Evidence map›Paper›PMID 32148489›Full record

ArticleInternational journal of endocrinology2020

The Prevalence of Single and Multiple Thyroid Nodules and Its Association with Metabolic Diseases in Chinese: A Cross-Sectional Study.

Bing Zou, Li Sun, Xin Wang, Zongtao Chen

Open access · goldAbstract read
In one paragraph

Article in International journal of endocrinology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.6field-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

15 citing papers in PubMed, 29 citations in OpenAlex.

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

4 authors at 1 institution in 1 country.

Bing ZouHealth Management Center, Southwest Hospital, Army Military Medical University, Chongqing 400038, China.
Li SunHealth Management Center, Southwest Hospital, Army Military Medical University, Chongqing 400038, China.
Xin WangDepartment of Epidemiology and Biostatistics, Southwest Hospital, Army Military Medical University, Chongqing 400038, China.ORCID https://orcid.org/0000-0001-9325-3194
Zongtao ChenHealth Management Center, Southwest Hospital, Army Military Medical University, Chongqing 400038, China.ORCID https://orcid.org/0000-0001-6720-9827
Southwest Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe present study aims to investigate the prevalence of single and multiple thyroid nodules and its association with metabolic diseases in subjects who participated in the heath examination in China.

methodsThis is a cross-sectional study. The participants who attend the physical examination at the Health Management Center of Southwest Hospital, Army Military Medical University, between January 2014 and December 2018, were included. Thyroid nodules were diagnosed by thyroid ultrasound. Multivariable logistic regression was used to investigate the association between metabolic diseases and nodular thyroid disease.

resultsA total of 9,146 subjects were included in this study; of them, 2,961 were diagnosed with thyroid nodules, with a prevalence of 32.4%. The prevalence in women was significantly higher than that in men (45.2%

conclusionsThe prevalence of thyroid nodules was relatively high. Age, female gender, and diabetes are positively associated with nodular thyroid disease. High LDL cholesterolemia is more likely to be associated with multiple thyroid sarcoidosis.

Identifiers

PMID32148489
PMCPMC7042532
OpenAlexW3005713898

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.