Literature DB >> 25330304

Evaluation of Meibomian Gland Dysfunction and Local Distribution of Meibomian Gland Atrophy by Non-contact Infrared Meibography.

David Finis1, Philipp Ackermann1, Nadja Pischel1, Claudia König1, Jasmin Hayajneh1, Maria Borrelli1, Stefan Schrader1, Gerd Geerling1.   

Abstract

AIMS: The main purpose of this study was to investigate the relationship between Meibomian gland atrophy (meiboscore) and Meibomian gland expressibility. In addition, the local distribution of Meibomian gland loss was analyzed.
METHODS: A retrospective analysis of 128 patients (92 women and 36 men, 57 ± 17 years) from our dry eye clinic was performed. Infrared meibography was performed using the Keratograph 5 M (Oculus, Wetzlar, Germany) and evaluated with a scoring system introduced by Arita et al.
RESULTS: A significant inverse correlation between Meibomian gland atrophy measured by meibography and expressible Meibomian glands (r = -0.197, p = 0.003) as well as between meiboscore and TBUT (r = -0.1615, p = 0.012) was found. There also was a significant correlation between the total meiboscore and the age (r = 0.33, p < 0.0001). We could find a strong and highly significant correlation between the total meiboscore and the individual meiboscore of the upper eyelid (r = 0.905, p < 0.0001) and the lower eyelid (r = 0.892, p < 0.0001). There was no significant difference of Meibomian gland atrophy between the individual thirds of the upper eyelid, but for the lower eyelid, we could find a higher degree of Meibomian gland atrophy in the nasal third compared with the middle and the temporal third (Dunn's post hoc test, p < 0.0001).
CONCLUSIONS: Meibomian gland atrophy seems to be not constant over the tarsal plate but the examination of the lower tarsus might be sufficient in most of the cases. The correlation of the meiboscore with functional dry eye parameters suggest that in patients with detectable Meibomian gland atrophy there is also an impaired Meibomian gland function. However, meibography seems not to be sufficient as a single test for the diagnosis of MGD. For the future larger, prospective studies are needed to confirm these results and further evaluate the potential of meibography in the diagnosis of MGD.

Entities:  

Keywords:  Dry eye; MGD; Meibomian gland dysfunction; meibography; tear film

Mesh:

Year:  2014        PMID: 25330304     DOI: 10.3109/02713683.2014.971929

Source DB:  PubMed          Journal:  Curr Eye Res        ISSN: 0271-3683            Impact factor:   2.424


  23 in total

1.  Repeatability of Non-invasive Keratograph Break-Up Time measurements obtained using Oculus Keratograph 5M.

Authors:  José Vicente García-Marqués; Noelia Martínez-Albert; Cristian Talens-Estarelles; Santiago García-Lázaro; Alejandro Cerviño
Journal:  Int Ophthalmol       Date:  2021-03-16       Impact factor: 2.031

2.  Changes of meibomian glands in patients with type 2 diabetes mellitus.

Authors:  Tao Yu; Wei-Yun Shi; Ai-Ping Song; Yang Gao; Guang-Fu Dang; Gang Ding
Journal:  Int J Ophthalmol       Date:  2016-12-18       Impact factor: 1.779

3.  Grading and baseline characteristics of meibomian glands in meibography images and their clinical associations in the Dry Eye Assessment and Management (DREAM) study.

Authors:  Ebenezer Daniel; Maureen G Maguire; Maxwell Pistilli; Vatinee Y Bunya; Giacomina M Massaro-Giordano; Eli Smith; Pooja A Kadakia; Penny A Asbell
Journal:  Ocul Surf       Date:  2019-04-22       Impact factor: 5.033

4.  In vivo confocal microscopy classification in the diagnosis of meibomian gland dysfunction.

Authors:  Matthieu Randon; Vittoria Aragno; Rachid Abbas; Hong Liang; Antoine Labbé; Christophe Baudouin
Journal:  Eye (Lond)       Date:  2018-12-12       Impact factor: 3.775

5.  Quantifying Meibomian Gland Morphology Using Artificial Intelligence.

Authors:  Jiayun Wang; Shixuan Li; Thao N Yeh; Rudrasis Chakraborty; Andrew D Graham; Stella X Yu; Meng C Lin
Journal:  Optom Vis Sci       Date:  2021-09-01       Impact factor: 2.106

6.  Automatic identification of meibomian gland dysfunction with meibography images using deep learning.

Authors:  Yi Yu; Yiwen Zhou; Hongmei Zheng; Yanning Yang; Miao Tian; Yabiao Zhou; Yuejiao Tan; Lianlian Wu
Journal:  Int Ophthalmol       Date:  2022-09-19       Impact factor: 2.029

Review 7.  The Growing Need for Validated Biomarkers and Endpoints for Dry Eye Clinical Research.

Authors:  Neeta S Roy; Yi Wei; Eric Kuklinski; Penny A Asbell
Journal:  Invest Ophthalmol Vis Sci       Date:  2017-05-01       Impact factor: 4.799

8.  Prevalence of Meibomian Gland Atrophy in a Pediatric Population.

Authors:  Preeya K Gupta; Madelyn N Stevens; Namita Kashyap; Yos Priestley
Journal:  Cornea       Date:  2018-04       Impact factor: 2.651

9.  Evaluation of Dry Eye and Meibomian Gland Dysfunction in Teenagers with Myopia through Noninvasive Keratograph.

Authors:  Xiu Wang; Xiaoxiao Lu; Jun Yang; Ruihua Wei; Liyuan Yang; Shaozhen Zhao; Xilian Wang
Journal:  J Ophthalmol       Date:  2016-01-06       Impact factor: 1.909

10.  Meibomian gland features in a Norwegian cohort of patients with primary Sjögren´s syndrome.

Authors:  Xiangjun Chen; Øygunn Aass Utheim; Jiaxin Xiao; Muhammed Yasin Adil; Aleksandar Stojanovic; Behzod Tashbayev; Janicke Liaaen Jensen; Tor Paaske Utheim
Journal:  PLoS One       Date:  2017-09-08       Impact factor: 3.240

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