Age Effects on Retinal Blood Flow Assessed Using Spectral-Domain Optical Coherence Tomography Doppler
Bibliographic record
Abstract
Purpose: : To determine the impact of healthy aging upon total retinal blood flow as derived by Spectral-Domain, Optical Coherence Tomography Doppler SD-OCT. Methods: : SD-OCT Doppler blood flow was non-invasively measured using the RTVue system (Optovue Inc., USA). One eye of each of 6 healthy young (mean age 25.7; SD 3.5 years) and 6 healthy elderly (mean age 63.5; SD 1.8 years) subjects was randomly selected for the study and dilated using Mydriacyl 1%. A double circular scanning pattern was employed. A minimum of six separate SD-OCT Doppler measurements (i.e. each separate measurement comprising a superior nasal pupil scan and an inferior nasal pupil scan) were acquired. Total retinal blood flow was calculated, using data from valid scans only, by summing flow from all detectable venules. Results: : 117 of 170 images (68.82%) were determined to be valid using the DOCTORC software (Centre for Ophthalmic Optics and Lasers, CA, USA). Mean total retinal blood flow for the young group was 44.96±15.59 µl/min, while for the elderly group it was 39.45±13.20 µl/min. Two-sided t-test showed no significant difference between both groups (p=0.52). Linear regression analysis showed no significant correlation between total retinal blood flow and age (r=-0.31, p=0.33). Conclusions: : Preliminary data acquired using SD-OCT Doppler shows no significant difference in retinal blood flow between a young and elderly group.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".