Dataset Information

Validation of Home Visual Acuity Tests for Telehealth in the COVID-19 Era.

ABSTRACT:

Importance

Visual acuity (VA) is one of the most important clinical data points in ophthalmology. However, few options for validated at-home VA assessments are currently available.

Objective

To validate 3 at-home visual acuity tests in comparison with in-office visual acuity.

Design, setting, and participants

Between July 2020 and April 2021, eligible participants with VA of 20/200 or better were recruited from 4 university-based ophthalmology clinics (comprehensive, cornea, glaucoma, and retina clinics). Participants were prospectively randomized to self-administer 2 of 3 at-home VA tests (printed chart, mobile phone app, and website) within 3 days before their standard-of-care clinic visit. Participants completed a survey assessing usability of the at-home tests. At the clinic visit, best-corrected Snellen distance acuity was measured as the reference standard.

Main outcomes and measures

The at-home VA test results were compared with the in-office VA test results using paired and unpaired t tests, Pearson correlation coefficients, analysis of variance, χ2 tests, and Cohen κ agreement. The sensitivity, specificity, positive predictive value, and negative predictive value of each at-home test were calculated to detect significant VA changes (≥0.2 logMAR) from the in-office baseline.

Results

A total of 121 participants with a mean (SD) age of 63.8 (13.0) years completed the study. The mean in-office VA was 0.11 logMAR (Snellen equivalent 20/25) with similar numbers of participants from the 4 clinics. Mean difference (logMAR) between the at-home test and in-office acuity was -0.07 (95% CI, -0.10 to -0.04) for the printed chart, -0.12 (95% CI, -0.15 to -0.09) for the mobile phone app, and -0.13 (95% CI, -0.16 to -0.10) for the website test. The Pearson correlation coefficient for the printed chart was 0.72 (95% CI, 0.62-0.79), mobile phone app was 0.58 (95% CI, 0.46-0.69), and website test was 0.64 (95% CI, 0.53-0.73).

Conclusions and relevance

The 3 at-home VA test results (printed chart, mobile phone app, and website) appeared comparable within 1 line to in-office VA measurements. Older participants were more likely to have limited access to digital tools. Further development and validation of at-home VA testing modalities is needed with the expansion of teleophthalmology care.

SUBMITTER: Bellsmith KN

PROVIDER: S-EPMC8972145 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Publications

Validation of Home Visual Acuity Tests for Telehealth in the COVID-19 Era.

Bellsmith Kellyn N KN Gale Michael J MJ Yang Sen S Nguyen Isabelle B IB Prentiss Christa J CJ Nguyen Luan T LT Mershon Sam S Summers Allison I AI Thomas Merina M

JAMA ophthalmology 20220501 5

<h4>Importance</h4>Visual acuity (VA) is one of the most important clinical data points in ophthalmology. However, few options for validated at-home VA assessments are currently available.<h4>Objective</h4>To validate 3 at-home visual acuity tests in comparison with in-office visual acuity.<h4>Design, setting, and participants</h4>Between July 2020 and April 2021, eligible participants with VA of 20/200 or better were recruited from 4 university-based ophthalmology clinics (comprehensive, cornea ...[more]

PMID: 35357405

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Project description:PurposeThe recent exponential growth in teleophthalmology has been limited in part by the lack of a validated method to measure visual acuity (VA) remotely. We investigated the validity of a self-administered Early Treatment Diabetic Retinopathy Study (ETDRS) home VA test. We hypothesized that a home VA test with a printout ETDRS chart is equivalent to a standard technician-administered VA test in clinic.DesignProspective cohort study.ParticipantsTwo hundred nine eyes from 108 patients who had a scheduled in-person outpatient ophthalmology clinic visit at an academic medical center.MethodsEnrolled patients were sent a .pdf document consisting of instructions and a printout ETDRS vision chart calibrated for 5 feet. Patients completed the VA test at home before the in-person appointment, where their VA was measured by an ophthalmic technician using a standard ETDRS chart. Survey questions about the ease of testing and barriers to completion were administered. For the bioequivalence test with a 5% nominal level, the 2 1-sided tests procedure was used, and an equivalent 90% confidence interval (CI) was constructed and compared with the prespecified 7-letter equivalence margin.Main outcome measuresThe primary outcome was the mean adjusted letter score difference between the home and clinic tests. Secondary outcomes included the unadjusted letter difference, absolute letter difference, and survey question responses.ResultsThe mean adjusted VA letter score difference was 4.1 letters (90% CI, 3.2-4.9 letters), well within the 7-letter equivalence margin. Average unadjusted VA scores in clinic were 3.9 letters (90% CI, 3.1-4.7 letters) more than scores at home. The absolute difference was 5.2 letters (90% CI, 4.6-5.9 letters). Ninety-eight percent of patients agreed that the home test was easy to perform.ConclusionsAn ETDRS VA test self-administered at home following a standardized protocol was equivalent to a standard technician-administered VA test in clinic in the examined population.

Project description:ImportanceIdentifying and tracking new infections during an emerging pandemic is crucial to design and deploy interventions to protect populations and mitigate the pandemic's effects, yet it remains a challenging task.ObjectiveTo characterize the ability of nonprobability online surveys to longitudinally estimate the number of COVID-19 infections in the population both in the presence and absence of institutionalized testing.Design, setting, and participantsInternet-based online nonprobability surveys were conducted among residents aged 18 years or older across 50 US states and the District of Columbia, using the PureSpectrum survey vendor, approximately every 6 weeks between June 1, 2020, and January 31, 2023, for a multiuniversity consortium-the COVID States Project. Surveys collected information on COVID-19 infections with representative state-level quotas applied to balance age, sex, race and ethnicity, and geographic distribution.Main outcomes and measuresThe main outcomes were (1) survey-weighted estimates of new monthly confirmed COVID-19 cases in the US from January 2020 to January 2023 and (2) estimates of uncounted test-confirmed cases from February 1, 2022, to January 1, 2023. These estimates were compared with institutionally reported COVID-19 infections collected by Johns Hopkins University and wastewater viral concentrations for SARS-CoV-2 from Biobot Analytics.ResultsThe survey spanned 17 waves deployed from June 1, 2020, to January 31, 2023, with a total of 408 515 responses from 306 799 respondents (mean [SD] age, 42.8 [13.0] years; 202 416 women [66.0%]). Overall, 64 946 respondents (15.9%) self-reported a test-confirmed COVID-19 infection. National survey-weighted test-confirmed COVID-19 estimates were strongly correlated with institutionally reported COVID-19 infections (Pearson correlation, r = 0.96; P < .001) from April 2020 to January 2022 (50-state correlation mean [SD] value, r = 0.88 [0.07]). This was before the government-led mass distribution of at-home rapid tests. After January 2022, correlation was diminished and no longer statistically significant (r = 0.55; P = .08; 50-state correlation mean [SD] value, r = 0.48 [0.23]). In contrast, survey COVID-19 estimates correlated highly with SARS-CoV-2 viral concentrations in wastewater both before (r = 0.92; P < .001) and after (r = 0.89; P < .001) January 2022. Institutionally reported COVID-19 cases correlated (r = 0.79; P < .001) with wastewater viral concentrations before January 2022, but poorly (r = 0.31; P = .35) after, suggesting that both survey and wastewater estimates may have better captured test-confirmed COVID-19 infections after January 2022. Consistent correlation patterns were observed at the state level. Based on national-level survey estimates, approximately 54 million COVID-19 cases were likely unaccounted for in official records between January 2022 and January 2023.Conclusions and relevanceThis study suggests that nonprobability survey data can be used to estimate the temporal evolution of test-confirmed infections during an emerging disease outbreak. Self-reporting tools may enable government and health care officials to implement accessible and affordable at-home testing for efficient infection monitoring in the future.

Dataset Information

Validation of Home Visual Acuity Tests for Telehealth in the COVID-19 Era.

Importance

Objective

Design, setting, and participants

Main outcomes and measures

Results

Conclusions and relevance

Publications

Validation of Home Visual Acuity Tests for Telehealth in the COVID-19 Era.

Similar Datasets

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