Prevalence, Demographics, and Treatment Characteristics of Visual Impairment due to Diabetic Macular Edema in a Representative Canadian Cohort
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Diabetic macular edema (DME) is the leading cause of blindness in the diabetic population. However, there is limited understanding of the epidemiology of DME with visual impairment (VI) and treatment in patients with diabetes in Canada. This observational, retrospective study used records from the Southwestern Ontario database to observe the demographics, prevalence, and treatment characteristics of VI due to DME compared to a healthy population in a real-world Canadian setting. Data was compared between a cohort of 8,368 diabetic (type 1 or 2) patients, who were ≥18 years old and had a diagnosis of DME with VI (visual acuity <20/40 in Snellen equivalent), and 76,077 age- and gender-matched subjects representing a healthy population. Among diabetic patients, prevalence of DME was 15.7%, and prevalence of VI due to DME was 2.56%. Laser monotherapy was the most frequently used treatment. Public funding covered costs for 85% of persons with DME while 18% were paid for with private funds. This study provides insight into the demographics, prevalence, and treatment of VI due to DME in a representative Canadian cohort. This data can help to inform evaluation of current DME treatment patterns and of proposed new treatment on drug plan budgets in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it