Literature DB >> 27466721

Interexaminer Reliability of Meibography: Upper or Lower Eyelid?

Aysun Sanal Dogan1, Mustafa Kosker, Nese Arslan, Canan Gurdal.   

Abstract

OBJECTIVES: To investigate the interexaminer reliability of meibography evaluation and the impact of eyelid selection for the procedure.
METHODS: Meibography images of 30 subjects' right eye, including both lids, were evaluated by three clinicians. Meibomian gland (MG) dropout was noted with respect to both percentage and grading (0-4). The examiners' (E1, E2, and E3) consistency was assessed by the intraclass correlation coefficient for MG loss percent and weighted kappa for grading. Correlations between the meibography findings and the fluorescein tear break-up time (FBUT), ocular surface disease index (OSDI) questionnaire, and noninvasive tear break-up time (NIBUT) data were also analyzed.
RESULTS: The patients' mean age was 49.2±13.4 years, and the male/female ratio distribution was 15/15. Mean FBUT was 9.6±3.1 sec. OSDI and NIBUT were not correlated with meibography findings. FBUT measurements were correlated with the MG loss assessments of all examiners for the upper lid (Spearman correlation test, E1: r=-0.617, P<0.001; E2: r=-0.428, P<0.018; E3: r=-0.429, P=0.018) but not for the lower lid. Weighted kappa statistics based on MG dropout grading revealed moderate-to-good agreement for the upper lid (E1-E2: κ=0.516, P<0.001; E1-E3: κ=0.621, P<0.001; E2-E3: κ=0.650, P<0.001) and fair-to-moderate agreement for the lower lid (E1-E2: κ=0.212; E1-E3: κ=0.272; E2-E3: κ=0.530).
CONCLUSIONS: Meibography is an objective tool for the detection of MG loss. Because of the correlation with FBUT and better interexaminer agreement on dropout by grading, the upper lid might be the preferred lid to make an evaluation.

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Mesh:

Year:  2018        PMID: 27466721     DOI: 10.1097/ICL.0000000000000307

Source DB:  PubMed          Journal:  Eye Contact Lens        ISSN: 1542-2321            Impact factor:   2.018


  7 in total

1.  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

2.  Assessment of dry eye disease in N95 versus surgical face mask wearers during COVID-19.

Authors:  Shirin Hamed Azzam; Amir Nama; Hanan Badarni; Helena Asael; Wadie Abu Dahoud; Michael Mimouni; Hiba Zayyad
Journal:  Indian J Ophthalmol       Date:  2022-03       Impact factor: 2.969

3.  Noncontact Meibography in Patients with Keratoconus.

Authors:  Engy Mohamed Mostafa; Marwa Mahmoud Abdellah; Ashraf Mostafa Elhawary; Amr Mounir
Journal:  J Ophthalmol       Date:  2019-06-02       Impact factor: 1.909

4.  Image based analysis of meibomian gland dysfunction using conditional generative adversarial neural network.

Authors:  Zakir Khan Khan; Arif Iqbal Umar; Syed Hamad Shirazi; Asad Rasheed; Abdul Qadir; Sarah Gul
Journal:  BMJ Open Ophthalmol       Date:  2021-02-12

5.  Noninvasive ocular surface analyzer as an adjunct in diagnosis and estimating prevalence of meibomian gland dysfunction: Hospital-based comparative study.

Authors:  Saumya Yadav; Noopur Gupta; Tarjani Makwana; Murugesan Vanathi; Radhika Tandon
Journal:  Indian J Ophthalmol       Date:  2022-05       Impact factor: 2.969

Review 6.  A Review of Imaging Biomarkers of the Ocular Surface.

Authors:  William W Binotti; Betul Bayraktutar; M Cuneyt Ozmen; Stephanie M Cox; Pedram Hamrah
Journal:  Eye Contact Lens       Date:  2020-03       Impact factor: 3.152

7.  The protective effect of 3% diquafosol on meibomian gland morphology in glaucoma patients treated with prostaglandin analogs: a 12-month follow-up study.

Authors:  Yue Guo; Jun Young Ha; He Long Piao; Mi Sun Sung; Sang Woo Park
Journal:  BMC Ophthalmol       Date:  2020-07-10       Impact factor: 2.209

  7 in total

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