Evidence map›Paper›PMID 36045442›Full record

ArticleBMC endocrine disorders2022

Clinical evaluation of an automated TSI bridge immunoassay in the diagnosis of Graves' disease and its relationship to the degree of hyperthyroidism.

Tianqi Liu, Xiuying Zhang, Li Long, Lingli Zhou, Jing Chen, Meng Li, Ying Gao, Xianghai Zhou, Xueyao Han, Linong Ji

Open access · goldAbstract read
In one paragraph

Article in BMC endocrine disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.7field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

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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

10 authors at 3 institutions in 1 country.

Tianqi Liu *Department of Endocrinology and Metabolism, Peking University People's Hospital, N0.11, Xi Zhi Men Nan Da Jie, Xicheng District, Beijing, 100044, China.
Xiuying Zhang *Department of Endocrinology and Metabolism, Peking University People's Hospital, N0.11, Xi Zhi Men Nan Da Jie, Xicheng District, Beijing, 100044, China. zhangxiuying717@163.com.
Li LongDepartment of Endocrinology and Metabolism, the Second People's Hospital, Guiyang, 550000, China.
Lingli ZhouDepartment of Endocrinology and Metabolism, Peking University People's Hospital, N0.11, Xi Zhi Men Nan Da Jie, Xicheng District, Beijing, 100044, China.
Jing ChenDepartment of Endocrinology and Metabolism, Peking University People's Hospital, N0.11, Xi Zhi Men Nan Da Jie, Xicheng District, Beijing, 100044, China.
Meng LiDepartment of Endocrinology and Metabolism, Peking University People's Hospital, N0.11, Xi Zhi Men Nan Da Jie, Xicheng District, Beijing, 100044, China.
Ying GaoDepartment of Endocrinology and Metabolism, Peking University People's Hospital, N0.11, Xi Zhi Men Nan Da Jie, Xicheng District, Beijing, 100044, China.
Xianghai ZhouDepartment of Endocrinology and Metabolism, Peking University People's Hospital, N0.11, Xi Zhi Men Nan Da Jie, Xicheng District, Beijing, 100044, China.
Xueyao HanDepartment of Endocrinology and Metabolism, Peking University People's Hospital, N0.11, Xi Zhi Men Nan Da Jie, Xicheng District, Beijing, 100044, China.
Linong JiDepartment of Endocrinology and Metabolism, Peking University People's Hospital, N0.11, Xi Zhi Men Nan Da Jie, Xicheng District, Beijing, 100044, China. jiln@bjmu.edu.cn.
Peking University People's Hospital · CNPeking University · CNXian Yang Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rapid and accurate detection of thyroid-stimulating hormone (TSH) receptor antibodies has always been an urgent need for the clinical diagnosis and management of Graves' disease (GD). We aimed to evaluate the use of an automated thyroid-stimulating immunoglobulin (TSI) bridge immunoassay in the diagnosis of GD and to analyze the relationship between TSI and the degree of hyperthyroidism.

methodsA total of 227 new-onset GD patients, 29 Hashimoto thyroiditis, 43 non-autoimmune thyroid diseases and 37 euthyroid controls were consecutively recruited. All participants accepted the measurement of their serum thyroid function and thyroid-associated antibodies, including TSI being measured by an Immulite 2000 bridge immunoassay and TSH receptor autoantibodies (TRAb) being measured by a third-generation Roche electrochemiluminescence immunoassay. The quantitative consistency between the TSI and TRAb detection methods was analyzed by using Passing-Bablok regression and Bland-Altman plots. The diagnostic performance for GD was assessed by receiver operating characteristic (ROC) curve analysis.

resultsAmong 227 GD patients (174 females and 53 males, with a mean age of 39 years), the quantitative TSI was positively correlated with TRAb (r = 0.8099). According to the cut-off values proposed by the manufacturers (TSI: 0.55 IU/L, TRAb: 1.75 IU/L), the positive rates of TSI and TRAb in new-onset GD patients were 96.92% and 95.15%, respectively. Both TSI and TRAb levels positively correlated with FT

conclusionThe automated TSI bridge immunoassay was positively correlated with thyroxine levels in new-onset GD patients and was more likely to be consistent with the clinical diagnosis of GD than with that of TRAb. The positive Immulite 2000 TSI cut-off value of 0.577 IU/L for GD diagnosis in the Chinese population were close to the value recommended by the manufacturer.

Indexed as

Graves DiseaseHyperthyroidismAdultAutoantibodiesFemaleHumansImmunoassayImmunoglobulins, Thyroid-StimulatingMaleReceptors, ThyrotropinAutoantibodiesImmunoglobulins, Thyroid-StimulatingReceptors, ThyrotropinGraves’ diseaseHyperthyroidismTSH receptor antibody

Identifiers

PMID36045442
PMCPMC9429690
OpenAlexW4293765080

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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.