Ocular Health Screening in a Type 1 Diabetes Mellitus Population
Bibliographic record
Abstract
Background: Type 1 Diabetes Mellitus is among the most common conditions worldwide, affecting nearly 95 million children worldwide.One of the detrimental effects of this condition can be vision loss.Comprehensive annual ocular screenings can have an important role in early detection and management of vision-threatening complications.Over 2,200 family members and children with diabetes type 1 (www.childrenwithdiabetes.com)from Australia, Asia, Canada, Europe, Latin America and the United States of America attended an annual meeting where participants wishing to undergo a full ocular wellness screening had to pre-register for this weeklong activity.Methods: Sixteen (16) volunteer screeners made up of second year medical students, allied health care specialist, physician optometrist and ophthalmologist participated in this yearly event since 2007.Ocular wellness screening involved several stations where participants went through 8 stations, which included personal/family health history, visual acuity (Snellen visual chart), non-contact auto-tonometry for measurement of intra-ocular pressure, automated-refractor, and optical coherence tomography angiography (OCT and OCTA).The last station was a Canon non-mydriatic retinal camera used to acquire an anterior segment, as well as 45-degree fundus color and mono-chromatic auto fluorescence images (FAF).Results: Two hundred and sixteen (216) participants or 10% of the attendees (average age 21-years-old) underwent this screening event at the Disney Property in Orlando, Florida.Forty-one (41) participants had some retinal hemorrhages findings including microaneurysms, dot hemorrhages, flame hemorrhages and Intraretinal Microvascular Abnormalities (IrMa).Fifty-six (56) cases had varying levels of nuclear sclerosis.Three on-site readers evaluated all collected data and counseled families on findings.Participants with proliferative diabetic retinopathy findings or macular edema seen on OCT were referred to a remote off-site board-certified ophthalmologist through a secure line following Digital Imaging and Communications in Medicine (DICOM) and Health Insurance Portability and Accountability Act (HIPPA) protocols and recommended for further workup or treatment by the participant's eye-care professional.Conclusions: Creating a safe and comprehensive yearly ocular screening for children with type 1 diabetes mellitus along with a positive learning experience for can improve the lives of those living with type 1 diabetes and their families.Early detection, prevention and management of vision threatening diseases (VTDs) insures the affected individual can safeguard their vision.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".