Evidence map›Paper›PMID 33266432›Full record

ArticleNutrients2020

Association between Habitual Dietary Iron Intake and Glucose Metabolism in Individuals after Acute Pancreatitis.

Wandia Kimita, Xinye Li, Juyeon Ko, Sakina H Bharmal, David Cameron-Smith, Maxim S Petrov

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2020. 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
1.6field-weighted citation impact, top 15% 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, 11 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

6 authors at 2 institutions in 2 countries.

Wandia KimitaSchool of Medicine, University of Auckland, Auckland 1023, New Zealand.
Xinye LiSchool of Medicine, University of Auckland, Auckland 1023, New Zealand.
Juyeon KoSchool of Medicine, University of Auckland, Auckland 1023, New Zealand.
Sakina H BharmalSchool of Medicine, University of Auckland, Auckland 1023, New Zealand.
David Cameron-SmithSingapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore 117609, Singapore.
Maxim S PetrovSchool of Medicine, University of Auckland, Auckland 1023, New Zealand.ORCID 0000-0002-5923-9062
University of Auckland · NZAgency for Science, Technology and Research · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dietary intake of iron is known to be associated with impaired glucose metabolism. However, its involvement in derangements of glucose metabolism after acute pancreatitis (AP) is not completely understood. The aim was to investigate the association between dietary iron intake and markers of glucose metabolism in individuals after an attack of AP. Fasting blood samples were collected to analyse markers of glucose metabolism (fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c)). The EPIC-Norfolk food frequency questionnaire was used to determine the habitual intake of dietary iron (total, haem, and non-haem). Multivariable linear regression analyses were conducted and six statistical models were built to adjust for covariates. A total of 109 individuals after AP were studied in a cross-sectional fashion. Total iron (β (95% confidence interval) = -0.19 (-0.35, -0.05);

Indexed as

AdultAgedBiomarkersBlood GlucoseCross-Sectional StudiesFastingFemaleGlucoseGlycated HemoglobinHumansIron, DietaryMaleMiddle AgedPancreatitisProspective StudiesBiomarkersBlood GlucoseGlucoseGlycated HemoglobinIron, Dietaryacute pancreatitisdietary ironfasting plasma glucosehaem ironhaemoglobin A1cnon-haem iron

Identifiers

PMID33266432
PMCPMC7700518
OpenAlexW3108293112

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.