Evidence map›Paper›PMID 35058879›Full record

SynthesisFrontiers in endocrinology2021

The Association Between COVID-19 and Thyroxine Levels: A Meta-Analysis.

Yiru Chen, Xiuneng Li, Yu Dai, Jingjing Zhang

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Frontiers in endocrinology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.9field-weighted citation impact, top 4% 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

17 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
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  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Thyroid Dysfunction among the Patients with Critical COVID-19.Infectious diseases & clinical microbiology · 2022
    Article
  14. The Potential of Thyroid Hormone Therapy in Severe COVID-19: Rationale and Preliminary Evidence.International journal of environmental research and public health · 2022
    Review
  15. Article
  16. Article
  17. Review
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 2 institutions in 1 country.

Yiru ChenNational Clinical Research Center for Metabolic Diseases, Metabolic Syndrome Research Center, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
Xiuneng LiNational Clinical Research Center for Metabolic Diseases, Metabolic Syndrome Research Center, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
Yu DaiNational Clinical Research Center for Metabolic Diseases, Metabolic Syndrome Research Center, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
Jingjing ZhangNational Clinical Research Center for Metabolic Diseases, Metabolic Syndrome Research Center, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
Second Xiangya Hospital of Central South University · CNCentral South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Recently, a number of reports have described the potential relationship between COVID-19 and thyroid hormones, but the results were conflicting. We performed a meta-analysis to evaluate the effect of the severity of COVID-19 on thyroid-related hormones and the effect of thyroid-related hormones on the outcome of COVID-19 in order to try to confirm the association between the serum levels of free triiodothyronine (FT3), free thyroxine (FT4) and thyroid stimulating hormone (TSH) and the severity or mortality of coronavirus-19 patients. Methods: The methodology was already registered in the International Prospective Register of Systematic Reviews (PROSPERO) database, and the protocol number is CRD42021269246. Systematic searches were carried out on the Cochrane Library, Embase, PubMed and Web of Science databases on November 15, 2021. We set up the literature search strategy based on the following keywords: [(T3 OR FT3 OR triiodothyronine) or (T4 OR FT4 OR thyroxine) or (TSH or thyrotropin)] and (COVID-19 OR SARS-CoV-2), without time restrictions. Results: Twenty studies satisfied the inclusion/exclusion criteria and were included in the meta-analysis. A total of 3609 patients were enrolled in the study. From the analysis of the included studies, the incidence of thyroid-related hormone abnormalities was higher in patients with severe COVID-19, and the serum levels of FT3 and TSH were lower than those of patients with nonsevere COVID-19. However, the difference in the FT4 levels was not significant. Similar characteristics were shown between survivors and nonsurvivors. In addition, the outcomes of the meta-analysis showed that patients with abnormal thyroid-related hormones had greater mortality. Conclusions: Low FT3 serum levels, low FT4 serum levels and low TSH serum levels may increase the mortality of COVID-19 patients during admission. On the other hand, the higher the severity level of COVID-19, the higher the probability of decreases in the FT3, FT4, TSH levels.

Indexed as

AdolescentAdultAgedAged, 80 and overCOVID-19FemaleHumansMaleMiddle AgedOutcome Assessment, Health CareSARS-CoV-2Severity of Illness IndexThyroxineYoung AdultThyroxineCOVID-19FT3FT4mortalityTSH

Identifiers

PMID35058879
PMCPMC8763686
OpenAlexW4205598896

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.