Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Feb 17;11(2):62.
doi: 10.3390/jimaging11020062.

Non-Hospitalized Long COVID Patients Exhibit Reduced Retinal Capillary Perfusion: A Prospective Cohort Study

Clayton E Lyons  1 , Jonathan Alhalel  1   2 , Anna Busza  1 , Emily Suen  1 , Nathan Gill  3 , Nicole Decker  1 , Stephen Suchy  4 , Zachary Orban  4 , Millenia Jimenez  4 , Gina Perez Giraldo  4 , Igor J Koralnik  4 , Manjot K Gill  1
Affiliations

Non-Hospitalized Long COVID Patients Exhibit Reduced Retinal Capillary Perfusion: A Prospective Cohort Study

Clayton E Lyons et al. J Imaging. .

Abstract

The mechanism of post-acute sequelae of SARS-CoV-2 (PASC) is unknown. Using optical coherence tomography angiography (OCT-A), we compared retinal foveal avascular zone (FAZ), vessel density (VD), and vessel length density (VLD) in non-hospitalized Neuro-PASC patients with those in healthy controls in an effort to elucidate the mechanism underlying this debilitating condition. Neuro-PASC patients with a positive SARS-CoV-2 test and neurological symptoms lasting ≥6 weeks were included. Those with prior COVID-19 hospitalization were excluded. Subjects underwent OCT-A with segmentation of the full retinal slab into the superficial (SCP) and deep (DCP) capillary plexus. The FAZ was manually delineated on the full slab in ImageJ. An ImageJ macro was used to measure VD and VLD. OCT-A variables were analyzed using linear mixed-effects models with fixed effects for Neuro-PASC, age, and sex, and a random effect for patient to account for measurements from both eyes. The coefficient of Neuro-PASC status was used to determine statistical significance; p-values were adjusted using the Benjamani-Hochberg procedure. Neuro-PASC patients (N = 30; 60 eyes) exhibited a statistically significant (p = 0.005) reduction in DCP VLD compared to healthy controls (N = 44; 80 eyes). The sole reduction in DCP VLD in Neuro-PASC may suggest preferential involvement of the smallest blood vessels.

Keywords: long COVID; optical coherence tomography angiography (OCT-A); retina; vessel density (VD); vessel length density (VLD).

PubMed Disclaimer

Conflict of interest statement

Manjot K. Gill is a consultant for Genentech-Roche and Regeneron. Igor J. Koralnik is a consultant for Gilead Sciences and Biogen. No conflicting relationship exists for any other author. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Optical coherence tomography angiography (OCT-A) image processing in Image J. (A) Original image of superficial capillary plexus (SCP) slab prior to processing. (B) Resulting large vessel mask after binarization with maximum entropy plug-in. (C) Binarized SCP slab used to calculate vessel density (VD) with the removed large vessels. (D) Final binarized and skeletonized SCP slab used to calculate vessel length density (VLD) with removal of the large vessels.
Figure 2
Figure 2
Quality of life and cognitive function results in non-hospitalized post-acute sequelae SARS-CoV-2 infection (PASC) patients with predominantly neurologic symptoms. Neuro-PASC patients exhibited a broad reduction in quality of life compared to a US normative population and significantly worse cognitive function in attention only. * p < 0.05.
Figure 3
Figure 3
Deep capillary plexus (DCP) VLD in Neuro-PASC patients versus healthy controls. A box plot showing the difference in DCP VLD between healthy controls and Neuro-PASC patients.
See this image and copyright information in PMC

References

    1. Sudre C.H., Murray B., Varsavsky T., Graham M.S., Penfold R.S., Bowyer R.C., Pujol J.C., Klaser K., Antonelli M., Canas L.S., et al. Attributes and predictors of long COVID. Nat. Med. 2021;27:626–631. doi: 10.1038/s41591-021-01292-y. - DOI - PMC - PubMed
    1. Davis H.E., McCorkell L., Vogel J.M., Topol E.J. Long COVID: Major findings, mechanisms and recommendations. Nat. Rev. Microbiol. 2023;21:133–146. doi: 10.1038/s41579-022-00846-2. - DOI - PMC - PubMed
    1. National Center for Health Statistics. USA Census Bureau, Household Pulse Survey, 2022–2023. Long COVID. Generated Interactively. [(accessed on 18 November 2024)]; Available online: https://www.cdc.gov/nchs/covid19/pulse/long-covid.htm.
    1. Bach K. New Data Shows Long COVID Is Keeping as Many as 4 Million People out of Work. Brookings. [(accessed on 19 May 2023)]. Available online: https://www.brookings.edu/research/new-data-shows-long-COVID-is-keeping-...
    1. Roberts K.A., Colley L., Agbaedeng T.A., Ellison-Hughes G.M., Ross M.D. Vascular Manifestations of COVID-19—Thromboembolism and Microvascular Dysfunction. Front. Cardiovasc. Med. 2020;7:598400. doi: 10.3389/fcvm.2020.598400. - DOI - PMC - PubMed

LinkOut - more resources