ArticleScientific reports2025
Identifying biomarkers for papilledema and pseudopapilledema.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Clinician-Led Code-Free Deep Learning for Detecting Papilledema and Pseudopapilledema Using Optic Disc Imaging.Translational vision science & technology · 2026Article
- Peripapillary Choroidal Vascularity Index for Differentiating Papilledema from Pseudopapilledema: A Deep Learning-Based Approach.Ophthalmology science · 2026Article
- Ocularultrasound versus SD-OCT in early papilledema differentiation.Bioinformation · 2026Article
- Neuroretinal damage associated with pituitary macroadenoma: endocrine and radiological predictors and correlation with optical coherence tomography-derived biomarkers.Frontiers in endocrinology · 2026Observational
- Validity of optical coherence tomography angiography in the differential diagnosis of papilledema and pseudopapilledema.Journal of optometryArticle
Corrections and comments
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Authors and funding
18 authors.
Funding
Abstract
Papilledema describes optic nerve head (ONH) swelling due to raised intracranial pressure which can lead to complications including visual loss. Differentiating it from pseudopapilledema is often challenging and may require invasive investigations. Optical Coherence Tomography (OCT) is a non-invasive imaging modality, allowing visualisation of the ONH. We identified OCT-derived biomarkers for papilledema and pseudopapilledema in the existing literature. 213 patients with confirmed papilledema, optic disc drusen (ODD), tilted optic discs (TOD) or crowded optic discs (COD) were included. OCT scans were analysed for qualitative and quantitative biomarkers, with sensitivity, specificity, and AUC calculated for individual and combined biomarkers. Logistic regression modelling including qualitative biomarkers to differentiate papilledema from ODD and COD demonstrated a sensitivity and specificity of 89% and AUC of 0.96. Inclusion of TOD reduced the sensitivity of the model to 66%. In a model differentiating papilledema from TOD, the best-performing biomarker achieved a sensitivity of 87%, specificity of 61% and AUC of 0.83. Using qualitative biomarkers, we identified a model with high sensitivity and specificity to differentiate papilledema from ODD and COD. Quantitative biomarkers displayed high AUCs for differentiating TOD from papilledema. Our findings show that OCT demonstrates promising utility in differentiating papilledema from pseudopapilledema.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.