Retinopathy in sickle cell trait: Does it exist?
Bibliographic record
Abstract
Background: Patients with sickle cell trait and concomitant systemic disease are known to be at risk for proliferative retinopathy, However, there are reports of retinopathy in patients with sickle cell trait without systemic disease. There are no population-based studies addressing the risk of sickle cell retinopathy in this group. We performed a study to clarify the relation between sickle cell trait and retinopathy in healthy subjects. Methods: We reviewed the medical records of 100 children with sickle cell disease who attended the Sickle Cell Clinic at the Hospital for Sick Children, Toronto. We then contacted 200 parents with sickle cell trait, of whom 32 agreed to participate in the study. All participants were proven to have hemoglobin AS status with prior hemoglobin electrophoresis. An ophthalmologic history was obtained, and a complete ophthalmologic examination was performed. We defined sickle cell retinopathy as any salmon patch hemorrhages, iridescent spots, black sunbursts, retinal neovascularization or retinal detachment. The evaluation also included attempts to identify the more subtle signs of sickle cell retinopathy, such as optic nerve head vascular changes, vascular tortuosity, macular changes (e.g., microaneurysms and vascular loops) and peripheral arteriovenous anastamoses. Blood samples were obtained for complete blood count, reticulocyte count and smear. Results: We found no cases of sickle cell retinopathy among the 32 subjects. Ten of 30 subjects had a high reticulocyte count (greater than 120 × 109/L); however, there were no associated eye findings in this subgroup. Interpretation: Our results indicate that there is no increased risk of retinopathy in healthy people with sickle cell trait.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".