ArticleEye (London, England)2019
In vivo confocal microscopy classification in the diagnosis of meibomian gland dysfunction.
Article in Eye (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 30 citations in OpenAlex.
- In Vivo Confocal Microscopy for Automated Detection of Meibomian Gland Dysfunction: A Study Based on Deep Convolutional Neural Networks.Journal of imaging informatics in medicine · 2025Article
- Multimodal Approach in Dry Eye Disease Combining In Vivo Confocal Microscopy and HLA-DR Expression.Translational vision science & technology · 2024Article
- Loose suture-related ocular surface inflammation and activation of conjunctiva-associated lymphoid tissue in patients after keratoplasty.Scientific reports · 2024Article
- Efficacy of indirect intense pulsed light irradiation on meibomian gland dysfunction: a randomized controlled study.International journal of ophthalmology · 2024Article
- Meibomian Gland Dysfunction Clinical Practice Guidelines.Japanese journal of ophthalmology · 2023Article
- Dry Eye Disease Associated with Meibomian Gland Dysfunction: Focus on Tear Film Characteristics and the Therapeutic Landscape.Ophthalmology and therapy · 2023Review
- Ductal Hyperkeratinization and Acinar Renewal Abnormality: New Concepts on Pathogenesis of Meibomian Gland Dysfunction.Current issues in molecular biology · 2023Article
- Automation of dry eye disease quantitative assessment: A review.Clinical & experimental ophthalmology · 2022Review
- Interobserver and Intraobserver Agreements of the Detection ofBeyoglu eye journal · 2022Article
- Artificial Intelligence to Detect Meibomian Gland Dysfunction FromFrontiers in medicine · 2021Article
- A review of meibography for a refractive surgeon.Indian journal of ophthalmology · 2020Review
- Novel Approaches for Imaging-Based Diagnosis of Ocular Surface Disease.Diagnostics (Basel, Switzerland) · 2020Review
- Grading and baseline characteristics of meibomian glands in meibography images and their clinical associations in the Dry Eye Assessment and Management (DREAM) study.The ocular surface · 2019Article
- Imaging of meibomian glands: from bench to bedside and back.Eye (London, England) · 2019Article
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimMeibomian gland dysfunction (MGD) is one of the most common disorders in ophthalmology. The aim of this study was to evaluate the use of this in vivo confocal microscopy (IVCM)-MGD description to classify patients affected by clinical MGD and measure the correlation with standard clinical criteria and subjective symptoms.
methodsOne hundred eyes of 100 patients suffering from MGD and 15 eyes of normal subjects were included. A comprehensive evaluation with the ocular surface disease index (OSDI), Schirmer test, tear break-up time (TBUT), tear osmolarity, Oxford score, Meibomian gland expression, palpebral IVCM, and meibography was performed. Then each patient was classified using a new IVCM classification: type 0 for normality, type 1 for meibum obstruction, type 2 for inflammation, and type 3 for fibrosis.
resultsThe mean age of patients was 52 ± 20 years old, the OSDI was 38 ± 23, the BUT 5 ± 2.6 s, the Schirmer test 13 ± 7 mm, tear osmolarity 300 ± 11 osmol/L, the Oxford score 0.5 ± 0.6, the meibum expression score 1.7 ± 1.02, and the meibography score 1.3 ± 0.9. The IVCM MG classification of the 15 normal subjects was 0. For MGD patients, 29% were in type 1, 40% were type 2, and 31% were type 3. The patients in IVCM MG type 2 had a higher OSDI (p = 0.001) compared with the other types. There was a strong correlation between the IVCM score and the meibography score (r = 0.71 p < 0.0001).
conclusionThis new IVCM classification provided a practical pathophysiological system for MGD. By giving objective criteria, this IVCM classification may help advance the understanding of patients' symptoms and enhance treatment effectiveness in MGD.
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