Evidence map›Paper›PMID 28709451›Full record

Observational studyBMC pediatrics2017

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

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 and 3 more

Abstract readComparative StudyObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in BMC pediatrics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

  1. Twin Birth Weight Chart Comparisons in Korea.Journal of Korean medical science · 2026
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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

13 authors.

Louise Im Koller-SmithFaculty of Health Science, University of Technology Sydney, Sydney, NSW, Australia.
Prakesh S ShahDepartment of Pediatrics, Mount Sinai Hospital and University of Toronto, Toronto, ON, Canada.
Xiang Y YeMaternal Infant Care Research Centre, Mount Sinai Hospital, Toronto, ON, Canada.
Gunnar SjörsUppsala University, Uppsala, Sweden.
Yueping A WangFaculty of Health Science, University of Technology Sydney, Sydney, NSW, Australia.
Sharon S W ChowFaculty of Health Science, University of Technology Sydney, Sydney, NSW, Australia.
Brian A DarlowDepartment of Paediatrics, University of Otago, Christchurch, New Zealand.
Shoo K LeeDepartment of Pediatrics, Mount Sinai Hospital and University of Toronto, Toronto, ON, Canada.
Stellan HåkansonUmeå University Hospital, Umeå, Sweden.
Kei LuiFaculty of Health Science, University of Technology Sydney, Sydney, NSW, Australia. k.lui@unsw.edu.au.
Australian and New Zealand Neonatal Network
Canadian Neonatal Network
Swedish Neonatal Quality Register

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCompared 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.

methodData 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.

resultsVLBW 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).

conclusionThere 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.

Indexed as

Hospital MortalityInfant, Extremely PrematureInfant MortalityInfant, Small for Gestational AgeInfant, Very Low Birth WeightArea Under CurveAustraliaBenchmarkingCanadaDecision Support TechniquesFemaleGestational AgeHumansInfantInfant, NewbornInfant, PrematureBenchmarkingInfantIntensive careNeonatalOutcomePrematureSmall for gestational ageVery low birth weight

Identifiers

PMID28709451
PMCPMC5512978

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.