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Published on: May 25, 2020
Standardization of distance visual acuity measurement using optonet computerized vision charts: A multicentric study
Caridad Galindo-Romero1, Jose A López-López2, Diego García-Ayuso1
1Grupo de Investigación Optometría Clínica y Experimental, Facultad de Óptica y Optometría, Universidad de Murcia, Murcia, Spain; Grupo de Investigación Oftalmología Experimental, Departamento de Oftalmología, Optometría, Otorrinolaringología y Anatomía Patológica, Facultad de Medicina, Universidad de Murcia, Instituto Murciano de Investigación Biosanitaria Pascual Parrilla-IMIB, Murcia, Spain.
Purpose:
To assess the repeatability and validity of computerized distance visual acuity (VA) charts from Optonet Vision Unit (OVU) using a Continuing Professional Development (CPD) programme which recreates real-life scenario conditions.
Methods:
This is a multicentric study with 481 participants aged from 7 to 88 years. Distance VA was assessed by OVU with five different computerized VA charts, according to Bailey and Lovie's principles (Sloan, British, Numbers, Landolt C and Broken Rings). Two consecutive measurements (TCM) and two measurements (Test re-test (TRT)) were evaluated (95% limits of agreement (LOA), ICC 95%).
Results:
In all VA charts, the mean difference between measurements was near 0.00 logMAR and there was an excellent correlation between TCM (ICC ≥0.968, 95% LOA of ±0.071 logMAR) and TRT (ICC ≥0.957, 95% LOA of ±0.09 logMAR). Pairwise comparison between VA charts showed a statistical difference between tests, with a minimum mean difference of 0.003 logMAR (95% CI, -0.010 to 0.004) between Landolt C and Broken rings; and a maximum mean difference of 0.071 logMAR between Sloan letters and Numbers (95% CI, -0.075 to -0.067).
Conclusions:
The reliability and reproducibility of OVU software for distance VA measurement is promising for eye care practitioner consultation highlighting the possibility of expanding the use of OVU for both clinic and research. The use of online CPD programs is useful to improve statistical and research understanding is an innovative, hands-on approach that helps in bridging the gap between clinical practice and research.
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