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Development and Validation of a Smartphone-Based Visual Acuity Test (Peek Acuity) for Clinical Practice and Community-Based Fieldwork.

ABSTRACT: IMPORTANCE:Visual acuity is the most frequently performed measure of visual function in clinical practice and most people worldwide living with visual impairment are living in low- and middle-income countries. OBJECTIVE:To design and validate a smartphone-based visual acuity test that is not dependent on familiarity with symbols or letters commonly used in the English language. DESIGN, SETTING, AND PARTICIPANTS:Validation study conducted from December 11, 2013, to March 4, 2014, comparing results from smartphone-based Peek Acuity to Snellen acuity (clinical normal) charts and the Early Treatment Diabetic Retinopathy Study (ETDRS) logMAR chart (reference standard). This study was nested within the 6-year follow-up of the Nakuru Eye Disease Cohort in central Kenya and included 300 adults aged 55 years and older recruited consecutively. MAIN OUTCOMES AND MEASURES:Outcome measures were monocular logMAR visual acuity scores for each test: ETDRS chart logMAR, Snellen acuity, and Peek Acuity. Peek Acuity was compared, in terms of test-retest variability and measurement time, with the Snellen acuity and ETDRS logMAR charts in participants' homes and temporary clinic settings in rural Kenya in 2013 and 2014. RESULTS:The 95% CI limits for test-retest variability of smartphone acuity data were ±0.033 logMAR. The mean differences between the smartphone-based test and the ETDRS chart and the smartphone-based test and Snellen acuity data were 0.07 (95% CI, 0.05-0.09) and 0.08 (95% CI, 0.06-0.10) logMAR, respectively, indicating that smartphone-based test acuities agreed well with those of the ETDRS and Snellen charts. The agreement of Peek Acuity and the ETDRS chart was greater than the Snellen chart with the ETDRS chart (95% CI, 0.05-0.10; P?=?.08). The local Kenyan community health care workers readily accepted the Peek Acuity smartphone test; it required minimal training and took no longer than the Snellen test (77 seconds vs 82 seconds; 95% CI, 71-84 seconds vs 73-91 seconds, respectively; P?=?.13). CONCLUSIONS AND RELEVANCE:The study demonstrated that the Peek Acuity smartphone test is capable of accurate and repeatable acuity measurements consistent with published data on the test-retest variability of acuities measured using 5-letter-per-line retroilluminated logMAR charts.

SUBMITTER: Bastawrous A

PROVIDER: S-EPMC5321502 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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Development and Validation of a Smartphone-Based Visual Acuity Test (Peek Acuity) for Clinical Practice and Community-Based Fieldwork.

Bastawrous Andrew A Rono Hillary K HK Livingstone Iain A T IA Weiss Helen A HA Jordan Stewart S Kuper Hannah H Burton Matthew J MJ

JAMA ophthalmology 20150801 8

<h4>Importance</h4>Visual acuity is the most frequently performed measure of visual function in clinical practice and most people worldwide living with visual impairment are living in low- and middle-income countries.<h4>Objective</h4>To design and validate a smartphone-based visual acuity test that is not dependent on familiarity with symbols or letters commonly used in the English language.<h4>Design, setting, and participants</h4>Validation study conducted from December 11, 2013, to March 4, ...[more]

PMID: 26022921

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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:Background & aimsDetection of covert hepatic encephalopathy (CHE) is difficult, but point-of-care testing could increase rates of diagnosis. We aimed to validate the ability of the smartphone app EncephalApp, a streamlined version of Stroop App, to detect CHE. We evaluated face validity, test-retest reliability, and external validity.MethodsPatients with cirrhosis (n = 167; 38% with overt HE [OHE]; mean age, 55 years; mean Model for End-Stage Liver Disease score, 12) and controls (n = 114) were each given a paper and pencil cognitive battery (standard) along with EncephalApp. EncephalApp has Off and On states; results measured were OffTime, OnTime, OffTime+OnTime, and number of runs required to complete 5 off and on runs. Thirty-six patients with cirrhosis underwent driving simulation tests, and EncephalApp results were correlated with results. Test-retest reliability was analyzed in a subgroup of patients. The test was performed before and after transjugular intrahepatic portosystemic shunt placement, and before and after correction for hyponatremia, to determine external validity.ResultsAll patients with cirrhosis performed worse on paper and pencil and EncephalApp tests than controls. Patients with cirrhosis and OHE performed worse than those without OHE. Age-dependent EncephalApp cutoffs (younger or older than 45 years) were set. An OffTime+OnTime value of >190 seconds identified all patients with CHE with an area under the receiver operator characteristic value of 0.91; the area under the receiver operator characteristic value was 0.88 for diagnosis of CHE in those without OHE. EncephalApp times correlated with crashes and illegal turns in driving simulation tests. Test-retest reliability was high (intraclass coefficient, 0.83) among 30 patients retested 1-3 months apart. OffTime+OnTime increased significantly (206 vs 255 seconds, P = .007) among 10 patients retested 33 ± 7 days after transjugular intrahepatic portosystemic shunt placement. OffTime+OnTime decreased significantly (242 vs 225 seconds, P = .03) in 7 patients tested before and after correction for hyponatremia (126 ± 3 to 132 ± 4 meq/L, P = .01) 10 ± 5 days apart.ConclusionsA smartphone app called EncephalApp has good face validity, test-retest reliability, and external validity for the diagnosis of CHE.

Project description:ImportanceVisual 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.ObjectiveTo validate 3 at-home visual acuity tests in comparison with in-office visual acuity.Design, setting, and participantsBetween 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 measuresThe 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.ResultsA 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 relevanceThe 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.

Dataset Information

Development and Validation of a Smartphone-Based Visual Acuity Test (Peek Acuity) for Clinical Practice and Community-Based Fieldwork.

Publications

Development and Validation of a Smartphone-Based Visual Acuity Test (Peek Acuity) for Clinical Practice and Community-Based Fieldwork.

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