Evidence map›Paper›PMID 34113406›Full record

ArticleDisease markers2021

Combination Model of Thyrotrophin Receptor Antibody and Volumetric Orbital Apex Crowding Index as an Indicator of Dysthyroid Optic Neuropathy.

Zhihong Deng, Lu Chen, Jia Tan, Sha Wang, Dan Liu, Jinwei Wang, Chengzhi Jiang, Jie Yang, Bei Xu

Open access · hybridAbstract read
In one paragraph

Article in Disease markers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Three-dimensional soft tissue reconstruction and volume measurement used for the diagnosis of dysthyroid optic neuropathy.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024
    Article
  5. Article
  6. 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

9 authors at 2 institutions in 1 country.

Zhihong DengDepartment of Ophthalmology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China.
Lu ChenEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.ORCID https://orcid.org/0000-0001-8380-014X
Jia TanEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.ORCID https://orcid.org/0000-0001-6482-818X
Sha WangEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Dan LiuEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Jinwei WangEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Chengzhi JiangPET-CT Center, Hunan Cancer Hospital, Changsha, Hunan, China.
Jie YangEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Bei XuEye Center of Xiangya Hospital, Central South University, Changsha, Hunan, China.
Central South University · CNHunan Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDysthyroid optic neuropathy (DON) is one of the most serious vision-threatening complications of thyroid eye disease (TED); however, accurate and established diagnostic tools for DON are yet lacking. The present study was aimed at identifying new diagnostic factors for the accurate diagnosis of DON.

methodsThis retrospective cross-sectional study included 25 TED patients (50 eyes) with enlarged extraocular muscles, no previous anti-inflammatory therapy, and the absence of other vision-affecting diseases between May 2017 and August 2019. Baseline data, such as gender, age, ophthalmological history, thyroid disease and management, TED history including clinical features, management, and long-term results, ophthalmological examinations, serology examinations, and single-photon emission computed tomography/computed tomography (SPECT/CT) results, were extracted. The diagnostic criteria were as follows: (1) best-corrected visual acuity (BCVA) loss coexisting with either of the following-increased latency or reduction of amplitude on visual evoked potential (VEP), impaired color vision, visual field defects, contrast sensitivity impairment, and optic disk swelling-and (2) Barrett's index ≥ 60% in CT. Univariate and multivariate logistic regression analyses assessed the differences in age, gender, eyes, medical history, clinical activity, thyroid hormone and antibodies, uptake ratio (UR) of extraocular muscles in SPECT/CT, and volumetric orbital apex crowding index (VACI) using the generalized estimation equation. Consequently, the receiver operating characteristic curve (ROC) of the significant factors was constructed.

resultsUnivariate analysis revealed significant differences in the clinical activity, free triiodothyronine (FT3), free thyroxine (FT4), thyrotrophin receptor antibody (TRAb) levels, the UR of superior and medial rectus, and VACI between DON and TED (without DON) groups. Multivariate regression analysis revealed that TRAb and VACI were significantly different. ROC analysis showed that the univariate models of TRAb or VACI and the multivariate model were effective indicators of DON, while the multivariate model had the highest area under the ROC curve.

conclusionA combination of TRAb and VACI is an effective indicator for DON.

Indexed as

Diagnostic Techniques, OphthalmologicalAdultAgedAutoantibodiesBiomarkersCross-Sectional StudiesFemaleGraves OphthalmopathyHumansLogistic ModelsMaleMiddle AgedModels, BiologicalMultivariate AnalysisOptic Nerve DiseasesReceptors, ThyrotropinAutoantibodiesBiomarkersReceptors, Thyrotropin

Identifiers

PMID34113406
PMCPMC8154283
OpenAlexW3163325276

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Registered trials

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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.