Akhilesh S Pathipati1, Edward H Wood2, Carson K Lam2, Christopher S Sáles2,3, Darius M Moshfeghi4. 1. Stanford University School of Medicine, Stanford, CA, USA. 2. Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, 2452 Watson Ct, Palo Alto, CA, USA. 3. Ophthalmic Consultants of Boston, Boston, MA, USA. 4. Department of Ophthalmology, Byers Eye Institute, Stanford University School of Medicine, 2452 Watson Ct, Palo Alto, CA, USA. dariusm@stanford.edu.
Abstract
PURPOSE: To assess the accuracy of best-corrected visual acuity (BCVA) measured by non-ophthalmic emergency department (ED) staff with a standard Snellen chart versus an automated application (app) on a handheld smartphone (Paxos Checkup, San Francisco, CA, USA). METHODS: The study included 128 subjects who presented to the Stanford Hospital ED for whom the ED requested an ophthalmology consultation. We conducted the study in two phases. During phase 1 of the study, ED staff tested patient BCVA using a standard Snellen test at 20 feet. During phase 2 of the study, ED staff tested patient near BCVA using the app. During both phases, ophthalmologists measured BCVA with a Rosenbaum near chart, which was treated as the gold standard. ED BCVA measurements were benchmarked prospectively against ophthalmologists' measurements and converted to logMAR. RESULTS: ED logMAR BCVA was 0.21 ± 0.35 (approximately 2 Snellen lines difference ± 3 Snellen lines) higher than that of ophthalmologists when ED staff used a Snellen chart (p = .0.00003). ED BCVA was 0.06 ± 0.40 (less than 1 Snellen line ± 4 Snellen lines) higher when ED staff used the app (p = 0.246). Inter-observer difference was therefore smaller by more than 1 line (0.15 logMAR) with the app (p = 0.046). CONCLUSIONS: BCVA measured by non-ophthalmic ED staff with an app was more accurate than with a Snellen chart. Automated apps may provide a means to standardize and improve the efficiency of ED ophthalmologic care.
PURPOSE: To assess the accuracy of best-corrected visual acuity (BCVA) measured by non-ophthalmic emergency department (ED) staff with a standard Snellen chart versus an automated application (app) on a handheld smartphone (Paxos Checkup, San Francisco, CA, USA). METHODS: The study included 128 subjects who presented to the Stanford Hospital ED for whom the ED requested an ophthalmology consultation. We conducted the study in two phases. During phase 1 of the study, ED staff tested patient BCVA using a standard Snellen test at 20 feet. During phase 2 of the study, ED staff tested patient near BCVA using the app. During both phases, ophthalmologists measured BCVA with a Rosenbaum near chart, which was treated as the gold standard. ED BCVA measurements were benchmarked prospectively against ophthalmologists' measurements and converted to logMAR. RESULTS: ED logMAR BCVA was 0.21 ± 0.35 (approximately 2 Snellen lines difference ± 3 Snellen lines) higher than that of ophthalmologists when ED staff used a Snellen chart (p = .0.00003). ED BCVA was 0.06 ± 0.40 (less than 1 Snellen line ± 4 Snellen lines) higher when ED staff used the app (p = 0.246). Inter-observer difference was therefore smaller by more than 1 line (0.15 logMAR) with the app (p = 0.046). CONCLUSIONS: BCVA measured by non-ophthalmic ED staff with an app was more accurate than with a Snellen chart. Automated apps may provide a means to standardize and improve the efficiency of ED ophthalmologic care.
Authors: Karun S Arora; Dolly S Chang; Wasu Supakontanasan; Manu Lakkur; David S Friedman Journal: Am J Ophthalmol Date: 2014-02-15 Impact factor: 5.258
Authors: Andrew Bastawrous; Hillary K Rono; Iain A T Livingstone; Helen A Weiss; Stewart Jordan; Hannah Kuper; Matthew J Burton Journal: JAMA Ophthalmol Date: 2015-08 Impact factor: 7.389
Authors: Aaron Y Lee; Joanne C Wen; Yue Wu; Ian Luttrell; Shu Feng; Philip P Chen; Ted Spaide Journal: Br J Ophthalmol Date: 2019-12-23 Impact factor: 4.638
Authors: Omer Trivizki; Michael R Karp; Anuj Chawla; Justin Yamanuha; Giovanni Gregori; Philip J Rosenfeld Journal: Am J Ophthalmol Date: 2020-07-02 Impact factor: 5.258
Authors: Xiaotong Han; Jane Scheetz; Stuart Keel; Chimei Liao; Chi Liu; Yu Jiang; Andreas Müller; Wei Meng; Mingguang He Journal: Transl Vis Sci Technol Date: 2019-08-19 Impact factor: 3.283
Authors: David A Leske; Sarah R Hatt; Yolanda S Castañeda; Suzanne M Wernimont; Christina S Cheng-Patel; Erick D Bothun; Eileen E Birch; Jonathan M Holmes Journal: J AAPOS Date: 2021-06-26 Impact factor: 1.325