Agreement analysis comparing iPad LCVA and Sloan testing in multiple sclerosis patients
Visual symptoms are common in multiple sclerosis (MS). Low-contrast visual acuity (LCVA) testing using Sloan charts has demonstrated increased sensitivity for visual deficits compared to high-contrast acuity testing. Computerized testing of visual acuity may facilitate use in the clinic setting. To...
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| Vydáno v: | Multiple sclerosis Ročník 24; číslo 8; s. 1126 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
England
01.07.2018
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| Témata: | |
| ISSN: | 1477-0970, 1477-0970 |
| On-line přístup: | Zjistit podrobnosti o přístupu |
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| Shrnutí: | Visual symptoms are common in multiple sclerosis (MS). Low-contrast visual acuity (LCVA) testing using Sloan charts has demonstrated increased sensitivity for visual deficits compared to high-contrast acuity testing. Computerized testing of visual acuity may facilitate use in the clinic setting.
To evaluate the agreement between an iPad-based and Sloan testing of LCVA in a cohort of MS patients.
A total of 38 patients with relapsing-remitting MS were enrolled after providing informed written consent at Partners MS Center, Brigham and Women's hospital. Monocular LCVA was measured using retroilluminated Sloan chart and iPad-based LogMAR chart. Number of correct letters and agreement between two measurements were assessed for each eye using Bland-Altman analysis and paired t-test.
For both eyes, there was no significant difference in number correct between the two measurements using a paired t-test, and there was high correlation between two measurements (oculus dextrus (OD) r = 0.89, p < 0.001; oculus sinister (OS) r = 0.78, p < 0.001). The limits of agreement were -7.9 to +8.5 letters for the right eye and -10.9 to +11.2 letters for the left eye.
An iPad-based LCVA test shows good agreement with Sloan testing in MS patients. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1477-0970 1477-0970 |
| DOI: | 10.1177/1352458517713667 |