Contrast Sensitivity and Visual Acuity Among the Elderly

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Contrast Sensitivity and Visual Acuity among the Elderly

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in

the Graduate School of The Ohio State University

Mawada Osman

Graduate Program in Vision Science

The Ohio State University

2020

Master's Examination Committee:

Angela M. Brown, PhD, Advisor

Bradley E. Dougherty, OD, PhD

Heidi A. Wagner, OD, MPH

Mawada Osman

2020

Abstract

Purpose: To establish the clinical utility and strengthen the validity of the Ohio Contrast

Cards (OCC), expand the use of the OCC in a healthy elderly population, and form a baseline dataset of patients to be compared to patients with dementia.

Method: Participants ages 65 and over (N = 51) were recruited from the Ohio State

University Primary Vision Care (PVC). We assessed the visual function of each patient using four visual tests which include: OCC, Pelli-Robson Chart (PR), Teller Acuity Cards

(TAC) and Clear Chart. The contrast sensitivity tests (OCC and PR) were assessed twice, once by each tester. The PR contrast levels were also evaluated at two different distances

1 meter and 3 meters (0.50 meter if visual acuity worse than 6.0 cy/cm). Cognitive abilities were evaluated using the 6-Item Cognitive Impairment Test (6-CIT).

Results: A significant effect of test was revealed (p < 0.005), in favor of OCC, yielding consistently higher average LogCS scores than PR, average difference of 0.412 LogCS.

The PR and OCC revealed similar repeatability with 95% LoA of ± 0.28 log units and

95% LoA of ± 0.27 log units, respectively. No statistically significant effect of testing distance was found. Strong statistically significant correlations were found between grating CS (OCC) vs. grating VA (TAC), letter CS (PR) vs. letter VA (Clear Chart),

Grating CS (OCC) vs. letter CS (PR), and Grating VA (TAC) vs. letter VA (Clear Chart).

No statistically significant association between cognitive impairment scores and age vs. our four tests (PR, OCC, TAC, Clear Chart) was found.

Conclusion: The Ohio Contrast Cards serve as an alternative to the Pelli-Robson chart and show greater potential in uninstructable patients (e.g. dementia patients).

Dedication

This document is dedicated to my family and friends.

Acknowledgments

Dr. Angela Brown has been a great mentor and advisor to me throughout this project. I am grateful for her guidance and support as I learned to grow as a researcher and developed a deeper understanding of vision science.

I would like to acknowledge Faustina Ottie Opoku for her dedication to collecting data and for always keeping me motivated .

I must thank the Ohio State College of Optometry’s Primary Vision Care Clinic, especially Dr. Dawn Goedde, chief, and the check-in and scheduling staff, for helping with recruiting and for their tremendous support and encouragement.

Finally, I would like to thank my committee members Dr. Bradley E. Dougherty and Dr.

Heidi A. Wagner for serving on my committee and providing me with advice on how to perfect my work.

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Vita

2012...... Gahanna Lincoln High School

2016...... B.S. Biology, The Ohio State University

2016 to present ...... O.D./M.S. student, College of Optometry,

The Ohio State University

Fields of Study

Major Field: Vision Science

Table of Contents

Abstract ...... i

Dedication ...... ii

Acknowledgments...... iii

Vita ...... iv

Fields of Study ...... iv

Table of Contents ...... v

List of Tables ...... viii

List of Figures ...... ix

Chapter 1: Introduction ...... 1

1.1: Visual Acuity ...... 2

1.1.1: Bailey Lovie Chart ...... 2

1.1.2: Clear Chart ® 4 Digital Acuity System ...... 4

1.1.3: Teller Acuity Cards ...... 6

1.2.1: Pelli-Robson Chart ...... 9

1.2.2: The Ohio Contrast Cards ...... 12

1.3: Cognitive Impairment ...... 14

1.3.1: Six-Item Cognitive Impairment Test ...... 14

1.4: Overview of this project ...... 16

Chapter 2: Methods ...... 17

2.1: Power Analysis ...... 17

2.2: Participants ...... 19

2.3: Visual Acuity Procedures ...... 19

2.3.1: Letter acuity ...... 19

2.3.2: Grating acuity ...... 20

2.4: Contrast Sensitivity Procedures ...... 20

2.4.1: Letter Contrast ...... 20

2.4.2: Grating Contrast ...... 21

2.5: Mental Status Assessment ...... 21

2.5.1: Six-Item Cognitive Impairment Test ...... 21

2.6: Randomization: ...... 22

Chapter 3: Analysis...... 24

Chapter 4: Results...... 25

4.1: Pelli-Robson and Ohio Contrast Cards Performance ...... 25

4.2: Test-Retest Reliability ...... 28

4.3: Testing Distance of PR...... 31

4.4: Contrast Sensitivity vs. Visual Acuity ...... 32

4.5: Gratings vs. Letters ...... 34

4.6: Cognitive impairment Test ...... 35

Chapter 5: Discussion ...... 37

5.1: Test-Retest Reliability of the OCC and PR chart ...... 37

5.2: Testing Distance of the Pelli-Robson Chart...... 37

5.3: Contrast Sensitivity vs. Visual Acuity ...... 38

5.4: Grating vs. Letter ...... 39

5.5: Cognitive test results: ...... 40

5.6: Future work ...... 40

Appendix A: Study Materials ...... 41

References:...... 61

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List of Tables

Table 1.1: Snellen Standard and LogMAR size progression of the Clear Chart ® Digital

Acuity System ...... 6

Table 2.1: Chosen Standard Deviations for power analysis ...... 18

Table 4.1: Average contrast sensitivity scores for each test (PR1m, OCC) by each tester

± standard deviation (N) ...... 25

Table 4.2: Three-way repeated measures ANOVA ...... 27

Table 4.3: Mean difference and standard deviation between PR1m and OCC for each tester...... 28

Table 4.4: Average difference, standard deviation of the difference, and limit of agreement indicating the test-retest reliability ...... 28

Table 4.5: Mean LogCS of OCC for first test by tester M and second test by tester T. ... 30

Table 4.6: Mixed ANOVA was calculated to measure the significance of PR distance (1m vs. 3m) and interaction between Distance and Tester (M vs. T) ...... 32

Table 4.7: Correlation between all four tests (Clear Chart, Teller, PR1m, OCC) ...... 35

Table 4.8: 6-Item Cognitive Impairment Test – Error scores greater than 10 ...... 36

Table 4.9: Linear Regression analyses to determine association between cognitive testing score and age vs. four visual tests (PR, OCC, TAC, Clear Chart) ...... 36

viii

List of Figures

Figure 1.1: Bailey-Lovie Acuity Chart ...... 3

Figure 1. 2: Clear Chart ® Digital Acuity System ...... 5

Figure 1.3: Teller Acuity Cards ...... 8

Figure 1.4: Pelli-Robson Chart ...... 11

Figure 1.5: Ohio Contrast Cards ...... 14

Figure 2.1: Randomization Sequences ...... 23

Figure 4.1: Average contrast sensitivity scores (log10 Michelson contrast sensitivity) for each test by each tester ± standard error ...... 26

Figure 4.2: Regression line and correlation coefficient for OCC vs. PR were calculated excluding the highly influential data point (triangle), the four points scored outside of normal on 6-CIT (squares), and participants tested by Tester A (diamonds)...... 27

Figure 4.3: Bland-Altman plots of test-retest data for two contrast sensitivity tests.

Difference between first and second administration of each test as a function of their average. All tests were Log10 Michelson units. Solid line: average difference. Dashed lines: ± 1.96 x SDdifference. A. Pelli-Robson Chart, B. Ohio Contrast Cards. Red data points: participants with cognitive impairment; Blue data points: participants tested by tester A ...... 30

Figure 4.4: Bland-Altman plots of test-retest of OCC. A. Tester M as the first tester, B.

Tester T as the first tester. Difference between first and second administration as a function of their average. All tests were Log10 Michelson units. Solid line: average

ix difference. Dashed lines: ± 1.96 x SDdifference. Red data points: participants with cognitive impairment; Blue data points: participants tested by tester A ...... 31

Figure 4.5: Average Log10 contrast threshold scores for Pelli-Robson at a distance of

1 meter and 3 meters ...... 32

Figure 4.6: Comparison between visual acuity and contrast threshold. Red data points: participants with cognitive impairment. Blue data points: participants tested by tester A.

Triangle: outlier...... 33

Figure 4.7: Comparison between grating and letter performance. Red data points: participants with cognitive impairment, Blue data points: participants tested by tester A.

Triangle: outlier...... 34

Chapter 1: Introduction

For many years now, the visual function of a patient has been determined by his/her visual acuity, which is measured by the smallest letters/symbols a patient can resolve. However, visual acuity does not provide the full picture of a patient’s visual capabilities. It lacks in predicting the quality of life of individuals, especially when it comes to simple everyday tasks such as walking down the stairs, stepping off a sidewalk or recognizing a handwave across the street. Such mobility tasks and social interactions have been shown to be limited by contrast sensitivity as opposed to visual acuity (Owsley

& Sloane, 1987) . Significant loss of visual acuity may help predict visual disability.

However, patients with normal visual acuity and reduced contrast sensitivity can have serious visual disabilities as well. The purpose of this research is to expand on the work done by Hopkins et al. in establishing the clinical utility of the Ohio Contrast Cards and to strengthen its validity (Hopkins, Dougherty, & Brown, 2017). This project will look specifically at the elderly, which is a different population that may benefit from contrast sensitivity testing. The goal of my research is to evaluate a new test of contrast sensitivity that is designed to be used on normal, visually impaired, and elderly populations with or without dementia.

1.1: Visual Acuity

1.1.1: Bailey Lovie Chart

The Bailey-Lovie acuity chart was developed in the 1970s by Ian Bailey and Jan

Lovie (Bailey & Lovie, 1976). The acuity chart provides the ability to test at different distances which serves to be useful in cases of low visual acuity, shorter examination rooms and verifying visual acuity scores to be able to detect malingerers. As shown in

Figure 1.1, the 80x75 cm chart, printed on a matte white card, is designed with five letters of equal legibility per row. The spacing between the letters and between the rows is standardized to be equal to one letter-width and the height of the letters on the lower line, respectively. The chart has a visual acuity range of 6/60 to 6/3 (20/200 to 20/10) at a standardized testing distance of 6 m (20 ft). Conveniently, the chart provides the logMAR acuity rating on one side of the chart and the Snellen acuity ratings on the other side

(Bailey & Lovie, 1976). The Baily-Lovie acuity chart follows a uniform logrithmic scale.

The letter sizes decrease by a factor of 0.1 log units across rows. This allows for using the chart at any nonstandard viewing distance. Therefore, when the testing distance is reduced by 0.1 log unit (a decrease of about 25%), the angular size of the letters on the chart increase by 0.1 log unit, a 25% increase, allowing the observer to read one row further. The test is administered by allowing the patient to read down the chart until more than half the letters are missed per row. Completion of the test is achieved once the patient misses 3 out of 5 letters in a row.

The Bailey-Lovie chart came with new advantageous features in the 1970s compared to the acuity charts that were used during that time (i.e. Snellen) . With the

Bailey-Lovie chart, the visual acuity task is equivalent at each acuity level, regardless of viewing distance, allowing letter size to be the sole influencer of visual acuity score.

Compared to the Bailey-Lovie chart, other acuity charts have irregular progression of letter size, and thus, changes in testing distance will impact the acuity scores (Bailey &

Lovie, 1976).

Although the Bailey-Lovie chart has many enhanced features that allow for more accurate measurements of visual acuity, it still requires the patient to be able to recognize and report the letters, which will be difficult for some patients with cognitive impairment such as dementia.

Figure 1.1: Bailey-Lovie Acuity Chart (Bailey & Lovie-Kitchin, 2013)

1.1.2: Clear Chart ® 4 Digital Acuity System

Clear Chart® 4 Digital Acuity System (Figure 1. 2), manufactured by AMETEK, is an electronic chart used in many eye care professional settings. The chart distance can be set up in two methods, direct throw where the chart is set up in front of the patient at a certain distance (usually 20 feet) or the mirror set up where the chart is set up behind the patient to reflect on a mirror in front of the patient. The chart is mainly used to measure visual acuity, although it contains many other features such as suppression testing, contrast sensitivity testing and disparity testing (Reichert, 2019).

The acuity notation can be displayed in Snellen (distance in feet over size in mm), metric (distance in meters over size in mm) or decimal (inverse of Snellen). The chart contains a variety of optotypes including: 17 letter, 8 letter, Sloan, Tumbling E, Landolt

C, HOTV and numbers. All optotypes within the Clear Chart Digital Acuity System follow the ANSI guidelines for ophthalmic instruments – general purpose clinical visual acuity charts (Reichert, 2019). The stroke width of each optotype is one-fifth of its overall size. The 17 letter optotype option is the default optotype used at the Ohio State

University optometry clinic which consists of the letters: A, B, C, D, E, F, G, H, K, L, N,

O, P, T, U, V, Z (Reichert, 2019). The chart provides the option of displaying multiple lines (up to 6) of descending size of optotype or one line at a time. Each line contains five letters. The size progression of each line can be set as standard progression or LogMAR progression as shown in Table 1.1. The logMAR size progression adds four more size levels concentrated at the end of the spectrum (20/100 to 20/400 range). This serves as an

4 advantage in a low vison clinical setting to detect the true visual acuity function of a patient. The test is administered by allowing the patient to read each line displayed until more than half of the letters are missed on a line. The test is completed once the patient misses 3 out of 5 letters.

Although Clear Chart® 4 Digital Acuity System is used in many optometry and ophthalmology clinics, it does have some limitations, especially in a low vision setting.

The largest letter size is 20/400 and the chart cannot display multiple letters in one line at the larger letter size range. This of course may not capture the true visual acuity of a patient with low vision. However, the ability to randomize the letters serves as an advantage when testing patients and avoids the problem of memorization.

Figure 1. 2: Clear Chart ® Digital Acuity System (from Reichert Technologies)

Table 1.1: Snellen Standard and LogMAR size progression of the Clear Chart ® Digital Acuity System Standard Size Progression LogMAR Size Progression 20/10 20/10 20/15 20/12.5 20/20 20/16 20/25 20/20 20/30 20/25 20/40 20/32 20/50 20/40 20/60 20/50 20/70 20/63 20/80 20/80 20/100 20/100 20/200 20/125 20/400 20/160 - 20/200 - 20/250 - 20/320 - 20/400

1.1.3: Teller Acuity Cards

The Teller Acuity Cards were developed in the 1980s by Davida Teller

(McDonald et al., 1985). The cards have been used most commonly in pediatric ophthalmology and optometry practices for many years. They are used to measure the highest spatial frequency an observer can resolve.

The cards are a set of sixteen 22 cm x 55 cm gray cards, each with vertical black- and-white grating centered within one half of the card’s face (Figure 1.3). The spatial frequency increases across the cards in half octave steps, progressing from very coarse gratings, more easily seen, to the finest limit of visibility. To be able to observe the participant’s personal looking behavior before testing begins, two cards are included, one 6 with a blank surface and the other with very wide stripes of 0.23 cycles per cm. This allows the examiner to become familiar with the “looking behavior” compared to the

“non-looking behavior” of the participant (Dobson & Teller, 1978). There is also a 4mm round peephole in the center of each card to allow the examiner to observe the participant’s eyes (especially in the case of infants) without causing any distractions. The examiner presents the cards, one at a time, at a testing distance of 55.5cm, approximately the length of a card. The visual acuity is estimated based on the looking behavior of the participant, or, if the participant is instructable, then the visual acuity is determined based on where the participant points. The participant’s visual acuity is the finest grating the patient can see.

Many patients with dementia have difficulty communicating the letters seen on a standard acuity chart (e.g., Bailey lovie or ETDRS) which can lead to misdiagnosis of vision conditions in a clinical setting (Friedman, Munoz, Massof, Bandeen-Roche, &

West, 2002). The Teller Acuity Cards overcame the communication barrier and filled in the need for testing the vision of those who cannot recognize letters or characters. One study by Friedman and colleagues, assessed the performance of the Teller Acuity Cards compared to letter or shape identification visual acuity charts, specifically ETDRS chart or Lea symbols, in participants with dementia (Friedman et al., 2002). Eighty-four percent of their participants were successfully tested with the Teller Acuity Cards, as opposed to seventy-four percent who were testable by the ETDRS or Lea symbols. The standard Mini-Mental Status Examination (MMSE), consisting of twenty questions, was

7 also administered by the authors to test for the level of cognitive impairment. A score of

0 corresponds to not answering any of the questions correctly, while a score of 30 indicates a perfect score. Any score below 18 is considered a severe cognitive impairment. The authors found that more patients with scores lower than 10 were testable with the Teller Acuity Cards compared to recognition acuity charts. This demonstrated how the Teller Acuity Cards can be effective in testing the visual acuity of cognitively impaired individuals who were, otherwise, unable to be tested by standard means. This finding provided the opportunity for those with both dementia and reduced vision and were otherwise untestable by conventional recognition acuity to be recognized as those who would qualify for vision rehabilitation (Friedman et al., 2002).

Figure 1.3: Teller Acuity Cards (from www.Precision-Vision.com)

1.2: Contrast Sensitivity

1.2.1: Pelli-Robson Chart

Contrast sensitivity measurement provides a means of early detection of various diseases, such as Glaucoma, that impair the visual function yet cannot be measured by visual acuity (Wolkstein, Atkin, & Bodis-Wollner, 1980). One of the earliest attempts to measure contrast sensitivity in a clinical setting was by George Young where he used waterproof inks of Winsor and Newton to create a small album with pages of various ink dilutions (Young, 1918). The inks were diluted to create a circular spot in each page. The first page was made of the most dilute ink and each succeeding page had a spot of ink twice the intensity of the previous one. Young would present the album to a patient in his clinic and allow the patient to turn from one page to the next starting from pages with spots of too low contrast to be seen to a page where the patient is able to see a spot. The patient’s threshold was then reported as the dilution of ink used at the page where the patient was first able to see the spot of ink. Subsequent successful attempts in measuring contrast sensitivity have followed. These were mainly done in the laboratory, using the cathode-ray tube and elaborate psychophysical procedures. However, these methods were complex and took time, which made them far from ideal for clinical use. In the late

1980s, Denis Pelli and John Robson wanted to find an efficient way of measuring contrast sensitivity in a clinical setting (Pelli & Robson, 1988). Consequently, they developed the Pelli-Robson contrast sensitivity chart, a letter chart that has been commonly used ever since.

The Pelli-Robson chart displays forty-eight large Sloan letters of constant size, designed to work in conjunction with the Sloan acuity letters. The letters are arranged on a 60 x 85 cm chart in sets of triplets (Figure 1.4), which contain the same contrast, decreasing in log10 contrast from top to bottom and left to right as you progress from one triplet to the other. Each group of three letters is decreased in contrast by a factor 0.71

(1/√2) (log contrast 0.15) of the proceeding set. The size of the letters on the chart subtend 0.5 degrees at 3m, which is the testing distance suggested by Pelli et al. The test is scored in LogCS units, where each set of triplets advances in steps of 0.15 log units ranging from LogCS of 0.00 (approx. 100% contrast) to LogCS 2.25 (approx. 0.56% contrast). However, Pelli and Robson suggested that the chart is to be used at a nearer testing distance in low vision patients. They also recommended putting the chart on a background that is as bright as the chart itself in order to detect any decrease in contrast sensitivity that may be due to a disease resulting in wide-angle light scatter such as cataracts (Pelli & Robson, 1988).

The test is administered by asking the subject to read the letters on the chart, starting with the highest contrast. The test ends when two out of the three letters in a group are read incorrectly. The subject’s score in LogCS will be the preceding triplet read correctly.

While the Pelli-Robson chart contains many beneficial features in measuring the contrast sensitivity of individuals, the recognition of optotypes makes it particularly hard to measure contrast sensitivity on uninstructable patients or those with dementia.

Figure 1.4: Pelli-Robson Chart (from www.Precision-Vision.com)

1.2.2: The Ohio Contrast Cards

Currently, there are no clinical tests of contrast sensitivity that can be used on uninstructable patients or those who cannot be tested using a letter chart. The first work done on establishing a grating method to test contrast sensitivity was the recent work done by Hopkins and Brown in 2017 (Hopkins et al., 2017). Their main goal was to create a different method of measuring the maximum contrast sensitivity while addressing the limitations of the Pelli-Robson chart. Hopkins’ study has measured the contrast sensitivity in low vision patients at the Ohio State School for the Blind using the

Ohio Contrast Cards (the same cards as those used in this study) and assessed how the quality of life may be impacted. The study found that higher contrast sensitivity using the

Ohio Contrast Cards was associated with better vision-related quality of life, compared to other standardized tests such as the Bailey Lovie, Pelli-Robson charts and Teller Acuity

Cards (Hopkins et al., 2017).

The dimensions of the gratings and the overall reflectance of the Ohio Contrast

Cards resemble the Teller Acuity Cards in that they are 55.5 x 25.5 cm and 50%, respectively (Hopkins et al., 2017). This will allow the Ohio Contrast Cards to be used in clinic in conjunction with the Teller Acuity Cards through the “seen/not seen” method.

Similar to the Teller Acuity Cards, there is a 3mm peephole in the center of the card to facilitate testing in patients that can be easily distracted such as infants. Since most eye movement disorders affect the horizontal rather than the vertical eye movements, the cards consist of horizontal gratings of low spatial frequency square wave. On one side of

12 the Ohio Contrast Cards there is a 22x20 cm horizontal square wave grating with a fixed spatial frequency of 1 cycle per 6.7 cm (Figure 1.5). The cards have a constant space- average luminance. The grating consists of three complete cycles of light and dark stripes. Each card presents a contrast value between 96% and 1 % contrast. The cards progress in 0.15 log10 unit steps, corresponding to the step-size of the Pelli-Robson Chart

(Hopkins et al., 2017).

The test is administered at 57 cm, which is the distance at which a 1 cm stimulus will subtend 1 degree of arc at the eye. The cards are presented one at a time from high contrast to low contrast using the descending method of limits. Depending on the patient’s capability, the patient either points to the side with the grating or looks at the grating. The examiner then determines whether each grating was “seen or not seen”. The test ends when the patient cannot indicate the location of the grating. The patient’s contrast threshold is the lowest contrast the patient is able to correctly identify.

Just as the Teller Acuity Cards opened new avenues in the mid-1980s in testing patients that cannot otherwise recognize letters or characters, the Ohio Contrast Cards may do the same for contrast sensitivity testing. The Ohio Contrast Cards provide an opportunity to expand on the data collected during a clinical exam. The purpose of the cards is to introduce a new clinical method in measuring contrast sensitivity in all patients including those that are uninstructable (e.g. infants and dementia patients).

Figure 1.5: Ohio Contrast Cards (Hopkins et al., 2017)

1.3: Cognitive Impairment

1.3.1: Six-Item Cognitive Impairment Test

The Six- Item Cognitive Impairment Test (6-CIT) is a test used to assess cognitive impairment. It was developed by Katzman and his collaborators in the early

1980s (Katzman et al., 1983). It consists of a 6-item subset of the 26-item Information-

Memory-Concentration Test. The Six-Item Cognitive Impairment Test (6-CIT), also known as the Six-Item Orientation-Memory-Concentration Test or the Short Blessed Test

(named after its developer). It has been used in different settings such as primary care, secondary care and in research (O'Sullivan, O'Regan, & Timmons, 2016).

The test measures temporal orientation, attention/concentration and short-term memory. The six items include questions about the year, month, time of day, along with counting backwards from 20 to 1, reciting the months backwards and a memory phrase which includes first name, last name and an address (Katzman et al., 1983). These items

14 were chosen based on their correlation with the total score of the Blessed test. Katzman found that the orientation questions, year and month, proved valuable when differentiating normal subjects or subjects with mild cognitive impairment from subjects with severe cognitive impairment. Moderate cognitive impairment was best differentiated from severe cognitive impairment using a combination of the attention and memory questions, specifically the questions about the time of day and counting backwards from

20 to 1. The Memory phrase and saying the months backwards served to be useful when differentiating normal subjects from mildly impaired subjects (Katzman et al., 1983).

The test is administered by reading the questions to the subject in the category order of Orientation, Attention/Concentration and Memory (Appendix A: Study

Materials). Each question is scored as the patient answers the question. The total weighted error score for the whole test is 28. A score more than 10 is suggestive of a cognitive impairment. The 6-CIT was chosen particularly for this study to help rule out the possibility of dementia and other cognitive impairments. Compared to other similar tests such as Mini Mental State Exam (MMSE), the 6-CIT is simple, short and easy to administer. It is also a convenient test to be used in subjects that are visually impaired because no visual tasks are required to perform the test.

1.4: Overview of this project

Although the Teller Acuity Cards have opened avenues to test the vision of infants and uninstructable patients, it does not provide us with a full assessment of the visual function. Visual acuity measurements help with refraction and understanding a patient’s ability to resolve optotypes or detail, but are less useful for predicting the ability of a patient to detect common targets or perform daily tasks such as recognizing faces and common objects (Owsley & Sloane, 1987). Contrast sensitivity, on the other hand, can predict how individuals see targets of everyday life, and clinicians can use that information to better communicate with their patients the types of problems they may face with their daily activities. Our study took another step further in establishing the clinical utility of the Ohio Contrast Cards comparing it to tests that are currently used in clinic. We tested healthy older adults ages 65 and over, with no cognitive impairment, to expand the use of the Ohio Contrast Cards in a different population, and to form a baseline dataset of subjects that can be used in future comparisons to a similar age group of subjects with dementia.

Chapter 2: Methods

2.1: Power Analysis

A statistical power analysis was performed to estimate the sample size required to find a clinically significant effect of 0.15 log10 units, if it exists, with a probability of

0.80, in four comparisons. These were: in (a) test/retest on PR, (b) test/retest on OCC, (c)

1m vs. 3m on PR, (d) PR vs. OCC. This analysis required estimates of the standard deviation of the mean for PR and OCC. Based on data from published studies, the LogCS standard deviation of the PR for a healthy adult sample was reported to be 0.12, 0.11,

0.09 in the published studies by Elliott et al. (Elliott, Sanderson, & Conkey, 1990), Elliott and Bullimore (Elliott & Bullimore, 1993), and Dougherty et al. (Dougherty, Flom, &

Bullimore, 2005), respectively. We used a PR standard deviation of 0.15, just to be conservative.

The estimated number of required subjects for comparison (a) and (c) is N=16.

This was calculated by finding the standard deviation of difference which is equal to the

2 2 sqrt of (SD1 + SD2 ) as shown in Table 2.1.

Very limited data are readily available on the OCC. A Bland-Altman analysis in

Hopkins et al. compared their OCC data to their PR data, within subjects, obtained on low-vision adolescents. After removing the variability associated with their PR data, the standard deviation of their OCC LogCS data was 0.237. Thus, the estimated number of required subjects to obtain a power of 0.8 for comparison (b) is N = 40 (Table 2.1).

The standard deviation for PR was close to the standard deviation of the OCC based on the Hopkins study. One approach to estimate the sample size required to obtain a significant difference of 0.15 log units for comparison (d) is by finding the standard deviation of the difference between the two. If we assume the standard deviation of the

PR to be 0.15 and the standard deviation of the OCC to be 0.237, the standard deviation of their difference is estimated to be 0.2805. This results in an estimated N=28 (Table

2.1) to obtain a difference of 0.15, significant at p<0.05, with a statistical power of 0.8.

Due to the uncertainties in the standard deviation estimates of the OCC and anticipating the probability of needing to discard some data if a few subjects scored above 10 on the cognitive impairment test, we elected to proceed in a more conservative manner with our choice of N=50.

Table 2.1: Chosen Standard Deviations for power analysis Comparison SD1 SD2 SDdifference N (a) test/retest on PR 0.15 0.15 0.2121 16 (b) test/retest on OCC 0.237 0.237 0.3352 40 (c) 1m vs. 3m on PR 0.15 0.15 0.2121 16 (d) PR vs. OCC 0.15 0.237 0.2805 28 *number of participants required, based on statistical power analysis

2.2: Participants

The Ohio State University Primary Vision Care (PVC) participants over 65 years of age were identified prospectively from the PVC optometry clinic schedule. Patients were introduced to the study by phone when their appointment was set up. Those interested were followed up with more information via postal mail, email or telephone.

There were 51 total participants (31 female). Forty of the subjects were white, eight subjects were Black, and three subjects identified themselves as Asian. Subjects were ages 65 to 92 years (mean 72 years, SD 5.86). Informed consent was obtained before testing from cognitively competent participants. We did not assess cognitive impairment before testing to determine who can provide a consent vs. an assent. However, we obtained informed assent from all subjects who came in with a legally authorized representative and we asked their legally authorized representative to grant permission for further testing. Subjects received $10 cash and, a $2 sticker to validate their parking pass after participating. All documents used in the study can be viewed in Appendix A:

Study Materials. The protocol for the study was approved by the Ohio State University

Institutional Review Board and followed the tenets of the Declaration of Helsinki.

2.3: Visual Acuity Procedures

2.3.1: Letter acuity

The subjects’ acuity values were obtained from their clinic charts after their regular eye exams were over. Visual acuity was measured in Snellen units using the Clear

Chart® 4 Digital Acuity System, manufactured by AMETEK, and transformed into logMAR units to be consistent with the other units used.

2.3.2: Grating acuity

The Teller Acuity Cards, manufactured by Precision Vision in 2011, were presented once by the first examiner at a testing distance of 57cm. The cards were tested under the Descending Method of Limits. The subject was asked to point towards the grating, and the examiner judged from the subject’s looking and pointing behavior whether the grating was “seen” or not “seen”. The test ended when the subject was no longer able to see a grating. The examiner verified the subject’s acuity by re-examining the last “seen” card. The resultant visual acuity was the cy/cm (or cy/deg) of the finest grating that the examiner judged the subject could see.

2.4: Contrast Sensitivity Procedures

2.4.1: Letter Contrast

The Pelli-Robson Chart, manufactured by Precision Vision, was presented three times to the subject. It was presented twice at 1 meter by both the first and second examiners and once at 3 meters (or 0.5 m if visual acuity was worse than 6 cy/cm) by the first examiner. There was a total of three Pelli-Robson charts with different letters. The first examiner chose one chart randomly and tested the subject at either 1 meter or 3 meters (depending on the order, discussed below). Then, the first examiner chose another chart and tested the subject at the second testing distance (not tested previously). The

20 second examiner chose the last chart that was yet to be used and tested the subject at 1 meter. The illumination of the PR at 1 meter was typically 590 lux and the illumination at 3 meters was typically 489 lux. Scoring for all tests was letter-by-letter, where each letter counted for 0.05 log units in contrast. The test ended when the subject missed 2 out of 3 letters in a triplet.

2.4.2: Grating Contrast

The Ohio Contrast Cards were manufactured by Precision Vision, Woodstock IL

60098, USA. The testing procedure for the Ohio Contrast Cards was similar to the Teller

Acuity Cards procedure, with a testing distance of 57 cm. Unlike the Teller Acuity Cards, the Ohio Contrast Cards were presented twice, once by each examiner, using the

Descending Method of Limits from high contrast (highest being 85% contrast) to low contrast (lowest being 0.5% contrast). The examiner observed the subject’s looking behavior and judged whether the grating was “seen” or not “seen”. The last “seen” card determined the subject’s lowest contrast value or contrast threshold.

2.5: Mental Status Assessment

2.5.1: Six-Item Cognitive Impairment Test

Immediately after the vision testing, the Six-Item Cognitive Impairment Test was administered orally by the second examiner. A series of six questions were read in a fixed order and each were scored based on a weighted error score. An error score of more than

10 indicated an impairment. There were four patients who scored above 10. Thus,

21 indicating a cognitive impairment.

2.6: Randomization:

All testing procedures were randomized in advance using excel (Appendix A:

Study Materials). This included tester order, test order, and the order of the testing distance of the Pelli-Robson (PR) chart. Prior to examination, one eye was selected to be tested based on patient’s preference. The first tester was selected from a pre-generated randomization system. Each exam followed one of the sequences (Seq1, Seq2, Seq3,

Seq4) illustrated in Figure 2.1for the first tester (A, M, or T) and one of the sequences

(SeqA, SeqB) in Figure 2.1for the second tester (A, M, or T).

The examination began with the first tester measuring grating acuity or grating contrast sensitivity using the Teller Acuity Cards (TAC) or the Ohio Contrast Cards

(OCC), respectively. The first tester then randomly chose a card from the deck, thereby selecting the start card. The same process then followed with the previously non-selected test. Subsequently, letter contrast sensitivity was measured using the Pelli-Robson chart at either 1m or 3m (0.5m for those with visual acuity worse than 6cy/cm) first. PR

Contrast sensitivity measurements were taken again at the second distance. After completion of the first tester’s duties, the second tester measured contrast sensitivity using the OCC and the PR chart. The order in which each test was administered followed

SeqA or SeqB as shown in Figure 2.1. The second tester concluded the testing session by administering the 6-Item Cognitive Impairment Test and recording the results based on a weighted error score. 22

Below is an example of subjects 3’s testing order following Seq 3 with M as the first tester and SeqA with T as the second tester:

Subject 3 is a 66 year-old Caucasian female

Tester M first administered the visual acuity cards selecting a random start card of

0.43 and continued until a threshold was reached. Then, she administered the

contrast sensitivity cards with a start card of 32. Next, she tested the Pelli-Robson

chart, first at 3m and then at 1m, choosing a chart with different letters at each

test. Tester T then administered first the Pelli-Robson chart at 1m then the Ohio

Contrast Cards with a start card of 0.64. The examination was concluded with the

6-Item Cognitive impairment test, on which the subject performed with a

weighted error score of 2.

Figure 2.1: Randomization Sequences

Chapter 3: Analysis

We used the Bland-Altman method to measure the repeatability and agreement between two clinical tests. This was done by calculating the mean difference between two administrations of the same test and two methods of measurement (OCC vs. PR) and determining the 95% limits of agreement, 1.96 standard deviation (SD). Bland et al.

(Bland & Altman, 1986) demonstrated this method to be better than the correlation coefficient when comparing a new clinical test to an established one. The 95% LoA judges how well two tests agree. The smaller the difference between two LoA, the better the agreement and more repeatable the test. We defined a clinically significant difference to be more than 0.15 log10 units. This is the difference in contrast between groups of three letters on the PR chart and the difference in contrast between each card on the OCC.

Chapter 4: Results

All 51 participants completed every test successfully. All but four of the participants scored within normal limits on the mental status test, with one of those (S17) having an extreme value on the mental status test. Those four participants will be eliminated from the main analysis (power analysis indicate N = 40). All subjects tested by tester A (N = 5) will also be removed from the main analysis due to insufficient data to be compared with the other two testers, M and T. One of A’s subjects did not score within the normal limits on the 6-CIT test, so this left us with 43 participants’ data available for analysis; N = 43 is greater than N = 40 which is the minimum number of subjects required for statistical power.

4.1: Pelli-Robson and Ohio Contrast Cards Performance

Overall, the two contrast sensitivity tests (OCC & PR) yielded comparable results regardless of whether they were presented first or second and regardless of tester (M,T) as shown in Table 4.1.

Table 4.1: Average contrast sensitivity scores for each test (PR1m, OCC) by each tester ± standard deviation (N) Test-Tester First Test Second Test PR-M 1.5613 ± 0.231 (23) 1.645 ± 0.161 (20) PR-T 1.590 ± 0.133 (20) 1.498 ± 0.208 (23) OCC-M 1.909 ± 0.179 (23) 2.022 ± 0.055 (20) OCC-T 2.023 ± 0.139 (20) 1.987 ± 0.234 (23) *Every observation occurs in this table exactly once

A three-way repeated measures ANOVA was run to understand the effects of test type, tester, and order of testers on contrast sensitivity (Table 4.2). Our results yielded a significant overall effect of test type, p <0.005, in favor of the OCC (Figure 4.1), where

OCC gave a higher average LogCS score, regardless of tester. The results on the PR1m and OCC tests were correlated as shown in Figure 4.2. There was no statistically significant three-way interaction between test type, tester and order of testers (p = 0.176).

There was a statistically significant two-way interaction between test type and tester

F(1,41) = 9.89, p = 0.003, which was trivial because it was not clinically significant, being less than 0.15 log10 units Table 4.3, which is less than a card difference for OCC and a group of triplets for the PR chart. The mean CS difference between OCC and

PR1m was similar for each tester. There was no statistically significant interaction between test-type x order, F(1,41) = 0.169, p = 0.683, and tester x order F(1,41) = 1.751, p = 0.193 (Table 4.2).

Figure 4.1: Average contrast sensitivity scores (log10 Michelson contrast sensitivity) for each test by each tester ± standard error

Table 4.2: Three-way repeated measures ANOVA Interaction df Mean F P value square TestType 1 7.256 608.058 <0.005 TestType x Order 1 0.002 0.169 0.683 Tests of Tester 1 0.004 0.610 0.439 Within-Subjects Tester x Order 1 0.013 1.751 0.193 TestType x Tester 1 0.103 9.888 0.003 TestType x Tester x 1 0.02 1.896 0.176 Order Tests of Order 1 0.281 2.829 0.100 Between-Subjects *Three-way repeated measures ANOVA was calculated to measure the significance and interaction of TestType (PR1m, OCC), Tester (M,T) and Order of testers.

Table 4.3: Mean difference and standard deviation between PR1m and OCC for each tester. Tester Mean difference between Standard deviation PR1m & OCC Tester M 0.363 log units 0.170 10 Tester T 0.461 log units 0.125 10 Difference 0.098 log units - 10 *The difference between testers =0.098 log10 unit difference (<0.15 log unit clinical significance).

4.2: Test-Retest Reliability

The OCC and PR1m were each administered twice, once by each tester. The differences between the CS scores, shown in Figure 4.3, demonstrate the repeatability of each test. Table 4.4 summarizes the repeatability of the PR1m and OCC. The repeatability of the PR1m and OCC was overall similar with 95% LoA of ± 0.28 log units and 95% LoA of ± 0.27 log units, respectively.

Table 4.4: Average difference, standard deviation of the difference, and limit of agreement indicating the test-retest reliability PR1m OCC Mean difference 0.022 0.041 Standard deviation of difference 0.144 0.136 Limit of Agreement ±0.282 ±0.266

It is important to keep in mind that the order of each test (PR and OCC) in Figure

4.3 is confounded within tester (T vs. M) for each subject. In other words, each subject was administered the first test (PR and OCC) by either tester T or tester M. There was no significant difference between the results of the first administration of the PR1m and second administration of PR1m, with a mean difference of 0.022 and standard error of the mean of the difference of 0.022 and t(42) =1.016, p = 0.315. However, the first and second administration of the OCC resulted in a standard error of the mean difference of

0.021 and t(42) = 2.001, p = 0.050. Again, this difference between the results of the two administrations of the OCC was trivial.

Because the first tester was always the same for each subject, a separate statistical analysis was indicated to evaluate the significance of the difference between first and second tests. We ran t-tests to evaluate the difference between the first and second administration of the OCC for each first tester (M or T) separately. Figure 4.4 shows

Bland-Altmann plots of test-retest data for tester M administrating the first OCC test, t(23) = 3.117, p =0.005, and tester T administrating the first OCC, t(18) = 0.004, p =

0.997. There was also statistically significant difference in test-retest of OCC when administered by tester M as the first tester, compared to when tester T was the first tester.

However, as shown in Table 4.5, the difference between first and second administration of OCC, when tester M was the first tester, was less than 0.15 log10 units (difference =

0.0743 log10 units), and was not considered to be clinically significant.

Figure 4.3: Bland-Altman plots of test-retest data for two contrast sensitivity tests. Difference between first and second administration of each test as a function of their average. All tests were Log10 Michelson units. Solid line: average difference. Dashed lines: ± 1.96 x SDdifference. A. Pelli-Robson Chart, B. Ohio Contrast Cards. Red data points: participants with cognitive impairment; Blue data points: participants tested by tester A

Table 4.5: Mean LogCS of OCC for first test by tester M and second test by tester T. Tester Mean OCC Standard deviation

Tester M (first test) 1.913 log10 units 0.176

Tester T (second test) 1.987 log10 units 0.229

Difference 0.0743 log10 units -

*The difference between first and second tests = 0.0743 log10 units (<0.15 log10 unit clinical significance)

Figure 4.4: Bland-Altman plots of test-retest of OCC. A. Tester M as the first tester, B. Tester T as the first tester. Difference between first and second administration as a function of their average. All tests were Log10 Michelson units. Solid line: average difference. Dashed lines: ± 1.96 x SDdifference. Red data points: participants with cognitive impairment; Blue data points: participants tested by tester A

4.3: Testing Distance of PR

Hopkins et al suggested that there might be an effect of testing distance using the

Pelli-Robson chart. In the present study, the testing distance of the PR was evaluated at

1m and 3m. Two patients (S13 and S42) were evaluated at 0.5 meter instead of 3 meters due to having a visual acuity worse than 6 cy/cm. These subjects were eliminated from this analysis because of insufficient data to compare to the 1 meter and 3 meters distances. Based on our analysis, there was no significant effect of testing distance (p =

0.499), and no significant interaction between Distance and Tester p = (0.060) as shown in Table 4.6. The average CS scores for each testing distance is shown in Figure 4.5.

Figure 4.5: Average Log10 contrast threshold scores for Pelli-Robson at a distance of 1 meter and 3 meters

Table 4.6: Mixed ANOVA was calculated to measure the significance of PR distance (1m vs. 3m) and interaction between Distance and Tester (M vs. T) Interaction df F Sig Tester 82 2.114 0.150 Distance 82 0.461 0.499 Tester x distance 82 3.642 0.060

4.4: Contrast Sensitivity vs. Visual Acuity

Linear regression analyses were run to assess the relationship between grating contrast sensitivity vs. grating visual acuity, and between letter contrast sensitivity vs. letter visual acuity. R values are summarized in Table 4.7. There was strong, statistically significant, positive correlation between grating contrast sensitivity (OCC) and grating

32 visual acuity (TAC), r = 0.636, p < 0.005 (Figure 4.6A). There was also a strong, statistically significant, positive correlation between letter contrast sensitivity (PR) and letter visual acuity (Clear Chart), r = 0.650, p < 0.005 (Figure 4.6B). However, the slopes of each of those lines was less than 1.0 on log-log coordinates (compare regression lines to the unit slopes in Figure 4.6), indicating that the association is not linear.

Figure 4.6: Comparison between visual acuity and contrast threshold. Red data points: participants with cognitive impairment. Blue data points: participants tested by tester A. Triangle: outlier.

4.5: Gratings vs. Letters

The relationships between grating contrast sensitivity vs. letter contrast sensitivity and between grating visual acuity vs. letter visual acuity were computed using linear regression analyses (Table 4.7). As shown in Figure 4.7A, there is a strong, statistically significant, positive correlation between grating contrast sensitivity (OCC) and letter contrast sensitivity (PR), r = 0.649, p < 0.005. The relationship between grating visual acuity (TAC) and letter visual acuity (Clear Chart) is illustrated in Figure 4.7B, demonstrating a moderate, statistically significant, positive correlation, r = 0.451, p

<0.005.

Figure 4.7: Comparison between grating and letter performance. Red data points: participants with cognitive impairment, Blue data points: participants tested by tester A. Triangle: outlier.

Table 4.7: Correlation between all four tests (Clear Chart, Teller, PR1m, OCC) Test Type Clear Chart Teller PR1m OCC Clear Chart 1 0.451 0.650 0.621 Teller 0.451 1 0.297 0.636 PR1m 0.650 0.297 1 0.649 OCC 0.621 0.636 0.649 1 *Highlighted brackets emphasize the corresponding figures above. All interactions show a highly statistically significant correlation of p < 0.005

4.6: Cognitive impairment Test

The 6-Item Cognitive Impairment Test was completed by each subject. This is particularly important for our project because we are interested in an overall healthy elderly population and would like to use the results of this study to compare to patients with cognitive impairment, mainly Dementia, in future projects. Four subjects had an error score of more than 10, indicating a cognitive impairment as shown on Table 4.8.

Vision results on these four subjects were not included in our analyses but their data points have been added as red squares in all our analyses. Linear regression analyses were run to determine the presence of an association between cognitive impairment test scores and age vs. our four tests (PR, OCC, TAC, Clear Chart). As shown in Table 4.9, there is no statistically significant association between cognitive impairment scores and the results of any of our four visual tests.

Table 4.8: 6-Item Cognitive Impairment Test – Error scores greater than 10 Subject Age (yrs) 6-CIT Score 1 78 14 6 92 11 16 68 12 17 78 21

Table 4.9: Linear Regression analyses to determine association between cognitive testing score and age vs. four visual tests (PR, OCC, TAC, Clear Chart) Cognitive testing score Age Pelli-Robosn Chart t(42) = 0.952, p = 0.347 t(42) = 0.147, p = 0.884 Ohio Contrast Cards t(42) = 1.108, p = 0.275 t(42) = 0.801, p = 0.428 Teller Acuity Cards t(42) = 0.414, p = 0.681 t(42) = 0.510, p = 0.613 Clear Chart t(42) = 0.488, p =0.628 t(42) = 0.992, p = 0.327

Chapter 5: Discussion

5.1: Test-Retest Reliability of the OCC and PR chart

In this project, we evaluated the test-retest reliability of the Ohio Contrast Cards and Pelli-Robson chart and compared the results of the two tests. The OCC demonstrated comparable test-retest repeatability to the PR test at 1 meter, and showed good Limits of

Agreement: ± 0.28 log units and ± 0.27 log units, respectively. In fact, the OCC displayed higher contrast sensitivity values than the PR chart. As shown in Figure 4.2, most data points fell below the solid equality line with a slope of 1. This indicated that the OCC revealed better contrast sensitivity values compared to the PR. In other words,

PR might not capture the full contrast abilities of a patient. These results suggest that

OCC may be a useful alternative for testing contrast sensitivity in both a clinical and a research setting.

5.2: Testing Distance of the Pelli-Robson Chart

Pelli and his colleagues suggested a testing distance of 3 meters (Pelli & Robson,

1988), the distance at which the size of the letters on the chart subtend 0.5 degrees. Work by Hopkins et al. found a statistically significant association between PR testing distance and the Bailey-Lovie logMAR acuity of a patient. They suggested the best testing distance in meters of the PR chart should be approximately distance in meters = 1.5 –

LogMAR acuity (Hopkins et al., 2017). We obtained contrast sensitivity values at 1 meter and 3 meters and our result show no significant effect of testing distance, p value of

0.634. As demonstrated in Figure 4.5, the average contrast sensitivity values for the

37 testing distance at 1 meter is 1.611 log units and at 3 meters is 1.586. The difference in the results between Hopkins’ data and our data can be attributed to the difference in the patient population examined, low vision population compared to an overall healthy elderly population.

5.3: Contrast Sensitivity vs. Visual Acuity

Each patient’s contrast threshold was compared to their visual acuity. The contrast sensitivity tests were significantly correlated with their corresponding visual acuity tests

(Figure 4.6), dotted line with a slope of 1 indicates the proportional performance. As illustrated in Figure 4.6A and Figure 4.6B, some patients may have good visual acuity, but their contrast sensitivity may be reduced. For example, Figure 4.6B shows 27 patients with a Clear Chart visual acuity of 0.0 LogMAR or 20/20 Snellen acuity, yet these patients exhibit a wide range of PR contrast threshold values that expand from 1.425 to

1.85 Log10 units. This range of contrast sensitivity is a difference of about 8 to 9 letters on the Pelli-Robson chart or as defined by Leat et al, it may be a difference between normal vision and visual impairment, <1.5 contrast sensitivity (Leat, Legge, &

Bullimore, 1999). This serves as a great reminder that each test examines a separate visual function and that a patient’s full visual system cannot be assessed correctly with one test rather than the other.

5.4: Grating vs. Letter

The level of function revealed by two grating tests (OCC and TAC) was compared to the level shown by two letter tests (PR and Clear Chart). The contrast sensitivity grating test (OCC) has shown better performance than the corresponding letter contrast sensitivity test (PR) (Figure 4.7A). All patients had a higher mean contrast threshold when tested with the OCC compared to the PR, indicating greater contrast sensitivity revealed by the grating test. We also evaluated the level of function of the grating visual acuity (TAC) test and compared it to letter visual acuity (Clear Chart) as shown in Figure 4.7B. Our results did not show better performance of the grating visual acuity test compared to letter visual acuity test. Most of the data fell above the equality line indicating worse performance of the Teller Acuity Cards compared to the Clear

Chart (Figure 4.7B). A similar result was shown in Friedman, fig 1 (Friedman et al.,

2002). They found that grating and letter acuity tests show agreement for acuities of 0.8 logMAR and better, worse acuities demonstrated better performance with the grating test.

A few studies have demonstrated results contrary to these, but these studies did not evaluate healthy elderly patients. A study by Bittner et al. compared letter visual acuity measured by ETDRS (Early Treatment Diabetic Retinopathy Study) chart to grating visual acuity using a Liquid Crystal Display screen on patients with severe vision loss

(Bittner, Jeter, & Dagnelie, 2011). They concluded that the grating acuity test measured equal or higher visual acuity compared to letter acuity. A more recent study by Hopkins et al., has also demonstrated better visual performance using a grating test, Teller Acuity

Cards, compared to the corresponding letter chart, Bailey-Lovie letter chart, in low vision adolescents (Hopkins et al., 2017).

5.5: Cognitive test results:

We assessed cognitive impairment using the 6- Item Cognitive Impairment Test.

We did not analyze the results of the four subjects who had an error score of greater than

10, indicating cognitive impairment. There was no problem testing these patients. Their results were similar to the rest of the data set and appear as red squares on all graphs.

This suggests that the tests can be used on these patients successfully.

5.6: Future work

Our study consisted of a healthy elderly (n = 43), ages 65 and older, population.

We chose a healthy elderly population to form a baseline dataset of patients for future work on a similar age group of patients with dementia. Work by Freidman and his colleagues (Friedman et al., 2002), has demonstrated the importance of a grating visual acuity test on an elderly population with cognitive impairment. In that study, Teller

Acuity Cards were effective in testing cognitively impaired patients who were, otherwise, unable to be tested using conventional recognition acuity tests. We hope future work with the Ohio Contrast Cards will have similarly successful performance as the TAC and we hope the additional information on contrast sensitivity completes the full picture of a patient’s visual function, ultimately allowing for comprehensive vison management and improving the lives of our senior citizens.

Appendix A: Study Materials

References:

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O'Sullivan, D., O'Regan, N. A., & Timmons, S. (2016). Validity and Reliability of the 6- Item Cognitive Impairment Test for Screening Cognitive Impairment: A Review. Dement Geriatr Cogn Disord, 42(1-2), 42-49. doi:10.1159/000448241 Owsley, C., & Sloane, M. E. (1987). Contrast sensitivity, acuity, and the perception of'real-world'targets. British Journal of Ophthalmology, 71(10), 791-796. Retrieved from https://bjo.bmj.com/content/bjophthalmol/71/10/791.full.pdf Pelli, D., & Robson, J. (1988). The design of a new letter chart for measuring contrast sensitivity. Paper presented at the Clinical Vision Sciences. Reichert. (2019). ClearChart(R) 4/4X/AcuityCheck In AMETEK Inc. (pp. 48). Wolkstein, M., Atkin, A., & Bodis-Wollner, I. (1980). Contrast sensitivity in retinal disease. Ophthalmology, 87(11), 1140-1149. doi:10.1016/s0161-6420(80)35112-9 Young, G. (1918). Threshold tests. The British journal of ophthalmology, 2(7), 384. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC513515/pdf/brjopthal01011- 0032.pdf