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Diagnostic Algorithm for Surgical Management of Limbal Stem Cell Deficiency

Authors :
Boris Malyugin
Svetlana Kalinnikova
Ruslan Isabekov
Dmitriy Ostrovskiy
Boris Knyazer
Maxim Gerasimov
Source :
Diagnostics, Vol 13, Iss 2, p 199 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Background: Limbal stem cell deficiency (LCSD) presents several challenges. Currently, there is no clearly defined systematic approach to LSCD diagnosis that may guide surgical tactics. Methods: The medical records of 34 patients with LSCD were analyzed. Diagnostic modalities included standard (visometry, tonometry, visual field testing, slit-lamp biomicroscopy with corneal fluorescein staining, Schirmer test 1, ultrasonography) and advanced ophthalmic examination methods such as anterior segment optical coherence tomography, in vivo confocal microscopy, impression cytology, and enzyme-linked immunoassay. Results: Standard ophthalmological examination was sufficient to establish the diagnosis of LSCD in 20 (58.8%) cases, whereas advanced evaluation was needed in 14 (41.2%) cases. Depending on the results, patients with unilateral LSCD were scheduled to undergo glueless simple limbal epithelial transplantation (G-SLET) or simultaneous G-SLET and lamellar keratoplasty. Patients with bilateral LSCD with normal or increased corneal thickness were enrolled in the paralimbal oral mucosa epithelium transplantation (pLOMET) clinical trial. Conclusions: Based on the diagnostic and surgical data analyzed, the key points in LSCD diagnosis were identified, helping to guide the surgeon in selecting the appropriate surgical procedure. Finally, we proposed a novel step-by-step diagnostic algorithm and original surgical guidelines for the treatment of patients with LSCD.

Details

Language :
English
ISSN :
20754418
Volume :
13
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Diagnostics
Publication Type :
Academic Journal
Accession number :
edsdoj.335fa4919ff4dce8906a20fd0c787e3
Document Type :
article
Full Text :
https://doi.org/10.3390/diagnostics13020199