Eales’ Disease in Inuit: A Short Report and Clinical Update
Bibliographic record
Abstract
Purpose: We report a case of Eales disease in Inuit and reflect on advances in telemedicine and treatment of retinal disease since the first report of Eales' disease in Greenlandic Inuit was published. Patients and Methods: A 41-year-old Inuit female complaining of blurred vision was referred to our eye department. There had been no sign of diabetic retinopathy during diabetic eye screening and the patient had been treated for tuberculosis in 2010. Telemedical assessment was suspicious for vitritis or vitreous hemorrhage in the right eye, and the patient was flown from Greenland to Denmark, where examination revealed mild vitritis in the right eye, vitreous hemorrhage in the left eye and retinal neovascularization in both eyes. Fundus fluorescein angiography showed vessel leakage and areas of retinal non-perfusion. There was left epiretinal membrane with retinal thickening on macular optical coherence tomography. Results: Based on the patient's clinical findings and history of tuberculosis infection, a diagnosis of Eales' disease was made. The left eye was treated with pars plana vitrectomy with epiretinal membrane peeling, endodiathermy and endolaser. The right eye was treated in outpatients with sectoral laser photocoagulation. At seven weeks' follow-up, the visual acuity had improved from 6/12 to 6/6 (right eye) and from 6/36 to 6/7.5 (left eye). Conclusion: The prevalence of tuberculosis in Greenland is very high and it is recommended that clinicians remain alert to the possibility of Eales' disease, as beneficial visual outcomes are associated with prompt diagnosis and treatment. Telemedicine allows more frequent follow-up of Greenlander patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".