Evidence map›Paper›PMID 26131329›Full record

ArticleWorld journal of diabetes2015

Pregnancy and neonatal outcomes in Indigenous Australians with diabetes in pregnancy.

Victor Duong, Bronwyn Davis, Henrik Falhammar

Open access · diamondAbstract read
In one paragraph

Article in World journal of diabetes, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 17 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Victor DuongVictor Duong, Royal Darwin Hospital, Tiwi NT 0810, Australia.
Bronwyn DavisVictor Duong, Royal Darwin Hospital, Tiwi NT 0810, Australia.
Henrik FalhammarVictor Duong, Royal Darwin Hospital, Tiwi NT 0810, Australia.
Royal Darwin Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo perform a systematic review of reported neonatal and pregnancy outcomes of Indigenous Australians with diabetes in pregnancy (DIP).

methodsElectronic searches of PubMed and Web of Science were carried out. Articles were selected if they contained original data on DIP outcomes in Indigenous Australians. There were no specific exclusion criteria.

resultsA total of eight articles, predominantly from Queensland and Western Australia were identified once inclusion criteria were applied. Birth data from midwifery registries or paper charts encompassing years 1985-2008 were used. A total of 465591 pregnant women with and without DIP were included in the eight studies, with 1363 being Indigenous women with DIP. Indigenous Australians experienced increased rates of many known adverse outcomes of DIP including: macrosomia, caesarean section, congenital deformities, low birth weight, hypoglycaemia, and neonatal trauma. There were regional differences among Indigenous Australians, particularly regional/remote vs metropolitan populations where the regional/remote data showed worse outcomes. Two of the articles did not note a difference between Aboriginals and Caucasians in the rates of measured adverse outcome. Studies varied significantly in size, measured outcomes, and subsequent analysis.

conclusionThe health disparities between Indigenous Australians and non-Indigenous Australians are further evidenced by poorer outcomes in DIP. This has broader implications for Indigenous health in general.

Indexed as

AboriginalDiabetesGestationalHyperglycaemiaIndigenousOutcomesPregnancyTorres Strait Islander

Identifiers

PMID26131329
PMCPMC4478583
OpenAlexW1811555603

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.