Algorithm for dry eye disease diagnosis in individuals infected with human T-cell lymphotropic virus type 1

• Autor(a) principal: Castro-Lima-Vargens,Cristina
• Data de Publicação: 2017
• Outros Autores: Grassi,Maria Fernanda Rios, Boa-Sorte,Ney, Rathsam-Pinheiro,Regina Helena, Almeida,Paula Caroline Matos, Galvão-Castro,Bernardo
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Arquivos brasileiros de oftalmologia (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0004-27492017000600369
• topic: Keratoconjunctivitis sicca; Human T-cell lymphotropic virus 1; Dry eye syndromes/diagnosis

ABSTRACT Purpose: To evaluate the accuracy of lacrimal film tests and propose an algorithm for the diagnosis of dry eye disease in individuals infected with human T-cell lymphotropic virus type 1. Methods: Ninety-six patients infected with human T-cell lymphotropic virus type 1 were enrolled in the study. To assess clinical complaints, patients completed the Ocular Surface Disease Index questionnaire. To evaluate lacrimal film quality, patients underwent the tear breakup time test, Schirmer I test, and Rose Bengal staining. Dry eye disease was diagnosed when at least two of the three test results were abnormal. The sensitivity, specificity, positive and negative predictive values, and overall accuracy of the questionnaire as well as of each test alone and combined in parallel and in series were determined. Results: The most sensitive test was the tear breakup time test (98%), whereas the most specific was the Schirmer I test (100%). Rose Bengal staining had the highest overall accuracy (88.64%), whereas the Ocular Surface Disease Index had the lowest overall accuracy (62.65%). The tear breakup time test, Schirmer I test, and Ocular Surface Disease Index combined in parallel showed increased sensitivity and decreased specificity for all tests. In contrast, when combined in series, these tests demonstrated increased specificity and decreased sensitivity. Conclusion: This study shows the need to use multiple tests to evaluate tear film quality and include a symptom questionnaire as part of the diagnostic algorithm for dry eye disease.