June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Assessment of Optical Coherence Tomography Findings Based on COVID-19 Status and Demographics
Author Affiliations & Notes
  • Nilesh Raval
    Department of Ophthalmology and Visual Sciences, Montefiore Medical Center, Bronx, New York, United States
  • Yael Steinberg
    Albert Einstein College of Medicine, Bronx, New York, United States
  • Irene Rusu Jutagir
    Surgery (Ophthalmology), Jacobi Medical Center, Bronx, New York, United States
    Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, New York, United States
  • Mariel Messilaty
    Surgery (Ophthalmology), Jacobi Medical Center, Bronx, New York, United States
  • Afshin Parsikia
    Department of Research Services, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • JOYCE NANJINGA MBEKEANI
    Surgery (Ophthalmology), Jacobi Medical Center, Bronx, New York, United States
    Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, New York, United States
  • Footnotes
    Commercial Relationships   Nilesh Raval None; Yael Steinberg None; Irene Rusu Jutagir None; Mariel Messilaty None; Afshin Parsikia None; JOYCE MBEKEANI None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 1001 – F0248. doi:
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      Nilesh Raval, Yael Steinberg, Irene Rusu Jutagir, Mariel Messilaty, Afshin Parsikia, JOYCE NANJINGA MBEKEANI; Assessment of Optical Coherence Tomography Findings Based on COVID-19 Status and Demographics. Invest. Ophthalmol. Vis. Sci. 2022;63(7):1001 – F0248.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The full scope of ophthalmic manifestations of coronavirus disease 2019 (COVID-19) has yet to be appreciated. We used optical coherence tomography (OCT) to compare subjects with a history of COVID-19 disease and those without evidence of past disease across qualitative and quantitative metrics.

Methods : Subjects diagnosed by reverse-transcriptase polymerase chain reaction with COVID-19 or presence of SARS-CoV-2 antibodies (N=25) and those with no history or antibody evidence of disease (N=25) were prospectively assessed using a Zeiss Cirrus HD OCT Model 5000. Retinal nerve fiber layer (RNFL), macular ganglion cell complex (GCC), and foveal thickness were tabulated. Retinal structural findings were evaluated by a retina specialist. Results were stratified by age, race, ethnicity, gender, and presence of comorbidities (diabetes and hypertension). Student’s t-test, linear and logistic regression, univariate analysis with COVID+ subjects, and multivariate analysis with all subjects were performed. Significance was set at p<0.05.

Results : COVID+ subjects did not show significant differences compared to COVID– subjects across any parameters. There were significant differences across demographic groups. Univariate analysis showed that COVID+ Asians had thinner RNFL (p=0.014, right; p=0.018, left) and GCC (p=0.041, right; p=0.051, left) than COVID+ Blacks and Whites. COVID+ Hispanics had decreased foveal thickness compared to COVID+ non-Hispanics (p=0.019, right; p=0.004, left). Multivariate analysis confirmed that Blacks (p=0.015, left) and Whites (p=0.010, left) had thicker GCC than Asians and that Hispanics had decreased foveal thickness (p=0.041, left) compared to non-Hispanics. The middle age group had thinner GCC (p=0.022, right; p=0.024, left) than the youngest age group. While COVID+ Blacks were more likely to have retinal structural changes than COVID+ subjects of other races with a trend toward significance (OR=5.00, p=0.084), multivariate analysis did not confirm this disparity.

Conclusions : Analysis of this cohort did not reveal significant differences between COVID+ and COVID– individuals. However, comparison of demographic parameters did show significant differences across age, race, and ethnicity. The reasons for these disparities are obscure. Further studies with a greater number of subjects may reveal differences based on COVID-19 status.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

 

 

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