Evidence map›Paper›PMID 31564932›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2019

Correlation analysis of metabolic syndrome and its components with thyroid nodules.

Jingfang Liu, Chenge Wang, Xulei Tang, Songbo Fu, Gaojing Jing, Lihua Ma, Weiming Sun, Yujuan Li, Dan Wu, Ying Niu and 3 more

Abstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Article
  8. Article
  9. Article
  10. Article
  11. Thyroid Nodules and Obesity.Life (Basel, Switzerland) · 2023
    Review
  12. Article
  13. Article
  14. Article
  15. Presence of Metabolic Syndrome and Thyroid Nodules in Subjects with Colorectal Polyps.Medical science monitor : international medical journal of experimental and clinical research · 2021
    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

13 authors.

Jingfang LiuDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Chenge WangDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Xulei TangDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Songbo FuDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Gaojing JingDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Lihua MaDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Weiming SunDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Yujuan LiDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Dan WuDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Ying NiuDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Qianglong NiuDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Huiping GuoDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.
Pei SongDepartment of Endocrinology, The First Hospital of Lanzhou University, Lanzhou, Gansu 730000, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to analyze the relationship between the metabolic syndrome (MetS) and its components with the occurrence of thyroid nodules.

methodsA total of 2719 volunteers from some areas of Gansu Province, China, who participated in the national survey of thyroid diseases and iodine nutrition status (Tide) and diabetes prevalence, were selected. Their height, weight, waist circumference (WC), systolic blood pressure (SBP), and diastolic blood pressure were recorded. The fasting plasma glucose (FPG), 2-h plasma postprandial glucose (2hPG), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and glycosylated hemoglobin (HbA1C) levels were measured. The prevalence of MetS and thyroid nodules was evaluated, and the correlation between each component of MetS and thyroid nodules was studied.

resultsThe prevalence of MetS and thyroid nodules was 15.4% and 17.2%, respectively. WC, SBP, body mass index, FPG, 2hPG, TG, TC, and thyroid-stimulating hormone levels were significantly higher in the thyroid nodule group. The prevalence of thyroid nodules was significantly higher in the MetS group. A positive correlation was found between the degree of metabolic disorder and the occurrence of thyroid nodules. WC was found to be a risk factor for the occurrence of thyroid nodules. For WC≥90 cm, an increase in the independent variables led to a significant rise in the incidence of thyroid nodules.

conclusionThe prevalence of thyroid nodules was higher in the MetS group. The WC of the MetS components might be an independent risk factor for the occurrence of thyroid nodules.

Indexed as

metabolic syndromerisk factorsthyroid noduleswaist circumference

Identifiers

PMID31564932
PMCPMC6724178

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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.