Evidence map›Paper›PMID 40141005›Full record

ArticleBMC endocrine disorders2025

Predictive modeling of graves' orbitopathy activity based on meibomian glands analysis using in vivo confocal microscopy.

Zixuan Su, Yayan You, Shengnan Cheng, Jiahui Huang, Xueqing Liang, Xinghua Wang, Fagang Jiang

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Article in BMC endocrine disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zixuan Su *Department of Ophthalmology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Yayan You *Department of Ophthalmology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, 321000, Zhejiang, China.
Shengnan Cheng *Department of Ophthalmology, Tongji Medical College, Wuhan Hospital of Traditional Chinese and Western Medicine, Huazhong University of Science and Technology, Wuhan No.1 Hospital, Wuhan, China.
Jiahui HuangDepartment of Ophthalmology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Xueqing LiangDepartment of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, 510515, China.
Xinghua WangDepartment of Ophthalmology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China. xinghua_wang@hust.edu.cn.
Fagang JiangDepartment of Ophthalmology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China. fgjiang@hust.edu.cn.

Funding

Fundamental Research Funds for the Central Universities YCJJ20230109the Key Research and Development Program of Hubei Province 2023BCB147
6 · The paper itself

Abstract

objectivesThis study aims to identify indicators of disease activity in patients with graves' orbitopathy (GO) by examining the microstructural characteristics of meibomian glands (MGs) and developed a diagnostic model.

methodsWe employed in vivo confocal microscopy (IVCM) to examine MGs in GO patients. Patients classified in the active phase were determined based on the clinical activity score (CAS). The research employed the least absolute shrinkage and selection operator (LASSO) method to select key indicators. Subsequently, a logistic regression model was constructed to predict GO disease activity.

resultsA total of 45 GO patients, corresponding to 90 eyes, were included in this study. A Lasso regression algorithm was utilized to select the predictor variables. Five predictor variables were included in our diagnostic model ultimately. The area under the curve (AUC) for the training set model reached 0.959, and for the validation set was 0.969. The training set and validation set models both demonstrated high accuracy in calibration. Finally, a Nomogram chart was constructed to visualize the diagnostic model.

conclusionWe constructed a diagnostic model based on microstructural indicators of MGs obtained through IVCM and offered a clinical utility for assessing GO disease activity, aiding in the diagnosis and selection of treatment strategies for GO.

Indexed as

Graves OphthalmopathyMeibomian GlandsAdultAgedFemaleFollow-Up StudiesHumansMaleMicroscopy, ConfocalMiddle AgedNomogramsPrognosisClinical activity scoreDiagnostic model.Graves’ orbitopathyIn vivo confocal microscopyMeibomian glands

Identifiers

PMID40141005
PMCPMC11938666

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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.