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Abstract

Objective

To evaluate longitudinal changes in peripapillary vessel density (VD) following coronavirus disease 2019 (COVID-19) using optical coherence tomography angiography.

Methods

As part of a prospective longitudinal observational study, we studied healthy individuals with a history of mild COVID-19 confirmed via real-time polymerase chain reaction. After recovery, we used the Optovue RTVue XR Avanti machine to perform optic nerve head (ONH) imaging. We also assessed the VD of all vessels and of small vessels in the disc and the radial peripapillary capillary (RPC) network at 1 and 3 months post-recovery.

Results

We included 17 patients (34 eyes; mean age: 36.9 ± 10.2 years, range: 24–62 years) who had recovered from COVID-19. No changes were observed in the ONH parameters. However, there was a noticeable trend of increased small vessel VD values in the RPC. These increases were significant for the peripapillary whole, superior hemifield, inferior-temporal, temporal-superior, and superior-temporal small vessels. Moreover, the evaluation of all vessel VD values in the RPC revealed a significant decrease in the inside disc and a significant increase in a grid-based inferior region.

Conclusion

COVID-19 may affect VD of the RPC in the ONH, and should be considered in ONH evaluations.

Keywords

Optic nerve head optical coherence tomography angiography coronavirus disease 2019 vessel density COVID-19 radial peripapillary capillary network

Introduction

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the most recent member of the Coronaviridae family, emerged in China.^1–3 It was initially believed to cause a respiratory disease affecting only the lower respiratory tract and leading to viral pneumonia, with symptoms such as fever, dry cough, anorexia, fatigue, and myalgia.⁴ However, further studies have revealed that it can also affect other body parts, including the vascular system, leading to issues such as changes in retinal microvasculature.^5,6 Although its respiratory symptoms have been extensively studied, more research is needed to understand its effects on other part of the body.^7,8

The SARS-CoV-2 virus enters cells by attaching to angiotensin-converting enzyme-2 (ACE2), its primary receptor.^9–11 ACE2 receptors are present in various cells throughout the body, such as small intestine enterocytes, type II alveolar cells, vascular endothelium, and glial cells of the central nervous system.^12,13 They are also expressed in different types of cells in the retina, including photoreceptors, vascular endothelium, ganglion cells, and Müller cells. This may explain why coronaviruses can cause eye problems.¹⁴ Most of the reported ocular manifestations of coronavirus are related to the ocular surface, such as conjunctivitis, chemosis, conjunctival congestion, conjunctival follicles, and discharge.^15,16 Regarding posterior segment involvement, Marinho et al. first reported changes in retinal microvasculature that lead to micro-hemorrhage and cotton wool spots.¹⁷ Subsequent studies confirmed these findings and described retinal involvement, including decreased retinal microvascular vessel density (VD), uveitis, other vascular abnormalities, and neuro-ophthalmic disorders.^18,19

Previous studies have demonstrated that patients with coronavirus disease 2019 (COVID-19) experience decreased macular VD in the superficial and deep capillary plexuses of the retina.²⁰ Furthermore, our previous cross-sectional report revealed that recovered COVID-19 patients have optic nerve head (ONH) VD alterations.²¹ Specifically, we identified a decrease in radial peripapillary capillary (RPC) VD in all vessels (AV) and in small vessels (SV) compared with healthy individuals.

In the present longitudinal study, we aimed to evaluate the changes in RPC VD over 3 months following COVID-19 using optical coherence tomography angiography (OCTA).

Methods

Study participants

The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.²² All participants in this prospective longitudinal observational study with a 3-month duration were nurses or physicians who worked at the Khatam Eye Hospital, the main ophthalmology center of Mashhad University of Medical Sciences, Mashhad, Iran. Each participant had confirmed mild COVID-19 (COVID-19 symptoms without shortness of breath or abnormal chest imaging based on the National Institutes of Health COVID-19 Treatment Guidelines) through a real-time reverse transcription polymerase chain reaction nasopharyngeal swab test, and had been recovered from their symptoms for at least 1 week. In addition, all participants were outpatients and provided detailed systemic and ocular histories. Moreover, they consented to undergo a complete ophthalmological evaluation and ONH OCTA imaging at their initial visit, followed by two subsequent visits (at 1 and 3 months after symptom remission).

The study excluded individuals with current pregnancy or breastfeeding; clinically apparent retinal or choroidal disease; a history of diabetes mellitus, migraine, auto-immune diseases, glaucoma, or refractive or intraocular surgery; ONH abnormalities or anomalies such as myelinated nerve fiber layer, tilted disc, peripapillary atrophy, ONH drusen, small crowded disc, or large disc; a high intraocular pressure; best-corrected visual acuity less than 20/20; a spherical refractive error greater than five diopters; or a cylindrical refractive error greater than two diopters. Refraction was measured using a KR-1 Auto Kerato-Refractometer (Topcon Medical Systems, Inc., Tokyo, Japan). Patients who had received corticosteroid therapy or had been hospitalized for COVID-19 were also excluded. In addition, the study did not include patients with ocular media opacity (such as corneal haziness or cataracts) that would prevent high-quality imaging or result in an OCTA scan quality index lower than 7/10. None of the patients had received the COVID-19 vaccine prior to the study.

Ethical considerations

The study protocol adhered to the principles of the Declaration of Helsinki. All participants provided written informed consent prior to registration, and the ethical aspects of the research were approved by the Committee of Ethics in Human Research at Mashhad University of Medical Sciences (approval number: IR.MUMS.MEDICAL.REC.1399.402).

Imaging technique

The OCTA scans were performed using an AngioVue device (RTVue XR Avanti, Optovue, Fremont, CA, USA; software version 2018.0.0.14), which has an A-scan-rate of 70,000 scans/s. The images were assessed to determine the degree of image decorrelation by repeating each B-scan line. Optic disc cubes and AngioDisc 4.5- × 4.5-mm HD scan (400 lines × 400 A-scans) protocols were used to examine the vertical and horizontal orthogonal orientations. Automated default segmentation with the preset sets for the RPC network was used to obtain all measurements (Figure 1). All regions were defined by the Optovue OCTA system. Furthermore, the 3D Projection Artifact Removal by OCT 3D volume set was used. All images were centered on the optic disc and had a scan quality index of at least 7/10. All images were checked for segmentation errors and artifacts by the first author. Images with unfavorable grades or artifacts were discarded and reacquired. Imaging was conducted at all three visits using the same machine and the same operator, and all imaging occurred between 11:00 a.m. and 2:00 p.m. to avoid diurnal oscillations of VD. Participants who did not complete the follow-up visits were excluded from the study.

Figure 1.

Examples of the 4.5- × 4.5-mm OCTA image segmentation pattern ONH subfields. (a) ONH subfields with all vessels and small vessels at the level of the RPC network. The numbers represent the vessel densities of all vessels in different regions of the RPC network. (b) Segmentation slabs of the ONH on a B-Scan image. The red line represents the inner border of the RNFL (the internal limiting membrane). The green lines represent the outer border of the RNFL (the border between RNFL and the ganglion cell layer) and (c) en-face angiogram at the level of the RPC network. OCTA, optical coherence tomography angiography; ONH, optic nerve head; RNFL, retinal nerve fiber layer; RPC, retinal peripapillary capillary.

Statistical analysis

Statistical analysis was performed using SPSS for Windows, Version 16.0 (SPSS Inc., Chicago, IL, USA). Descriptive statistics are used to present the data, including the mean ± standard deviation and range. The normal distribution of variables was evaluated using the Shapiro–Wilk test, and Levene’s test was used to assess normality properties and the homogeneity of variances. Generalized estimating equation analysis was performed to compare differences within the study group, and analysis of variance was used to compare mean values between visits. We considered a p-value of 0.05 to be significant.

Results

In the current investigation, 17 participants contributed a total of 34 eyes. The mean age of participants was 36.9 ± 10.2 years, ranging from 24 to 62 years old. None of the patients had a history of hospitalization, intensive care unit admission, or corticosteroid therapy. All ONH parameters, such as the cup disc area, cup volume, and peripapillary retinal nerve fiber layer thickness, remained unchanged over the study period (Table 1).

Table 1.

Optic nerve head parameters of COVID-19 patients within the study period

	Baseline, mean ± SD (range)	Month 1, mean ± SD (range)	Month 3, mean ± SD (range)	p-Value
Cup/disc area ratio	0.14 ± 0.12 (0.0–0.4)	0.12 ± 0.13 (0.0–0.5)	0.13 ± 0.12 (0.0–0.4)	0.39
Cup/disc vertical ratio	0.32 ± 0.23 (0–0.77)	0.28 ± 0.26 (0.0–0.77)	0.31 ± 0.24 (0.0–0.78)	0.31
Cup/disc horizontal ratio	0.28 ± 0.2 (0–0.63)	0.25 ± 0.22 (0.0–0.65)	0.28 ± 0.2 (0.0–0.64)	0.96
Rim area	1.6 ± 0.23 (0.8–2.04)	1.6 ± 0.24 (0.7–1.92)	1.6 ± 0.23 (0.79–2.04)	0.53
Disc area	1.9 ± 0.28 (1.4–2.5)	1.9 ± 0.3 (1.4–2.6)	1.9 ± 0.3 (1.4 ± 2.6)	0.84
Cup volume	0.04 ± 0.05 (0–0.24)	0.04 ± 0.05 (0–0.25)	0.04 ± 0.05 (0–0.25)	0.85
Peripapillary RNFL	106.9 ± 11.05 (81.0–128.0)	105.6 ± 11.7 (81.0–127.0)	106.0 ± 11.1 (80.0–128.0)	0.08

COVID-19, coronavirus disease 2019; RNFL, retinal nerve fiber layer; SD, standard deviation.

There was a significant increase in peripapillary whole VD in the RPC network, from 52.1% ± 2.9% at baseline to 53.1% ± 2.1% at month 3 (p = 0.04). The superior peripapillary hemifield also had a significant increase in VD, from 52.2% ± 2.8% at baseline to 53.4% ± 2.4% at month 1 (p = 0.007) and 53.7% ± 2.2% at month 3 (p = 0.03). Furthermore, the peripapillary vessels in the inferior temporal (p = 0.008), temporal superior (p = 0.009), and superior temporal (p = 0.013) sectors showed a significant increase of approximately 2% in SV VD from baseline to month 3 (Table 2).

Table 2.

Comparison of VD changes in small vessels of the RPC over the study period.

Small vessel VD (%)	Baseline, mean ± SD (range)	Month 1, mean ± SD (range)	Month 3, mean ± SD (range)	p-Value	Significant differences between visits
Whole image	49.6 ± 2.3 (42.4–53.3)	49.7 ± 2.2 (45.2–53.8)	50.0 ± 1.9 (46.2–54.0)	0.23
Inside disc	48.3 ± 5.1 (36.2–55.8)	47.8 ± 4.8 (35.9–56.8)	46.3 ± 5.7 (34.3–57.1)	0.06
Whole peripapillary	52.1 ± 2.9 (44.3–56.4)	52.5 ± 2.5 (47.6–56.9)	53.1 ± 2.1 (47.7–56.4)	0.007*	Baseline vs. month 3, p = 0.04
Peripapillary superior hemifield	52.5 ± 2.8 (45.1–56.7)	53.2 ± 2.4 (48.2–57)	53.7 ± 2.2 (49.3–57.6)	0.01*	Baseline vs. month 1, p = 0.007; month 1 vs. 3, p = 0.03
Peripapillary inferior hemifield	51.5 ± 3.5 (43.4–56.8)	51.8 ± 3.1 (45.6 ± 56.8)	52.5 ± 2.9 (46.1–56.8)	0.07
Peripapillary nasal superior	49.7 ± 3.9 (40.3–56.6)	49.9 ± 3.4 (44.3–55.5)	50.4 ± 3.7 (43.4–57.4)	0.18
Peripapillary nasal inferior	47.9 ± 4.5 (37.1–54.5)	47.0 ± 3.9 (39.7–53.9)	47.8 ± 3.8 (40.2–54.3)	0.9
Peripapillary inferior nasal	49.5 ± 4.5 (38.1–57.2)	49.6 ± 4.4 (41.5–57.9)	51.1 ± 4.1 (41.9–58)	0.06
Peripapillary inferior temporal	57.7 ± 3.8 (49.6–67.1)	58.9 ± 3.6 (53.7–66.7)	59.5 ± 3.1 (54.1–65.2)	0.008*	Baseline vs. month 3, p = 0.02
Peripapillary temporal inferior	53.5 ± 4.1 (39.3–59.4)	53.1 ± 5.3 (34.9–59.4)	53.7 ± 4.9 (36.8–59.9)	0.68
Peripapillary temporal superior	56.5 ± 3.7 (49.9–64.1)	57.3 ± 2.9 (52.0–63.0)	57.1 ± 3.3 (48.7–62.0)	0.009*	Baseline vs. month 2, p = 0.007
Peripapillary superior temporal	55.7 ± 3.7 (48.6–62.0)	56.8 ± 3.9 (47.9–63.8)	57.7 ± 3.0 (50.0–62.0)	0.013*	Baseline vs. month 3, p = 0.04
Peripapillary superior nasal	49.7 ± 4.4 (37.3–58.1)	50.3 ± 3.8 (40.9–57.1)	51.5 ± 3.2 (41.3–57.4)	0.06

RPC, radial peripapillary capillary; SD, standard deviation; VD, vessel density.

In contrast to the increase of RPC SV VD, the inside disc AV VD significantly decreased from 57.9% ± 4.6% at baseline to 55.4% ± 5.9% at month 3 (p = 0.037). However, the grid-based inferior AV VD significantly increased over this period (p = 0.03) (Table 3).

Table 3.

Comparison of VD changes in all vessels, including both small and large vessels, of the RPC of COVID-19 patients over the study period.

All vessel VD (%)	Baseline, mean ± SD (range)	Month 1, mean ± SD (range)	Month 3, mean ± SD (range)	p-Value	Significant differences between visits
Whole image	55.9 ± 2.2 (48.2–59.6)	55.9 ± 2.2 (50.4–58.8)	55.9 ± 2.08 (50.9–59.3)	0.9
Inside disc	57.9 ± 4.6 (48.3–64.1)	57.3 ± 3.6 (51.2–65)	55.4 ± 5.9 (41.7–64.1)	0.019*	Baseline vs. month 3, p = 0.037
Whole peripapillary	58.3 ± 2.5 (51.4–62.4)	58.6 ± 2.2 (54.0–61.6)	58.8 ± 2.1 (54.6–61.9)	0.11
Peripapillary superior hemifield	58.8 ± 2.4 (51.8–62.5)	59.2 ± 1.2 (54.8–62)	59.5 ± 2.1 (55–62.9)	0.09
Peripapillary inferior hemifield	57.7 ± 2.9 (50.9–62.9)	57.8 ± 2.8 (51.8–61.4)	58.2 ± 2.6 (52.3–61.7)	0.27
Grid-based superotemporal	58.1 ± 2.5 (52.1–62.9)	58.2 ± 2.8 (54.3–65.2)	58.4 ± 2.8 (49.3–63.7)	0.48
Grid-based temporal	56.1 ± 3.2 (49.7–62.5)	56.1 ± 3.2 (47.2–60.7)	56.1 ± 3.1 (48.7–59.8)	0.76
Grid-based inferotemporal	58.0 ± 3.0 (52.1–64.1)	57.4 ± 2.9 (50.4–61.9)	58.2 ± 3.2 (50.9–65.1)	0.52
Grid-based superior	57.9 ± 3.5 (51.3–64.4)	58.8 ± 3.3 (52.4–65)	58.8 ± 3.0 (48.9–63.2)	0.78
Grid-based central	58.9 ± 3.9 (48.4–63.8)	58.3 ± 3.1 (52.3–65)	56.8 ± 5.4 (44.5–65.3)	0.09
Grid-based inferior	60.9 ± 3.9 (47.0–66.1)	61.1 ± 4.2 (50.4–67.6)	61.9 ± 3.5 (53–66.9)	0.04*	Baseline vs. month 3, p = 0.03
Grid-based superonasal	52.2 ± 4.2 (39.3–58.4)	52.5 ± 3.7 (39.9–58)	52.5 ± 4.1 (43.1–58.4)	0.73
Grid-based nasal	52.2 ± 3.3 (44.4–56.9)	51.2 ± 3.4 (42.8–56)	51.8 ± 2.9 (42.8–58.4)	0.65
Grid-based inferonasal	49.8 ± 3.9 (37.9–54.9)	49.2 ± 4.2 (40.1–55.5)	50.1 ± 4.0 (41.5–55.7)	0.9

COVID-19, coronavirus disease 2019; RPC, radial peripapillary capillary; SD, standard deviation; VD, vessel density.

Discussion

In the present observational study, 34 eyes were evaluated for ONH and VD changes in 17 otherwise-healthy individuals who had previously recovered from mild COVID-19. OCTA imaging was performed at baseline and at 1 and 3 months. There were no significant changes in ONH parameters. In the RPC SV VD evaluations, all parameters except for the inside disc values tended to increase. However, these increases in SV VD values were only significant in the peripapillary whole, superior hemifield, inferior temporal, temporal superior, and superior temporal regions. Conversely, the RPC AV VD values did not show any trend toward an increase. However, the inside disc AV VD decreased from baseline to 3 months, whereas the grid-based inferior AV VD value significantly increased.

SARS-CoV-2 has been detected in various eye parts, including the ocular surface, anterior chamber, and retina. The virus-binding receptor (i.e., ACE2) in different ocular cell types may contribute to the ocular manifestations of COVID-19.^9,23,24 In addition, the virus can activate the renin–angiotensin–aldosterone system, leading to endothelial dysfunction. These pathophysiological changes can result in both microvascular and macrovascular alterations in the retina.²⁵

Previous studies have investigated the correlations between systemic or ocular diseases and VD of the macular region or ONH. In a cross-sectional study involving 1487 participants, Zhu et al. reported that a decrease in ONH VD was associated with increasing age, longer axial length, male sex, lower signal strength index, and higher blood pressure.²⁶ In addition, reduced ONH VD has been observed in patients with glaucoma, diabetes mellitus, and subcortical vascular cognitive impairment.^27–29

There is limited research into changes in macular VD following COVID-19.^20,30,31 Some studies have reported ONH changes after COVID-19. For example, in a case–control study, Cennamo et al. evaluated the macular and peripapillary VD of 40 patients after 6 months of recovery from COVID-19, and found a significant reduction in peripapillary VD.³¹ However, in a prospective exploratory investigation of 90 subjects with severe COVID-19, Burgos-Blasco et al. used OCTA to evaluate peripapillary VD at 4 and 12 weeks after diagnosis; they reported no changes in peripapillary VD in the early months after COVID-19.³² Conversely, an observational case–control study of 80 subjects who recovered from COVID-19 revealed lower peripapillary perfusion density in the COVID-19 group.¹⁸ In addition, Guemes-Villahoz et al. reported a significant increase in peripapillary VD in a cross-sectional case–control study of 27 children at 4 to 8 weeks after recovery from COVID-19.³³

In a previous cross-sectional case–control study, we analyzed peripapillary VD changes in 25 COVID-19 patients (16 outpatients and nine hospitalized patients). We observed no significant differences in ONH parameters between the two groups. However, when we compared AV VD and SV VD values, there was a significant decrease in whole SV VD, inferior temporal SV VD, superior nasal SV VD, inferior nasal SV VD, and grid-based inferior sector AV VD values in the COVID-19 group. Furthermore, the inside disc SV VD in the COVID-19 group showed a significant increase.²¹ Based on these findings, we aimed to evaluate the longitudinal changes in ONH parameters following COVID-19 in the present study.

It is worth noting that the AngioVue OCTA device demonstrates good repeatability, with a within-subject standard deviation of 0.065 for ONH VD measurement in healthy subjects.³⁴ Our study demonstrated significant changes in ONH VD, of approximately 1% to 2%. Nonetheless, it is essential to highlight that these changes were observed in patients with 20/20 visual acuity and no neurological signs or symptoms.

Inconsistencies in previous findings led us to conduct the current longitudinal study to assess changes in the ONH in COVID-19 patients. Our findings indicate that healthy patients who have recovered from COVID-19 have increased peripapillary SV VD values, which may be used as an index to support the vascular nature of COVID-19 pathophysiology. Furthermore, the use of OCTA provides a non-invasive tool to demonstrate ongoing vascular activity in the disease. ONH alterations following COVID-19 should therefore be considered in ONH assessments for other conditions, such as patients with suspected glaucoma or conditions that cause optic disc swelling.

The optic nerve and its blood vessels can be examined through ophthalmic examination and imaging, which may reveal changes in the central nervous and vascular systems. Given that the optic nerve is part of the central nervous system, changes in the optic nerve may indicate the importance of evaluating both small and large brain vessels using various techniques such as magnetic resonance angiography. This will provide valuable information about how COVID-19 affects the vascular system.

In conclusion, our study sought to examine the impact of COVID-19 on ONH VD and other parameters, which were assessed using OCTA. We identified a notable increase in ONH SV VD. However, further investigations are necessary to validate the potential reversibility of these findings. Our study involved a limited group of middle-aged, otherwise-healthy individuals who had recuperated from COVID-19 without complications. Furthermore, our follow-up duration spanned just 3 months, and subsequent follow-up inquiries may elucidate the transient or enduring natures of these alterations. Although our study represents the inaugural longitudinal exploration of ONH VD variations in COVID-19-recovered individuals without complications, our findings are not broadly applicable to severe COVID-19 cases. Prospective studies integrating an age-matched control group and patients exhibiting severe COVID-19 symptoms may allow for a more comprehensive understanding of the influence of COVID-19 on ONH VD.

Footnotes

Acknowledgements

The authors are grateful to the research participants and all hospital staff who took interest in and helped with the study.

Author contributions

MoA and HRH designed the study, supervised the project, and performed ophthalmic examinations. HRH, KH, KB, and PS collected the data. KH and NA performed the statistical analysis. HRH, MaA, SMH, and MoA wrote and revised the main manuscript text. All the authors read and approved the final manuscript.

Declaration of conflicting interest

The authors declare that there is no conflict of interest.

Funding

The authors would like to acknowledge the financial support of the Vice-Chancellor of Research of Mashhad University of Medical Sciences for this research project (code: 990823). The funding organization had no role in the design or conduct of this research.

ORCID iD

Hamid Reza Heidarzadeh

References

Huang

Wang

, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395: 497–506. DOI: 10.1016/s0140-6736(20)30183-5.

Palmieri

Palmer

Lo Noce

, Italian National Institute of Health COVID-19 Mortality Group (*)et al. Differences in the clinical characteristics of COVID-19 patients who died in hospital during different phases of the pandemic: national data from Italy. Aging Clin Exp Res 2021; 33: 193–199. DOI: 10.1007/s40520-020-01764-0.

Ahn

Shin

Kim

, et al. Current status of epidemiology, diagnosis, therapeutics, and vaccines for novel coronavirus disease 2019 (COVID-19). J Microbiol Biotechnol 2020; 30: 313–324. DOI: 10.4014/jmb.2003.03011.

Singh

Pritam

Pandey

, et al. Microstructure, pathophysiology, and potential therapeutics of COVID‐19: a comprehensive review. J Med Virol 2021; 93: 275–299. DOI: 10.1002/jmv.26254.

Klok

Kruip

Van der Meer

, et al. Confirmation of the high cumulative incidence of thrombotic complications in critically ill ICU patients with COVID-19: an updated analysis. Thromb Res 2020; 191: 148–150. DOI: 10.1016/j.thromres.2020.04.041.

Becker

RC.

COVID-19 update: Covid-19-associated coagulopathy. J Thromb Thrombolysis 2020; 50: 54–67. DOI: 10.1007/s11239-020-02134-3.

Lam

DSC

Chen

, et al. Novel coronavirus disease 2019 (COVID-19): the importance of recognising possible early ocular manifestation and using protective eyewear. Br J Ophthalmol 2020; 104: 297–298. DOI: 10.1136/bjophthalmol-2020-315994.

Mungmungpuntipantip

Wiwanitkit

Ocular manifestation, eye protection, and COVID-19. Graefes Arch Clin Exp Ophthalmol 2020; 258: 1339. DOI: 10.1007/s00417-020-04662-3.

Casagrande

Fitzek

Püschel

, et al. Detection of SARS-CoV-2 in human retinal biopsies of deceased COVID-19 patients. Ocul Immunol Inflamm 2020; 28: 721–725. DOI: 10.1080/09273948.2020.1770301.

10.

Zhou

Zhang

, et al. Expressions and significances of the angiotensin-converting enzyme 2 gene, the receptor of SARS-CoV-2 for COVID-19. Mol Biol Rep 2020; 47: 4383–4392. DOI: 10.1007/s11033-020-05478-4.

11.

Sun

, et al. Atlas of ACE2 gene expression in mammals reveals novel insights in transmission of SARS-CoV-2. Heliyon 2021; 7: e05850. DOI: 10.1016/j.heliyon.2020.e05850.

12.

Hamming

Timens

Bulthuis

, et al. Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis. J Pathol 2004; 203: 631–637. DOI: 10.1002/path.1570.

13.

Zhou

Kang

, et al. Understanding the neurotropic characteristics of SARS-CoV-2: from neurological manifestations of COVID-19 to potential neurotropic mechanisms. J Neurol 2020; 267: 2179–2184. DOI: 10.1007/s00415-020-09929-7.

14.

Choudhary

Kapoor

Singh

, et al. Therapeutic targets of renin-angiotensin system in ocular disorders. J Curr Ophthalmol 2017; 29: 7–16. DOI: 10.1016/j.joco.2016.09.009.

15.

Abrishami

Tohidinezhad

Daneshvar

, et al. Ocular manifestations of hospitalized patients with COVID-19 in northeast of Iran. Ocul Immunol Inflamm 2020; 28: 739–744. DOI: 10.1080/09273948.2020.1773868.

16.

Olson

Ghosh

Zhang

AY.

Ophthalmic manifestations of coronavirus disease 2019 and ocular side effects of investigational pharmacologic agents. Curr Opin Ophthalmol 2020; 31: 403–415. DOI: 10.1097/icu.0000000000000682.

17.

Marinho

Marcos

AAA

Romano

, et al. Retinal findings in patients with COVID-19. Lancet 2020; 395: 1610. DOI: 10.1016/s0140-6736(20)31014-x.

18.

Savastano

Gambini

Cozzupoli

, et al. Retinal capillary involvement in early post-COVID-19 patients: a healthy controlled study. Graefes Arch Clin Exp Ophthalmol 2021; 259: 2157–2165. DOI: 10.1007/s00417-020-05070-3.

19.

Landecho

Yuste

Gándara

, et al. COVID-19 retinal microangiopathy as an in vivo biomarker of systemic vascular disease? J Intern Med 2021; 289: 116–120. DOI: 10.1111/joim.13156.

20.

Abrishami

Emamverdian

Shoeibi

, et al. Optical coherence tomography angiography analysis of the retina in patients recovered from COVID-19: a case-control study. Can J Ophthalmol 2021; 56: 24–30. DOI: 10.1016/j.jcjo.2020.11.006.

21.

Abrishami

Daneshvar

Emamverdian

, et al. Optic nerve head optical coherence tomography angiography findings after coronavirus disease. J Ophthalmic Vis Res 2021; 16: 592–601. DOI: 10.18502/jovr.v16i4.9749.

22.

Von Elm

Altman

Egger

, STROBE Initiativeet al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med 2007; 147: 573–577. DOI: 10.7326/0003-4819-147-8-200710160-00010.

23.

Willcox

Walsh

Nichols

, et al. The ocular surface, coronaviruses and COVID-19. Clin Exp Optom 2020; 103: 418–424. DOI: 10.1111/cxo.13088.

24.

Yan

Diao

Liu

, et al. Severe acute respiratory syndrome coronavirus 2 nucleocapsid protein in the ocular tissues of a patient previously infected with coronavirus disease 2019. JAMA Ophthalmol 2020; 138: 1201–1204. DOI: 10.1001/jamaophthalmol.2020.3962.

25.

Siddiqi

Libby

Ridker

PM.

COVID-19 – a vascular disease. Trends Cardiovasc Med 2021; 31: 1–5. DOI: 10.1016/j.tcm.2020.10.005.

26.

Zhu

Choy

BNK

You

, et al. Optic disc and peripapillary vessel density measured with optical coherence tomography angiography and its associations in Chinese adults: a large population-based study. Br J Ophthalmol 2021; 106: 1411–1416. DOI: 10.1136/bjophthalmol-2020-318199.

27.

Huang

, et al. Vessel density in the macular and peripapillary areas in preperimetric glaucoma to various stages of primary open-angle glaucoma in Taiwan. J Clin Med 2021; 10: 5490. DOI: 10.3390/jcm10235490.

28.

Zhang

Jia

, et al. Quantitative analysis of the RPC vessel density and the RNFL thickness in patients with type 2 diabetes mellitus by using OCT angiography. Ophthalmic Res 2021; 64: 951–959. DOI: 10.1159/000517145.

29.

Lee

Kim

Jang

, et al. Optical coherence tomography angiography as a potential screening tool for cerebral small vessel diseases. Alz Res Therapy 2020; 12: 73. DOI: 10.1186/s13195-020-00638-x.

30.

González-Zamora

Bilbao-Malavé

Gándara

, et al. Retinal microvascular impairment in COVID-19 bilateral pneumonia assessed by optical coherence tomography angiography. Biomedicines 2021; 9: 247. DOI: 10.3390/biomedicines9030247.

31.

Cennamo

Reibaldi

Montorio

, et al. Optical coherence tomography angiography features in post-COVID-19 pneumonia patients: a pilot study. Am J Ophthalmol 2021; 227: 182–190. DOI: 10.1016/j.ajo.2021.03.015.

32.

Burgos-Blasco

Güemes-Villahoz

Vidal-Villegas

, et al. Optic nerve head vessel density assessment in recovered COVID-19 patients: a prospective study using optical coherence tomography angiography. J Glaucoma 2021; 30: 711–717. DOI: 10.1097/IJG.0000000000001858.

33.

Guemes-Villahoz

Burgos-Blasco

Perez-Garcia

, et al. Retinal and peripapillary vessel density increase in recovered COVID-19 children by optical coherence tomography angiography. J AAPOS 2021; 25: 325.e1–325.e6. DOI: 10.1016/j.jaapos.2021.06.004.

34.

Kee

Yip

VCH

Tay

ELT

, et al. Comparison of two different optical coherence tomography angiography devices in detecting healthy versus glaucomatous eyes – an observational cross-sectional study. BMC Ophthalmol 2020; 20: 440. DOI: 10.1186/s12886-020-01701-9.

Optic nerve head alterations after COVID-19: an optical coherence tomography angiography-based longitudinal study

Abstract

Objective

Methods

Results

Conclusion

Keywords

Introduction

Methods

Study participants

Ethical considerations

Imaging technique

Statistical analysis

Results

Discussion

Footnotes

Acknowledgements

Author contributions

Declaration of conflicting interest

Funding

ORCID iD

References