Structural Features of Patients with Drusen-like Deposits and Systemic Lupus Erythematosus
Bibliographic record
Abstract
Background: The relevance of drusen-like deposits (DLD) in patients with systemic lupus erythematosus (SLE) is to a large extent uncertain. Their genesis is proposed to be correlated to immune-complex and complement depositions in the framework of SLE. The intention of this study was to determine potential morphological differences in the choroid and retina as well as potential microvascular changes comparing two cohorts of SLE patients divergent in the presence or absence of DLD using multimodal imaging. Methods: Both eyes of 16 SLE patients with DLD were compared to an age- and sex-matched control-group consisting of 16 SLE patients without detectable DLD. Both cohorts were treated with hydroxychloroquine (HCQ) and did not differ in the treatment duration or dosage. Using spectral-domain optical coherence tomography (SD-OCT) choroidal volume measures, choroidal vascularity indices (CVI) and retinal layer segmentation was performed and compared. In addition, by the exploitation of optical coherence tomography angiography vascular density, perfusion density of superficial and deep retinal capillary plexuses and the choriocapillaris were analyzed. For the choroidal OCT-scans, a subset of 51 healthy individuals served as a reference-group. Results: CVI measures revealed a significant reduction in eyes with DLD compared to healthy controls (0.56 (0.54−0.59) versus 0.58 (0.57−0.59) (p = 0.018) and 0.56 (0.54−0.58) versus 0.58 (0.57−0.60) (p < 0.001)). The photoreceptor cell layer presented significant thinning in both eyes of subjects with DLD compared to control subjects without DLD (68.8 ± 7.7 µm vs. 77.1 ± 7.3 µm for right eyes, p = 0.008, and 66.5 ± 10.5 µm vs. 76.1 ± 6.3 µm for left eyes, p = 0.011). OCTA scans revealed no significant changes, yet there could be observed numerically lower values in the capillary plexuses of the retina in eyes with DLD than in eyes without DLD. Conclusions: Our results illustrated significant alterations in the choroidal and retinal analyzes, suggesting a correlation between DLD and the progression of inflammatory processes in the course of SLE leading to retinal degeneration. For this reason, DLD could serve as a biomarker for a more active state of disease.
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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 | 0.001 |
| 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) | 0.002 | 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".