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1.
Eye Contact Lens ; 2024 Apr 23.
Artigo em Inglês | MEDLINE | ID: mdl-38652487

RESUMO

OBJECTIVE: To evaluate the effects of rigid corneal lenses (RCL) in patients with keratoconus, based on eccentricity. METHODS: Eighty-four eyes from 84 patients were included in this retrospective comparative study. Based on the median value of eccentricity difference between the cornea and back surface of the RCL, the patients were divided into groups 1 (<0.08) and 2 (≥0.08). Visual acuity, refractive index, and corneal topography indices were compared before and three months after lens use. RESULTS: Visual acuity, astigmatism, refractive error, corneal curvature, and corneal thickness improved significantly in both groups. Apical power and anterior elevation improved significantly in group 1, with small differences in eccentricity, but not in group 2. Changes in apical power before and after lens use were significantly different between the two groups. CONCLUSION: The RCL was effective for the cornea of keratoconus, especially when the prescription was made with a small difference in eccentricity.

2.
BMC Ophthalmol ; 23(1): 426, 2023 Oct 23.
Artigo em Inglês | MEDLINE | ID: mdl-37867195

RESUMO

Mucoceles are cystic formations characterized by the presence of mucus-secreting epithelial cells, which enlarge when the excretory duct becomes obstructed. Posterior ethmoidal mucoceles are rare conditions that can lead to severe ocular complications requiring immediate intervention. The close anatomical proximity of posterior ethmoidal mucoceles to the optic nerve underscores their significance. In this case report, we present a case of rapidly progressing compressive optic neuropathy secondary to a posterior ethmoidal mucocele. A previously healthy forty-six-year-old woman presented with sudden visual loss in her left eye, preceded by left-sided headache and periorbital pain. Clinical examination and imaging studies revealed an oval-shaped mass within the posterior ethmoid cell compressing the left optic nerve. Emergency surgery was performed to alleviate optic nerve compression, which successfully relieved periocular pain. However, the patient's visual acuity and visual field defect remained unchanged postoperatively. Thinning of the ganglion cell layer in the macula region was observed during follow-up examinations. The role of corticosteroids and antibiotics in visual rehabilitation and the impact of delayed surgical decompression on visual outcome remain subjects of debate. Additional cases of mucocele-associated optic neuropathy should be published and analyzed to establish optimal treatment approaches.


Assuntos
Mucocele , Doenças do Nervo Óptico , Doenças dos Seios Paranasais , Humanos , Feminino , Pessoa de Meia-Idade , Mucocele/complicações , Mucocele/diagnóstico , Mucocele/cirurgia , Doenças do Nervo Óptico/diagnóstico , Doenças do Nervo Óptico/etiologia , Doenças do Nervo Óptico/cirurgia , Nervo Óptico , Transtornos da Visão/etiologia , Dor/complicações , Doenças dos Seios Paranasais/complicações , Doenças dos Seios Paranasais/diagnóstico , Doenças dos Seios Paranasais/cirurgia
4.
Diagnostics (Basel) ; 12(12)2022 Dec 14.
Artigo em Inglês | MEDLINE | ID: mdl-36553174

RESUMO

Dry eye disease (DED) is one of the most common diseases worldwide that can lead to a significant impairment of quality of life. The diagnosis and treatment of the disease are often challenging because of the lack of correlation between the signs and symptoms, limited reliability of diagnostic tests, and absence of established consensus on the diagnostic criteria. The advancement of machine learning, particularly deep learning technology, has enabled the application of artificial intelligence (AI) in various anterior segment disorders, including DED. Currently, many studies have reported promising results of AI-based algorithms for the accurate diagnosis of DED and precise and reliable assessment of data obtained by imaging devices for DED. Thus, the integration of AI into clinical approaches for DED can enhance diagnostic and therapeutic performance. In this review, in addition to a brief summary of the application of AI in anterior segment diseases, we will provide an overview of studies regarding the application of AI in DED and discuss the recent advances in the integration of AI into the clinical approach for DED.

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