Evaluating Visual Acuity in the American Academy of Ophthalmology IRIS® Registry
Objective: To describe visual acuity data representation in the American Academy of Ophthalmology Intelligent Research in Sight (IRIS) Registry and present a data-cleaning strategy.
Design: Reliability and validity study.
Participants: Patients with visual acuity records from 2018 in the IRIS Registry.
Methods: Visual acuity measurements and metadata were identified and characterized from 2018 IRIS Registry records. Metadata, including laterality, assessment method (distance, near, and unspecified), correction (corrected, uncorrected, and unspecified), and flags for refraction or pinhole assessment were compared between Rome (frozen April 20, 2020) and Chicago (frozen December 24, 2021) versions. We developed a data-cleaning strategy to infer patients' corrected distance visual acuity in their better-seeing eye.
Main Outcome Measures: Visual acuity data characteristics in the IRIS Registry.
Results: The IRIS Registry Chicago data set contains 168 920 049 visual acuity records among 23 001 531 unique patients and 49 968 974 unique patient visit dates in 2018. Visual acuity records were associated with refraction in 5.3% of cases, and with pinhole in 11.0%. Mean (standard deviation) of all measurements was 0.26 (0.41) logarithm of the minimum angle of resolution (logMAR), with a range of - 0.3 to 4.0 A plurality of visual acuity records were labeled corrected (corrected visual acuity [CVA], 39.1%), followed by unspecified (37.6%) and uncorrected (uncorrected visual acuity [UCVA], 23.4%). Corrected visual acuity measurements were paradoxically worse than same day UCVA 15% of the time. In aggregate, mean and median values were similar for CVA and unspecified visual acuity. Most visual acuity measurements were at distance (59.8%, vs. 32.1% unspecified and 8.2% near). Rome contained more duplicate visual acuity records than Chicago (10.8% vs. 1.4%). Near visual acuity was classified with Jaeger notation and (in Chicago only) also assigned logMAR values by Verana Health. LogMAR values for hand motion and light perception visual acuity were lower in Chicago than in Rome. The impact of data entry errors or outliers on analyses may be reduced by filtering and averaging visual acuity per eye over time.
Conclusions: The IRIS Registry includes similar visual acuity metadata in Rome and Chicago. Although fewer duplicate records were found in Chicago, both versions include duplicate and atypical measurements (i.e., CVA worse than UCVA on the same day). Analyses may benefit from using algorithms to filter outliers and average visual acuity measurements over time.
Financial Disclosures: Proprietary or commercial disclosure may be found found in the Footnotes and Disclosures at the end of this article.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:4 |
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| Enthalten in: |
Ophthalmology science - 4(2024), 1 vom: 28. Jan., Seite 100352 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Brant, Arthur [VerfasserIn] |
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| Links: |
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| Themen: |
Epidemiology |
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| Anmerkungen: |
Date Revised 10.02.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1016/j.xops.2023.100352 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM363613358 |
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| 500 | |a Date Revised 10.02.2024 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Objective: To describe visual acuity data representation in the American Academy of Ophthalmology Intelligent Research in Sight (IRIS) Registry and present a data-cleaning strategy | ||
| 520 | |a Design: Reliability and validity study | ||
| 520 | |a Participants: Patients with visual acuity records from 2018 in the IRIS Registry | ||
| 520 | |a Methods: Visual acuity measurements and metadata were identified and characterized from 2018 IRIS Registry records. Metadata, including laterality, assessment method (distance, near, and unspecified), correction (corrected, uncorrected, and unspecified), and flags for refraction or pinhole assessment were compared between Rome (frozen April 20, 2020) and Chicago (frozen December 24, 2021) versions. We developed a data-cleaning strategy to infer patients' corrected distance visual acuity in their better-seeing eye | ||
| 520 | |a Main Outcome Measures: Visual acuity data characteristics in the IRIS Registry | ||
| 520 | |a Results: The IRIS Registry Chicago data set contains 168 920 049 visual acuity records among 23 001 531 unique patients and 49 968 974 unique patient visit dates in 2018. Visual acuity records were associated with refraction in 5.3% of cases, and with pinhole in 11.0%. Mean (standard deviation) of all measurements was 0.26 (0.41) logarithm of the minimum angle of resolution (logMAR), with a range of - 0.3 to 4.0 A plurality of visual acuity records were labeled corrected (corrected visual acuity [CVA], 39.1%), followed by unspecified (37.6%) and uncorrected (uncorrected visual acuity [UCVA], 23.4%). Corrected visual acuity measurements were paradoxically worse than same day UCVA 15% of the time. In aggregate, mean and median values were similar for CVA and unspecified visual acuity. Most visual acuity measurements were at distance (59.8%, vs. 32.1% unspecified and 8.2% near). Rome contained more duplicate visual acuity records than Chicago (10.8% vs. 1.4%). Near visual acuity was classified with Jaeger notation and (in Chicago only) also assigned logMAR values by Verana Health. LogMAR values for hand motion and light perception visual acuity were lower in Chicago than in Rome. The impact of data entry errors or outliers on analyses may be reduced by filtering and averaging visual acuity per eye over time | ||
| 520 | |a Conclusions: The IRIS Registry includes similar visual acuity metadata in Rome and Chicago. Although fewer duplicate records were found in Chicago, both versions include duplicate and atypical measurements (i.e., CVA worse than UCVA on the same day). Analyses may benefit from using algorithms to filter outliers and average visual acuity measurements over time | ||
| 520 | |a Financial Disclosures: Proprietary or commercial disclosure may be found found in the Footnotes and Disclosures at the end of this article | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Epidemiology | |
| 650 | 4 | |a IRIS Registry | |
| 650 | 4 | |a Intelligent Research in Sight | |
| 650 | 4 | |a Visual acuity | |
| 700 | 1 | |a Kolomeyer, Natasha |e verfasserin |4 aut | |
| 700 | 1 | |a Goldberg, Jeffrey L |e verfasserin |4 aut | |
| 700 | 1 | |a Haller, Julia |e verfasserin |4 aut | |
| 700 | 1 | |a Lee, Cecilia S |e verfasserin |4 aut | |
| 700 | 1 | |a Lee, Aaron Y |e verfasserin |4 aut | |
| 700 | 1 | |a Lorch, Alice C |e verfasserin |4 aut | |
| 700 | 1 | |a Miller, Joan W |e verfasserin |4 aut | |
| 700 | 1 | |a Hyman, Leslie |e verfasserin |4 aut | |
| 700 | 1 | |a Pershing, Suzann |e verfasserin |4 aut | |
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