Evidence map›Paper›PMID 28410926›Full record

ArticleJournal of diabetes and its complications2017

Effect of high density lipoprotein cholesterol on the relationship of serum iron and hemoglobin with kidney function in diabetes.

Ashley N Williams, Baqiyyah N Conway

Abstract read
In one paragraph

Article in Journal of diabetes and its complications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

8 citing papers in PubMed, 13 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

2 authors at 1 institution in 1 country.

Ashley N WilliamsDepartment of Epidemiology, West Virginia University, Morgantown, WV.
Baqiyyah N ConwayDepartment of Epidemiology, West Virginia University, Morgantown, WV. Electronic address: baqiyyah@yahoo.com.
West Virginia University · US

Funding

West Virginia IDEA-CTRU54GM104942 · NIGMS · WEST VIRGINIA UNIVERSITY · PI Sally Lynn Hodder · 2012 to 2026
$81.0M
NIGMS NIH HHS U54 GM104942
6 · The paper itself

Abstract

Findings of increased hemoglobin inside the HDL proteome among persons with diabetes who have haptoglobin 2-2 genotype suggest that iron-induced lipid peroxidation may be involved in diabetic kidney disease. We investigated the relationships of serum hemoglobin and iron with kidney function, and whether this varied by level of HDLc, in 5296 adults with and 49,161 without diabetes. Estimated eGFR was our marker of kidney function. Hemoglobin was positively associated with eGFR among those with diabetes and inversely among those without diabetes (interaction p-value <0.0001). Iron was inversely associated with eGFR regardless of diabetes status. When stratified by median HDLc and median hemoglobin, among persons with diabetes mean eGFR was highest in those with high hemoglobin and low HDLc and lowest in those with both low hemoglobin and low HDLc. This divergent relationship was not observed in the non-diabetic population. In contrast to hemoglobin, high iron and low HDLc were associated with a lower mean eGFR regardless of diabetes status. Our data suggest that among persons with diabetes, both hemoglobin and iron are harmful to kidney function at high levels. Our data also suggest that HDLc may play a role in the relationship of high hemoglobin in kidney function in diabetes.

Indexed as

AdultAgedCholesterol, HDLDiabetes MellitusDiabetic NephropathiesFemaleGlomerular Filtration RateHemoglobinsHumansIronKidneyMaleMiddle AgedRisk FactorsCholesterol, HDLHemoglobinsIron

Identifiers

PMID28410926
PMCPMC5560583
OpenAlexW2599363432

What OpenQuestion holds

Textmetadata
LicenceTDM
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.