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Record W4401183422 · doi:10.1177/03000605241263236

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

2024· article· en· W4401183422 on OpenAlexaff
Mojtaba Abrishami, Kiana Hassanpour, Kia Bayat, Seyedeh Maryam Hosseini, Nasibeh Amini, Majid Abrishami, Parham Sayyah Ensan, Hamid Reza Heidarzadeh

Bibliographic record

VenueJournal of International Medical Research · 2024
Typearticle
Languageen
FieldMedicine
TopicRetinal and Optic Conditions
Canadian institutionsUniversity of Toronto
FundersMashhad University of Medical Sciences
KeywordsMedicineOptic nerveOphthalmologyCoronavirus disease 2019 (COVID-19)Optical coherence tomographyNuclear medicinePathologyDisease

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.116
GPT teacher head0.494
Teacher spread0.378 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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