Retinal Vascular Density Change in Patients With Aortic Valve Regurgitation
Bibliographic record
Abstract
Background: The aim of this study was to assess retinal vessel density in the superficial capillary plexus layer, deep capillary plexus layer and choriocapillaris plexus layer in patients with aortic valve regurgitation (AR) using optical coherence tomography angiography (OCTA). Methods: Thirty-eight healthy participants (group 1) and 38 patients with AR (group 2) were assessed for this study. Diagnosis of AR is made by transthoracic echocardiography (TTE). Severity of AR was assessed according to values in the 2014 American Heart Association/American College of Cardiology (AHA/ACC) valve guideline. Superficial capillary plexus density (SCPD), deep capillary plexus density (DCPD) and choriocapillaris plexus density (CCPD) were analyzed between groups using OCTA. Results: SCPD measurements were found to be decreased in the nasal, inferior and central regions of patients with AR (P ≤ 0.05). DCPD measurements were found to be decreased in the nasal and inferior regions of patients with AR (P ≤ 0.05). CCPD measurements were found to be decreased in the inferior and central regions of patients with AR (P ≤ 0.05). In patients with AR, CCPD measurements were significantly decreased in the inferior region compared to the control group. Central macular thickness was found to be significantly decreased in the patients with AR. Conclusions: Patients with AR showed decreased flow density compared with healthy controls. Retinal perfusion measured using OCTA in patients with AR may give an idea about microperfusion.
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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".