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Comparing very low birth weight versus very low gestation cohort methods for outcome analysis of high risk preterm infants

Overview of attention for article published in BMC Pediatrics, July 2017
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Title
Comparing very low birth weight versus very low gestation cohort methods for outcome analysis of high risk preterm infants
Published in
BMC Pediatrics, July 2017
DOI 10.1186/s12887-017-0921-x
Pubmed ID
Authors

Louise IM Koller-Smith, Prakesh S. Shah, Xiang Y. Ye, Gunnar Sjörs, Yueping A. Wang, Sharon S. W. Chow, Brian A. Darlow, Shoo K. Lee, Stellan Håkanson, Kei Lui, on behalf of the Australian and New Zealand Neonatal Network, Canadian Neonatal Network, Swedish Neonatal Quality Register

Abstract

Compared to very low gestational age (<32 weeks, VLGA) cohorts, very low birth weight (<1500 g; VLBW) cohorts are more prone to selection bias toward small-for-gestational age (SGA) infants, which may impact upon the validity of data for benchmarking purposes. Data from all VLGA or VLBW infants admitted in the 3 Networks between 2008 and 2011 were used. Two-thirds of each network cohort was randomly selected to develop prediction models for mortality and composite adverse outcome (CAO: mortality or cerebral injuries, chronic lung disease, severe retinopathy or necrotizing enterocolitis) and the remaining for internal validation. Areas under the ROC curves (AUC) of the models were compared. VLBW cohort (24,335 infants) had twice more SGA infants (20.4% vs. 9.3%) than the VLGA cohort (29,180 infants) and had a higher rate of CAO (36.5% vs. 32.6%). The two models had equal prediction power for mortality and CAO (AUC 0.83), and similarly for all other cross-cohort validations (AUC 0.81-0.85). Neither model performed well for the extremes of birth weight for gestation (<1500 g and ≥32 weeks, AUC 0.50-0.65; ≥1500 g and <32 weeks, AUC 0.60-0.62). There was no difference in prediction power for adverse outcome between cohorting VLGA or VLBW despite substantial bias in SGA population. Either cohorting practises are suitable for international benchmarking.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 95 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 10 11%
Researcher 9 9%
Student > Master 9 9%
Professor 7 7%
Other 6 6%
Other 24 25%
Unknown 30 32%
Readers by discipline Count As %
Medicine and Dentistry 40 42%
Nursing and Health Professions 6 6%
Psychology 4 4%
Unspecified 2 2%
Social Sciences 2 2%
Other 6 6%
Unknown 35 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 July 2017.
All research outputs
#17,906,525
of 22,990,068 outputs
Outputs from BMC Pediatrics
#2,285
of 3,032 outputs
Outputs of similar age
#224,293
of 312,499 outputs
Outputs of similar age from BMC Pediatrics
#22
of 31 outputs
Altmetric has tracked 22,990,068 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,032 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.