Distinguishing Central Serous Chorioretinopathy From Neovascular Age-Related Macular Degeneration: A Prospective Study
Bibliographic record
Abstract
Purpose: This article identifies clinical features that differentiate central serous chorioretinopathy (CSR) from neovascular age-related macular degeneration (nAMD) and uses this information to develop a diagnostic tool. Methods: A prospective observational study was conducted of patients with a new diagnosis of CSR, nAMD, or indeterminate presentation. All patients underwent clinical assessment, axial length measurement, enhanced-depth imaging-optical coherence tomography, and intravenous fluorescein angiography. A final consensus diagnosis was derived following review of these factors. Results: < .001). The following odds ratio of CSR reached statistical significance: age 70 and younger (72.00, 95% CI: 11.99-432.50), subfoveal choroidal thickness greater than or equal to 300 µm (33.92, 95% CI: 4.06-283.18), dome-shaped neurosensory detachment (13.24, 95% CI: 3.22-54.45), retinal pigment epithelial changes (0.31, 95% CI: 0.10-0.97), subretinal hyperreflective material (0.11, 95% CI: 0.03-0.42), and fibrovascular pigment epithelial detachment (0.05, 95% CI: 0.01-0.47). A stepwise CSR vs nAMD clinical decision-making algorithm is proposed. Conclusions: Choroidal thickness is increased in CSR when compared with nAMD. The presented odds ratios and the CSR vs nAMD clinical decision-making tool can be applied to distinguish CSR from nAMD.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".