Does the EyeChart App for iPhones Give Comparable Measurements to Traditional Visual Acuity Charts?

Smart Devices in Optometry: Current and Future Perspectives to Clinical Optometry

There is a huge unmet need for eye care with more than a hundred million people living without basic eye care services and facilities. There is an exigency to deploy adequate resources in terms of manpower and equipment to address this. The usage of smart devices in optometry and eye care practice has been gaining momentum for last half a decade, due to the COVID-19 pandemic and technological advancements in telemedicine. These smart devices will help facilitate remote monitoring of important visual functions, ocular signs and symptoms, thus providing better eye care services and facilities and promoting outreach services. Smart devices in optometry exist in the form of gadgets that can be worn in the wrist, and spectacle-mounted or head-mounted devices. On the other hand, with the ubiquitous nature of smartphones, a large number of smartphone applications have been developed and tested for advanced optometry and primary eye care practice, which may potentially reduce the burden of inadequate resources and the unmet need for eye care. This article aims to give an overview of the current trends and future perspectives on the application of such smart devices in optometric practice.

Agreement between a mobile applet-based visual acuity self-test program and the conventional method for distance and near visual acuity tests

BACKGROUND

To investigate the agreement between a mobile applet-based visual acuity (VA) self-test program and the conventional VA tests.

METHODS

This consecutive case series study included 121 children and adults (242 eyes). Patients were classified into three groups according to age (children, adolescents, and adults). They underwent uncorrected distance visual acuity (UDVA) testing, distance visual acuity with available spectacle correction (DVA with ASC) testing at 2.5-m distance, uncorrected near visual acuity (UNVA) testing, and near visual acuity with available spectacle correction (NVA with ASC) testing at a 0.4-m distance using a mobile applet-based VA self-test program and conventional VA tests in two eyes.

RESULTS

Correlations among UDVA, DVA with ASC, UNVA, and NVA with ASC between the two methods were significant in all subjects (all p < 0.001). The intraclass correlation coefficient were 0.960, 0.845, 0.960, and 0.669, respectively (all p < 0.001). The proportions of bias outside the 95% confidence interval limit of agreements were 6.20%, 4.82%, 7.08%, and 6.10%, respectively. There were significant differences in NVA with ASC between the two methods (p < 0.05) in the adolescent group, but no differences in measured parameters were found among children and adult groups.

CONCLUSIONS

There is good agreement between the mobile applet-based VA self-test program and the conventional VA tests. The VA self-test has good practical value especially in the current pandemic, allowing self-screening of visual acuity, myopia control, and remote management of visual impairment in ocular morbidity.

The Accuracy of a Web-Based Visual Acuity Self-assessment Tool Performed Independently by Eye Care Patients at Home: Method Comparison Study

BACKGROUND

 Telehealth solutions can play an important role in increasing access to eye care. Web-based eye tests can enable individuals to self-assess their visual function remotely without the assistance of an eye care professional. A web-based tool for self-assessing visual acuity (VA) has previously been studied in controlled, supervised conditions. The accuracy of this tool when performed independently by patients in their home environment, using their own devices, has not yet been examined.

OBJECTIVE

 The objective of this paper was to examine the accuracy of a web-based tool with respect to measuring VA in ophthalmic patients in their home environment, compared with a conventional in-hospital assessment using a Snellen chart (the gold standard).

METHODS

 From April through September 2020, consecutive adult patients with uveitis at the University Medical Center Utrecht, the Netherlands, performed the web-based VA test at home (the index test) before their upcoming conventional VA assessment at the hospital (the reference test). The agreement between the 2 tests was assessed by the Bland-Altman analysis. Additional analyses were performed to investigate associations between clinical characteristics and the accuracy of the web-based test.

RESULTS

 A total of 98 eyes in 59 patients were included in the study. The difference in VA between the index and reference tests was not significant, with a mean difference of 0.02 (SD 0.12) logMAR (P=.09) and 95% limits of agreement of -0.21 to 0.26 logMAR. The majority of the differences (77%) fell within the predetermined acceptable deviation limit of 0.15 logMAR. In addition, no patient characteristics or clinical parameters were found to significantly affect the accuracy of the web-based test.

CONCLUSIONS

 This web-based test for measuring VA is a valid tool for remotely assessing VA, also when performed independently by patients at home. Implementation of validated web-based tools like this in the health care system may represent a valuable step forward in revolutionizing teleconsultations and can provide individual patients with the opportunity to self-monitor changes in VA. This is particularly relevant when the patient's access to ophthalmic care is limited. Future developments should focus on optimizing the testing conditions at home to reduce outliers.

Comparison of smartphone application-based visual acuity with traditional visual acuity chart for use in tele-ophthalmology

PURPOSE:

The aim of this study was to compare the visual acuity (VA) by smartphone-based applications – EyeChart and the Peek Acuity to the standard Snellen chart to explore the possibility of using them as an alternative in tele-ophthalmology in the current COVID-19 pandemic.

MATERIALS AND METHODS:

An analytical type of observational study was done on 360 eyes of 184 patients above 18 years of age. Patients with VA <6/60 and gross ocular pathology were excluded from the study. VA measured by these three methods was converted to logMAR scale for ease of statistical analysis. One-way analysis of variance with post Tukey HSD was used to compare the VA measured by these three methods.

RESULTS:

There was no statistically significant difference between VA measured using the smartphone-based apps (EyeChart and Peek Acuity) and the Snellen chart (F = 2.5411, P = 0.7925) in 360 eyes assessed. VA measured by Peek Acuity (P = 0.5225) was more comparable to Snellen chart than EyeChart (P = 0.4730). Intraclass correlation coefficient (ICC) demonstrated a strong positive correlation for EyeChart (ICC: 0.982, P < 0.001) and Peek Acuity (ICC: 0.980, P < 0.001) with Snellen chart. A Bland–Altman difference plot showed good limits of agreement for both EyeChart and Peek Acuity with Snellen chart. In subgroup analysis, VA measured by Peek Acuity was not statistically different from Snellen in any subgroups, but in EyeChart, it was statistically different in emmetropes.

CONCLUSION:

VA measured by smartphone apps (EyeChart and Peek Acuity) was comparable with traditional Snellen chart and can be used as an effective, reliable, and feasible alternative to assess VA in tele-ophthalmology.

Digital Tools for the Self-Assessment of Visual Acuity: A Systematic Review

INTRODUCTION

Numerous digital tools to self-assess visual acuity have been introduced. The recent COVID-19 pandemic underlined the need for high-quality remote care. This review gives a current overview of digital tools for remotely assessing visual function and reports on their accuracy.

METHODS

We searched the databases of Embase and Pubmed, and systematically reviewed the literature, conforming to PRISMA guidelines. Two preliminary papers were added from medRxiv.org. The main outcome was the agreement of the digital tools with conventional clinical charts, as expressed by mean differences and 95% limits of agreement (95% LoA).

RESULTS

Seventeen publications included studies reported on 13 different digital tools. Most of the tools focus on distance visual acuity. The mean differences of the digital tools ranged from - 0.08 to 0.10 logMAR, when compared to traditional clinical assessments. The 95% LoA differed considerably between studies: from ± 0.08 logMAR to ± 0.47 logMAR, though the variability was less pronounced for higher visual acuities.

CONCLUSION

The low mean differences between digital visual acuity assessments and reference charts suggest clinical equivalence, though the wide 95% LoA identify a lower precision of digital self-assessments. This effect diminishes in individuals with better visual acuities, which is a common feature of visual acuity assessments. There is great potential for the digital tools to increase access to eye care and we expect the accuracy of the current tools to improve with every iteration in technology development.

Evaluation of a New Method to Track Changes in Vision at Home for Children Undergoing Amblyopia Treatment

PURPOSE

A new amblyopia tracker app has been designed to provide parents with a method of monitoring a child's vision by presenting a single optotype size that the tester moves to identify the furthest distance the optotypes can be seen. The aim of this study is to evaluate this methodology in adults, comparing the findings to visual acuity (VA) measured with the iSight app and to determine the test retest variability.

METHODS

Adults, aged 18-39 years, with no known eye condition and VA ≤ 0.7 logMAR were recruited. Bangerter filters were used to simulate amblyopia, where VA was reduced below 0.0 with an interocular difference of at least 0.2 logMAR. Testing for both apps was performed monocularly, with the test order being randomised.

RESULTS

Data from 32 subjects were analysed. For the test retest variability analysis, paired t-tests showed no statistically significant difference between the tests for either eye, either app or the interocular acuity difference (p > 0.3 in all cases). Bland Altman plots showed similar limits of agreement between the two apps. When comparing measurements between the apps there was no statistically significant difference on the first or second test, either eye or the interocular acuity difference (p > 0.5 in all cases).

CONCLUSION

The results support the theory that changing distance is a valid method of assessing VA as the measurements agree well with the standard approach of reducing optotype size. Test retest variability is similar between the two apps and there is good agreement between the measurements.