1. High-Tech Parameters for the Evaluation of Signs and Symptoms of Dry Eye Disease: Identification of Clinical Cut-Offs and Agreement with Low-Tech Tests
- Author
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Paolo Fogagnolo, Pasquale Aragona, Alfonso Strianese, Edoardo Villani, Giuseppe Giannaccare, Vincenzo Orfeo, Valentina Mirisola, Rita Mencucci, and the Italian Dry Eye Study Group
- Subjects
Dry eye disease ,Tear film instability ,Break-up time ,High-tech imaging ,Ophthalmology ,RE1-994 - Abstract
Abstract Introduction High-tech devices for the assessment of dry eye disease (DED) are increasingly available. However, the agreement between high- and low-tech parameters has been poorly explored to date. Trying to fill these gaps, we conducted a post hoc analysis on a recently published retrospective study on patients with DED receiving both low- and high-tech (Keratograph®) assessments, and treatment with different lubricating eyedrops. Methods Six clinical questions were defined by the authors, considering literature gaps and their clinical experience, namely: (1) are NIKBUT-i and T-BUT interchangeable parameters? (2) What was the correlation between low- and high-tech parameters in untreated and treated patients with DED? (3) What was the correlation between signs and symptoms at baseline and during/after treatment? (4) Which parameters were better associated with symptoms? And with symptoms change over time? (5) What was the performance of NIKBUT-i and T-BUT in detecting clinically relevant changes? (6) What was the clinical advantage of adding other high- and low-tech parameters, respectively, to NIKBUT-i and T-BUT? Results Low-tech measures were the best descriptors of the Ocular Surface Disease Index (OSDI) at baseline. In contrast, high-tech assessments demonstrate better performance in detecting changes over time. The distribution of NIKBUT-i data was more dispersed than TBUT both at baseline and follow-up. At a fixed specificity of 80%, the sensitivity in detecting clinically relevant ameliorations of symptoms was 42% for NIKBUT-i and 25% for T-BUT. A battery of high-tech tests could detect 90% of clinical amelioration, compared with 45% with low-tech tests (p
- Published
- 2024
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