, Jo Anne Rayner, Shelley Rowlands

Abstract

Identification of pregnancies that are higher risk than average is important to allow the possibility of interventions aimed at preventing adverse outcomes like preterm birth. Many scoring systems designed to classify the risk of a number of poor pregnancy outcomes (e.g. perinatal mortality, low birthweight, and preterm birth) have been developed, but they have usually been introduced without evaluation of their utility and validity. To determine whether the use of a risk-screening tool designed to predict preterm birth (in combination with appropriate consequent interventions) reduces the incidence of preterm birth and very preterm birth, and associated adverse outcomes. We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (30 June 2015). All randomised or quasi-randomised (including cluster-randomised) or controlled clinical trials that compared the incidence of preterm birth between groups that used a risk-scoring instrument to predict preterm birth with those who used an alternative instrument, or no instrument; or that compared the use of the same instrument at different gestations. The reports may have been published in peer reviewed or non-peer reviewed publications, or not published, and written in any language. All review authors planned to independently assess for inclusion all the potential studies we identified as a result of the search strategy. However, we did not identify any eligible studies. Searching revealed no trials of the use of risk-scoring systems for preventing preterm birth. The role of risk-scoring systems in the prevention of preterm birth is unknown.There is a need for prospective studies that evaluate the use of a risk-screening tool designed to predict preterm birth (in combination with appropriate consequent interventions) to prevent preterm birth, including qualitative and/or quantitative evaluation of their impact on women's well-being. If these prove promising, they should be followed by an adequately powered, well-designed randomised controlled trial.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 236 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 <1%
United States 1 <1%
Unknown 234 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 34 14%
Student > Bachelor 29 12%
Student > Ph. D. Student 28 12%
Researcher 21 9%
Student > Doctoral Student 14 6%
Other 37 16%
Unknown 73 31%
Readers by discipline Count As %
Medicine and Dentistry 95 40%
Nursing and Health Professions 17 7%
Social Sciences 10 4%
Psychology 8 3%
Engineering 4 2%
Other 24 10%
Unknown 78 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 August 2023.
All research outputs
#2,838,748
of 25,595,500 outputs
Outputs from Cochrane database of systematic reviews
#5,593
of 13,156 outputs
Outputs of similar age
#38,473
of 294,709 outputs
Outputs of similar age from Cochrane database of systematic reviews
#175
of 302 outputs
Altmetric has tracked 25,595,500 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,156 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.8. This one has gotten more attention than average, scoring higher than 57% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 294,709 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 302 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.