Evidence map›Paper›PMID 34066203›Full record

ArticleJournal of clinical medicine2021

Serum C-Reactive Protein and Interleukin-6 Levels as Biomarkers for Disease Severity and Clinical Outcomes in Patients with Idiopathic Granulomatous Mastitis.

Yi-Min Huang, Chiao Lo, Chiao-Feng Cheng, Cheng-Hsun Lu, Song-Chou Hsieh, Ko-Jen Li

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

18 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Review
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. 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

6 authors at 1 institution in 1 country.

Yi-Min HuangDepartment of Internal Medicine, National Taiwan University Hospital Yunlin branch, Yunlin 640, Taiwan.ORCID 0000-0002-7920-0341
Chiao LoDepartment of Surgery, National Taiwan University Hospital, Taipei 100, Taiwan.
Chiao-Feng ChengDepartment of Internal Medicine, National Taiwan University Hospital Yunlin branch, Yunlin 640, Taiwan.ORCID 0000-0002-8618-9945
Cheng-Hsun LuDepartment of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan.ORCID 0000-0002-4794-9438
Song-Chou HsiehDepartment of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan.
Ko-Jen LiDepartment of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan.ORCID 0000-0002-4544-4620
National Taiwan University Hospital · TW

Funding

National Taiwan University Hospital NTUH-107-003899
6 · The paper itself

Abstract

Idiopathic granulomatous mastitis (IGM) is a rare inflammatory breast disease mimicking breast cancer. Limited research has been conducted on the application of serum biomarkers. This study aims to investigate the association of serum biomarkers with disease severity in patients with IGM. From November 2011 to March 2020, medical records of patients with IGM were reviewed. Serum cytokine levels were measured in patients and healthy controls between July 2018 and March 2020. A total of 41 patients with histologically proven IGM were found. Serum interleukin (IL)-6 level was significantly higher in patients with IGM (

Indexed as

C-reactive proteindisease severityidiopathic granulomatous mastitisinterleukin-6time to resolution

Identifiers

PMID34066203
PMCPMC8150275
OpenAlexW3161005629

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.