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Non-nutritive sucking for increasing physiologic stability and nutrition in preterm infants

Overview of attention for article published in Cochrane database of systematic reviews, October 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
policy
1 policy source
twitter
6 tweeters
facebook
4 Facebook pages
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
245 Mendeley
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Title
Non-nutritive sucking for increasing physiologic stability and nutrition in preterm infants
Published in
Cochrane database of systematic reviews, October 2016
DOI 10.1002/14651858.cd001071.pub3
Pubmed ID
Authors

Jann P Foster, Kim Psaila, Tiffany Patterson

Abstract

Non-nutritive sucking (NNS) is used during gavage feeding and in the transition from gavage to breast/bottle feeding in preterm infants to improve the development of sucking behavior and the digestion of enteral feedings. To assess the effects of non-nutritive sucking on physiologic stability and nutrition in preterm infants. We used the standard search strategy of the Cochrane Neonatal Review group to search the Cochrane Central Register of Controlled Trials (CENTRAL; 2016, Issue 1), MEDLINE via PubMed (1966 to 25 February 2016), Embase (1980 to 25 February 2016), and CINAHL (1982 to 25 February 2016). We also searched clinical trials databases, conference proceedings, and the reference lists of retrieved articles for randomised controlled trials. Randomised controlled trials and quasi-randomised trials that compared non-nutritive sucking versus no provision of non-nutritive sucking in preterm infants. We excluded cross-over trials. Two review authors assessed trial eligibility and risk of bias and undertook data extraction independently. We analysed the treatment effects in the individual trials and reported mean differences (MD) for continuous data, with 95% confidence intervals (CIs). We used a fixed-effect model in meta-analyses. We did not perform subgroup analyses because of the small number of studies related to the relevant outcomes. We used the GRADE approach to assess the quality of evidence. We identified 12 eligible trials enrolling a total of 746 preterm infants. Meta-analysis, though limited by data quality, demonstrated a significant effect of NNS on transition from gavage to full oral feeding (MD -5.51 days, 95% CI -8.20 to -2.82; N = 87), transition from start of oral feeding to full oral feeding (MD -2.15 days, 95% CI -3.12 to -1.17; N = 100), and the length of hospital stay (MD -4.59 days, 95% CI -8.07 to -1.11; N = 501). Meta-analysis revealed no significant effect of NNS on weight gain. One study found that the NNS group had a significantly shorter intestinal transit time during gavage feeding compared to the control group (MD -10.50 h, 95% CI -13.74 to -7.26; N = 30). Other individual studies demonstrated no clear positive effect of NNS on age of infant at full oral feeds, days from birth to full breastfeeding, rates and proportion of infants fully breastfeeding at discharge, episodes of bradycardia, or episodes of oxygen desaturation. None of the studies reported any negative outcomes. These trials were generally small and contained various methodological weaknesses including lack of blinding of intervention and outcome assessors and variability on outcome measures. The quality of the evidence on outcomes assessed according to GRADE was low to very low. Meta-analysis demonstrated a significant effect of NNS on the transition from gavage to full oral feeding, transition from start of oral feeding to full oral feeding, and length of hospital stay. None of the trials reported any adverse effects. Well-designed, adequately powered studies using reliable methods of randomisation, concealment of treatment allocation and blinding of the intervention and outcome assessors are needed. In order to facilitate meta-analysis of these data, future research should involve outcome measures consistent with those used in previous studies.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 245 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
South Africa 1 <1%
Portugal 1 <1%
Ethiopia 1 <1%
Spain 1 <1%
United States 1 <1%
Korea, Republic of 1 <1%
Canada 1 <1%
Unknown 236 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 50 20%
Student > Bachelor 37 15%
Unspecified 28 11%
Other 25 10%
Student > Ph. D. Student 24 10%
Other 81 33%
Readers by discipline Count As %
Medicine and Dentistry 91 37%
Nursing and Health Professions 65 27%
Unspecified 39 16%
Social Sciences 11 4%
Psychology 9 4%
Other 30 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 20 June 2017.
All research outputs
#462,721
of 12,527,219 outputs
Outputs from Cochrane database of systematic reviews
#1,481
of 8,923 outputs
Outputs of similar age
#17,671
of 265,542 outputs
Outputs of similar age from Cochrane database of systematic reviews
#37
of 173 outputs
Altmetric has tracked 12,527,219 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,923 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.2. This one has done particularly well, scoring higher than 93% 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 265,542 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 173 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.