Macular microvasculature in patients with thyroid-associated orbitopathy: a cross-sectional study
Bibliographic record
Abstract
PURPOSE: The aim of this study was to evaluate macular blood flow in patients with thyroid-associated orbitopathy (TAO) as compared to healthy subjects. The inflammatory nature of the disease, as well as the vascular congestion caused by the increase in the volume of orbital soft tissue and extraocular muscles, rationalize the assessment of retinal blood flow changes in these patients. METHODS: This is a cross-sectional study with the convenience sampling method. Macular flow density was assessed using optical coherence tomography angiography (OCTA) and compared between patients with TAO and healthy individuals. We also compared macular flow density in two subgroups of patients based on clinical activity score (CAS). RESULTS: Eighty-five cases, including 30 healthy individuals and 55 patients with TAO, participated. The foveal avascular zone (FAZ) area was significantly larger in the patient group than in the control. Patients with active TAO with CAS 3 or more had significantly larger FAZ areas than those with CAS less than 3 (p = 0.04). CONCLUSION: We showed that the FAZ area is larger in active TAO patients and can be considered a possible candidate feature for monitoring disease activity and thyroid-associated vasculopathy.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".