Evidence map›Paper›PMID 32722394›Full record

ArticleJournal of personalized medicine2020

Correlations between Iron Metabolism Parameters, Inflammatory Markers and Lipid Profile Indicators in Patients with Type 1 and Type 2 Diabetes Mellitus.

Nadezhda N Musina, Tatiana V Saprina, Tatiana S Prokhorenko, Alexander Kanev, Anastasia P Zima

Abstract read
In one paragraph

Article in Journal of personalized medicine, 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
–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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Association of whole blood copper, zinc, calcium, magnesium, and iron with non-alcoholic fatty liver disease in overweight and obese children.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2024
    Article
  4. Article
  5. The Relationship of Hyperferritinemia to Metabolism and Chronic Complications in Type 2 Diabetes.Diabetes, metabolic syndrome and obesity : targets and therapy · 2022
    Article
  6. Article
  7. Article
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

5 authors.

Nadezhda N MusinaSiberian State Medical University, 634050 Tomsk, Russia.
Tatiana V SaprinaSiberian State Medical University, 634050 Tomsk, Russia.
Tatiana S ProkhorenkoSiberian State Medical University, 634050 Tomsk, Russia.
Alexander KanevSiberian State Medical University, 634050 Tomsk, Russia.ORCID 0000-0001-9612-8815
Anastasia P ZimaSiberian State Medical University, 634050 Tomsk, Russia.

Funding

Russian Foundation for Basic Research 19-315-90061
6 · The paper itself

Abstract

This study aims to establish relationships between inflammatory status, ferrokinetics and lipid metabolism in patients with diabetes mellitus. Subclinical inflammation was assessed by levels of high-sensitive C-reactive protein, tumor necrosis factor-α and erythrocyte sedimentation rate. Iron metabolism parameters included complete blood count, serum iron, transferrin and ferritin. Metabolic status assessment included lipid profile, glycated hemoglobin and microalbuminuria measurement. As a result of the study it was possible to establish both general (universal) and diabetes mellitus (DM) type-dependent relationships between the parameters of lipid profile and metabolic control in DM. High-density lipoprotein cholesterol (HDL-C) levels negatively correlated with microalbuminuria (

Indexed as

anemia of chronic diseaseC-reactive proteindiabetes mellituserythrocyte sedimentation ratehyperlipidemiainflammationiron deficiency anemiatumor necrosis factor-α

Identifiers

PMID32722394
PMCPMC7563504

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.